Mean zero artificial diffusion for stable finite element approximation of convection in cellular aggregate formation

Soheil Firooz, B. Daya Reddy, Vasily Zaburdaev, Paul Steinmann

We develop and implement finite element approximations for the coupled problem of cellular aggregate formation. The equation governing evolution of cell density is convective in nature, necessitating a modification of standard approaches to circumvent the instabilities associated with standard finite element approximations. To this end, a novel mean zero artificial diffusion approach is proposed, in which the classical artificial diffusion term is replaced by one that is orthogonal to its projection on to continuous functions. The resulting approach for the convective equation is shown to be well-posed. A range of numerical results illustrate the stability and accuracy of the new approach, and its behaviour in comparison with an alternative approach using Taylor–Hood elements. The results also provide insights into the behaviour of cellular aggregates in the context of the model studied here.

iSCAT microscopy and particle tracking with tailored spatial coherence

Mahdi Mazaheri, Kiarash Kasaian, David Albrecht, Jan Renger, Tobias Utikal, Cornelia Holler, Vahid Sandoghdar

Interferometric scattering (iSCAT) microscopy has demonstrated unparalleled performance among label-free optical methods for detecting and imaging isolated nanoparticles and molecules. However, when imaging complex structures such as biological cells, the superposition of the scattering fields from different locations of the sample leads to a speckle-like background, posing a significant challenge in deciphering fine features. Here, we show that by controlling the spatial coherence of the illumination, one can eliminate the spurious speckle without sacrificing sensitivity. We demonstrate this approach by positioning a rotating diffuser coupled with an adjustable lens and an iris in the illumination path. We report on imaging at a high frame rate of 25 kHz and across a large field of view of 100µm×100µm, while maintaining diffraction-limited resolution. We showcase the advantages of these features by three-dimensional (3D) tracking over 1000 vesicles in a single COS-7 cell and by imaging the dynamics of the endoplasmic reticulum (ER) network. Our approach opens the door to the combination of label-free imaging, sensitive detection, and 3D high-speed tracking using wide-field iSCAT microscopy.

Deep learning of many-body observables and quantum information scrambling

Naeimeh Mohseni, Junheng Shi, Tim Byrnes, Michael Hartmann

Machine learning has shown significant breakthroughs in quantum science, where in particular deep neural networks exhibited remarkable power in modeling quantum many-body systems. Here, we explore how the capacity of data-driven deep neural networks in learning the dynamics of physical observables is correlated with the scrambling of quantum information. We train a neural network to find a mapping from the parameters of a model to the evolution of observables in random quantum circuits for various regimes of quantum<br>scrambling and test its \textit{generalization} and \textit{extrapolation} capabilities in applying it to unseen circuits. Our results show that a particular type of recurrent neural network is extremely powerful in generalizing its predictions within the system size and time window that it has been trained on for both, localized and scrambled regimes. These include<br>regimes where classical learning approaches are known to fail in sampling from a representation of the full wave function. Moreover, the considered neural network succeeds in \textit{extrapolating} its predictions beyond the time window and system size that it has been trained on for models that show localization, but not in scrambled regimes.

0.7 MW Yb:YAG pumped degenerate optical parametric oscillator at 2.06 μm

Anni Li, Mehran Bahri, Robert M. Gray, Seowon Choi, Sajjad Hoseinkhani, Anchit Srivastava, Alireza Marandi, Hanieh Fattahi

Frequency comb and field-resolved broadband absorption spectroscopy are promising techniques for rapid, precise, and sensitive detection of short-lived atmospheric pollutants on-site. Enhancing detection sensitivity in absorption spectroscopy hinges on bright sources that cover molecular resonances and fast signal modulation techniques to implement lock-in detection schemes efficiently. Yb:YAG thin-disk lasers, combined with optical parametric oscillators (OPO), present a compelling solution to fulfill these requirements. In this work, we report on a bright OPO pumped by a Yb:YAG thin-disk Kerr-lens mode-locked oscillator delivering 2.8 W, 114 fs pulses at 2.06 {\mu}m with an averaged energy of 90 nJ. The OPO cavity operates at 30.9 MHz pulse repetition rates, the second harmonic of the pump cavity, allowing for broadband, efficient, and dispersion-free modulation of the OPO output pulses at 15.45 MHz rate. With 13% optical-to-optical conversion efficiency and a high-frequency intra-cavity modulation, this scalable scheme holds promise to advance the detection sensitivity and frontiers of field-resolved spectroscopic techniques.

Precision Quantum Parameter Inference with Continuous Observation

Bijita Sarma, Junxin Chen, Sangkha Borah

Quantum Parameter Estimation (QPE) is important from the perspective of both fundamental quantum research and various practical applications of quantum technologies such as for developing optimal quantum control strategies. Standard and traditional methods for QPE involve projective measurements on thousands of identically prepared quantum systems. However, these methods face limitations, particularly in terms of the required number of samples and the associated experimental resources. In this work, we present a novel method for precise QPE that diverges from conventional techniques, employs continuous measurements, and enables accurate QPE with a single quantum trajectory. In an application, we demonstrate the use of the method for the task of parameter estimation and force sensing of a levitated nanoparticle.

High-Resolution Cryogenic Spectroscopy of Single Molecules in Nanoprinted Crystals

Mohammad Musavinezhad, Jan Renger, Johannes Zirkelbach , Tobias Utikal, Claudio U. Hail, Thomas Basché, Dimos Poulikakos, Stephan Götzinger, Vahid Sandoghdar

We perform laser spectroscopy at liquid helium temperatures (T = 2 K) to investigate single dibenzoterrylene (DBT) molecules doped in anthracene crystals of nanoscopic height fabricated by electrohydrodynamic dripping. Using high-resolution fluorescence excitation spectroscopy, we show that zero-phonon lines of single molecules in printed nanocrystals are nearly as narrow as the Fourier-limited transitions observed for the same guest–host system in the bulk. Moreover, the spectral instabilities are comparable to or less than one line width. By recording super-resolution images of DBT molecules and varying the polarization of the excitation beam, we determine the dimensions of the printed crystals and the orientation of the crystals’ axes. Electrohydrodynamic printing of organic nano- and microcrystals is of interest for a series of applications, where controlled positioning of quantum emitters with narrow optical transitions is desirable.

Measuring Concentration of Nanoparticles in Polydisperse Mixtures Using Interferometric Nanoparticle Tracking Analysis

Anna D. Kashkanova, David Albrecht, Michelle Küppers, Martin Blessing, Vahid Sandoghdar

Quantitative measurements of nanoparticle concentration in liquid suspensions are in high demand, for example, in the medical and food industries. Conventional methods remain unsatisfactory, especially for polydisperse samples with overlapping size ranges. Recently, we introduced interferometric nanoparticle tracking analysis (iNTA) for high-precision measurement of nanoparticle size and refractive index. Here, we show that by counting the number of trajectories that cross the focal plane, iNTA can measure concentrations of subpopulations in a polydisperse mixture in a quantitative manner and without the need for a calibration sample. We evaluate our method on both monodisperse samples and mixtures of known concentrations. Furthermore, we assess the concentration of SARS-CoV-2 in supernatant samples obtained from infected cells.

Fully Non-Linear Neuromorphic Computing with Linear Wave Scattering

Clara C. Wanjura, Florian Marquardt

The increasing complexity of neural networks and the energy consumption associated with training and inference create a need for alternative neuromorphic approaches, e.g. using optics. Current proposals and implementations rely on physical non-linearities or opto-electronic conversion to realise the required non-linear activation function. However, there are significant challenges with these approaches related to power levels, control, energy-efficiency, and delays. Here, we present a scheme for a neuromorphic system that relies on linear wave scattering and yet achieves non-linear processing with a high expressivity. The key idea is to inject the input via physical parameters that affect the scattering processes. Moreover, we show that gradients needed for training can be directly measured in scattering experiments. We predict classification accuracies on par with results obtained by standard artificial neural networks. Our proposal can be readily implemented with existing state-of-the-art, scalable platforms, e.g. in optics, microwave and electrical circuits, and we propose an integrated-photonics implementation based on racetrack resonators that achieves high connectivity with a minimal number of waveguide crossings.

Discovering Local Hidden-Variable Models for Arbitrary Multipartite Entangled States and Arbitrary Measurements

Nick von Selzam, Florian Marquardt

Measurement correlations in quantum systems can exhibit non-local behavior, a fundamental aspect of quantum mechanics with applications such as device-independent quantum information processing. However, the explicit construction of local hidden-variable (LHV) models remains an outstanding challenge in the general setting. To address this, we develop an approach that employs gradient-descent algorithms from machine learning to find LHV models which reproduce the statis- tics of arbitrary measurements for quantum many-body states. In contrast to previous approaches, our method employs a general ansatz, enabling it to discover an LHV model in all cases where the state is local. Therefore, it provides actual estimates for the critical noise levels at which two-qubit Werner states and three-qubit GHZ and W states become non-local. Furthermore, we find evidence suggesting that two-spin subsystems in the ground states of translationally invariant Hamiltonians are local, while bigger subsystems are in general not. Our method now offers a quantitative tool for determining the regimes of non-locality in any given physical context, including scenarios involving non-equilibrium and decoherence.

Fourier-transform infrared spectroscopy with undetected photons from high-gain spontaneous parametric down-conversion

Kazuki Hashimoto, Dmitri B. Horoshko, Mikhail I. Kolobov, Yoad Michael, Ziv Gefen, Maria Chekhova

Fourier-transform infrared spectroscopy (FTIR) is an indispensable analytical method that allows label-free identification of substances via fundamental molecular vibrations. However, traditional FTIR spectrometers require mid-infrared (MIR) elements, including low-efficiency MIR photodetectors. SU(1,1) interferometry has previously enabled FTIR with undetected MIR photons via spontaneous parametric down-conversion in the low-parametric-gain regime, where the number of photons per mode is much less than one and sensitive photodetectors are needed. In this work, we develop a high-parametric-gain SU(1,1) interferometer for MIR-range FTIR with undetected photons. Using our method, we demonstrate three major advantages: a high photon number at the interferometer output, a considerably lower photon number at the sample, and improved interference contrast. In addition, we broaden the spectral range of the interferometer by aperiodic poling in the gain medium. Exploiting the broadband SU(1,1) interferometer, we measure and evaluate the MIR absorption spectra of polymers in the 3-μm region.

Mutation of the ALS-/FTD-Associated RNA-Binding Protein FUS Affects Axonal Development

Francesca W. van Tartwijk, Lucia C. S. Wunderlich, Ioanna Mela, Stanislaw Makarchuk, Maximilian A. H. Jakobs, Seema Qamar, Kristian Franze, Gabriele S. Kaminski Schierle, Peter H. St George-Hyslop, et al.

Aberrant condensation and localization of the RNA-binding protein (RBP) fused in sarcoma (FUS) occur in variants of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Changes in RBP function are commonly associated with changes in axonal cytoskeletal organization and branching in neurodevelopmental disorders. Here, we asked whether branching defects also occur in vivo in a model of FUS-associated disease. We use two reported Xenopus models of ALS/FTD (of either sex), the ALS-associated mutant FUS(P525L) and a mimic of hypomethylated FUS, FUS(16R). Both mutants strongly reduced axonal complexity in vivo. We also observed an axon looping defect for FUS(P525L) in the target area, which presumably arises due to errors in stop cue signaling. To assess whether the loss of axon complexity also had a cue-independent component, we assessed axonal cytoskeletal integrity in vitro. Using a novel combination of fluorescence and atomic force microscopy, we found that mutant FUS reduced actin density in the growth cone, altering its mechanical properties. Therefore, FUS mutants may induce defects during early axonal development.

Roadmap on photonic metasurfaces

Sebastian A. Schulz, Rupert. F. Oulton, Mitchell Kenney, Andrea Alù, Isabelle Staude, Ayesheh Bashiri, Zlata Fedorova, Radoslaw Kolkowski, A. Femius Koenderink, et al.

Here we present a roadmap on Photonic metasurfaces. This document consists of a number of perspective articles on different applications, challenge areas or technologies underlying photonic metasurfaces. Each perspective will introduce the topic, present a state of the art as well as give an insight into the future direction of the subfield.

Theory of symmetry-resolved quench-drive spectroscopy: Nonlinear response of phase-fluctuating superconductors

Matteo Puviani

Recent experiments on cuprates have shown the possibility of opening a gap above the superconducting critical temperature, in the so-called phase-fluctuating state, by enhancing the phase coherence of preformed Cooper pairs. Quench-drive spectroscopy, an implementation of 2D coherent spectroscopy, has emerged as a powerful tool for investigating out-of-equilibrium superconductors and their collective modes. In this paper, we enrich the quench-drive scheme by developing a systematic generalization to study the nonlinear response of d-wave incoherent Cooper pairs in a symmetry-resolved manner. In particular, we not only show that it is possible to obtain a third-harmonic signal from fully incoherent pairs with an equilibrium vanishing order parameter, but we also characterize the full flourishing 2D spectrum of the generated nonlinear response. The results provide a deeper theoretical insight on recent experimental results, opening the door to a symmetry-driven design of future experiments on unconventional and enhanced superconductors.

Merging automatic differentiation and the adjoint method for photonic inverse design

Alexander Luce, Rasoul Alaee, Fabian Knorr, Florian Marquardt

Optimizing the shapes and topology of physical devices is crucial for both scientific and technological advancements, given their wide-ranging implications across numerous industries and research areas. Innovations in shape and topology optimization have been observed across a wide range of fields, notably structural mechanics, fluid mechanics, and more recently, photonics. Gradient-based inverse design techniques have been particularly successful for photonic and optical problems, resulting in integrated, miniaturized hardware that has set new standards in device performance. To calculate the gradients, there are typically two approaches: namely, either by implementing specialized solvers using automatic differentiation (AD) or by deriving analytical solutions for gradient calculation and adjoint sources by hand. In this work, we propose a middle ground and present a hybrid approach that leverages and enables the benefits of AD for handling gradient derivation while using existing, proven but black-box photonic solvers for numerical solutions. Utilizing the adjoint method, we make existing numerical solvers differentiable and seamlessly integrate them into an AD framework. Further, this enables users to integrate the optimization environment seamlessly with other autodifferentiable components such as machine learning, geometry generation, or intricate post-processing which could lead to better photonic design workflows. We illustrate the approach through two distinct photonic optimization problems: optimizing the Purcell factor of a magnetic dipole in the vicinity of an optical nanocavity and enhancing the light extraction efficiency of a µLED.

Flying Particle Thermosensor in Hollow-Core Fiber Based on Fluorescence Lifetime Measurements

Jasper Freitag, Max Koeppel, Maria N. Romodina, Nicolas Joly, Bernhard Schmauß

Thermosensitive fluorescence lifetime measurements enable accurate thermometry independent of intensity fluctuations along the optical path. Here, we report lifetime-based temperature measurements of a single europium-doped particle optically trapped in an air-filled hollow-core fiber. A frequency-domain fluorescence lifetime measurement setup was integrated into a dual-beam optical trap. The measured apparent lifetime shows a linear temperature dependence of −1.8 µs/K for excitation at 400Hz . The results were repeatable over multiple cooling and heating cycles. In addition to temperature sensing, the influence of the high-power trapping laser on the measured apparent lifetime and fluorescence intensity was investigated. The observed laser-induced particle heating can be exploited to increase the fluorophore's sensitivity and operating range for low-temperature sensing. Fluorescence lifetime measurements of optically trapped particles inside a hollow-core fiber are promising for temperature sensing with micrometer spatial resolution over meter-scale distances.

Predicting atmospheric turbulence for secure quantum communications in free space

Tareq Jaouni, Lukas Scarfe, Frédéric Bouchard, Mario Krenn, Khabat Heshami, Francesco Di Colandrea, Ebrahim Karimi

Atmospheric turbulence is the main barrier to large-scale free-space quantum communication networks. Aberrations distort optical information carriers, thus limiting or preventing the possibility of establishing a secure link between two parties. For this reason, forecasting the turbulence strength within an optical channel is highly desirable, as it allows for knowing the optimal timing to establish a secure link in advance. Here, we train a Recurrent Neural Network, TAROCCO, to predict the turbulence strength within a free-space channel. The training is based on weather and turbulence data collected over 9 months for a 5.4 km intra-city free-space link across the City of Ottawa. The implications of accurate predictions from our network are demonstrated in a simulated high- dimensional Quantum Key Distribution protocol based on orbital angular momentum states of light across different turbulence regimes. TAROCCO will be crucial in validating a free-space channel to optimally route the key exchange for secure communications in real experimental scenarios.

Coherent pair injection as a route towards the enhancement of supersolid order in many-body bosonic models

Emmanouil Grigoriou, Zhiyao Ning, Hang Su, Benjamin Löckler, Ming Li, Yoshitomo Kamiya, Carlos Navarrete-Benlloch

Over the last couple of decades, quantum simulators have been probing quantum many-body physics with un- precedented levels of control. So far, the main focus has been on the access to novel observables and dynamical conditions related to condensed-matter models. However, the potential of quantum simulators goes beyond the traditional scope of condensed-matter physics: Being based on driven-dissipative quantum optical platforms, quantum simulators allow for processes that are typically not considered in condensed-matter physics. These processes can enrich in unexplored ways the phase diagram of well-established models. Taking the extended Bose-Hubbard model as the guiding example, in this work we examine the impact of coherent pair injection, a process readily available in, for example, superconducting circuit arrays. The interest behind this process is that, in contrast to the standard injection of single excitations, it can be configured to preserve the U(1) symmetry underlying the model. We prove that this process favors both superfluid and density-wave order, as opposed to insulation or homogeneous states, thereby providing a novel route towards the access of lattice supersolidity.

Revisiting N2 with Neural-Network-Supported CI

Yorick L. A. Schmerwitz, Louis Thirion, Gianluca Levi, Elvar Ö. Jónsson, Pavlo Bilous, Hannes Jónsson, Philipp Hansmann

We apply a recently proposed computational protocol for a neural-network-supported configura- tion interaction (NN CI) calculation to the paradigmatic N2 molecule. By comparison of correlation energy, binding energy, and the full dissociation curve to experimental and full CI benchmarks, we demonstrate the applicability and robustness of our approach for the first time in the context of molecular systems, and offer thereby a new complementary tool in the family of machine-learning- based computation methods. The main advantage of the method lies in the efficiency of the neural- network-selected many-body basis set. Specifically, we approximate full CI results obtained on bases of ≈ 1010 Slater Determinants with only ≈ 105 determinants with good accuracy. The high effi- ciency of the NN CI approach underlines its potential for broader applications such as structural optimizations and even computation of spectroscopic observables in systems for which computational resources are a limiting factor.

Tunable entangled photon-pair generation in a liquid crystal

Vitaliy Sultanov, Aljaž Kavčič, Emmanouil Kokkinakis, Nerea Sebastián, Maria Chekhova, Matjaž Humar

Liquid crystals, with their ability to self-assemble, strong response to an electric field and integrability into complex systems, are key materials in light-beam manipulation1. The recently discovered ferroelectric nematic liquid crystals2,3 also have considerable second-order optical nonlinearity, making them a potential material for nonlinear optics4,5. Their use as sources of quantum light could considerably extend the boundaries of photonic quantum technologies6. However, spontaneous parametric down-conversion, the basic source of entangled photons7, heralded single photons8 and squeezed light9, has so far not been observed in liquid crystals—or in any liquids or organic materials. Here we implement spontaneous parametric down-conversion in a ferroelectric nematic liquid crystal and demonstrate electric-field tunable broadband generation of entangled photons, with an efficiency comparable to that of the best nonlinear crystals. The emission rate and polarization state of photon pairs is markedly varied by applying a few volts or twisting the molecular orientation along the sample. A liquid-crystal source enables a special type of quasi-phase matching10, which is based on the molecular twist structure and is therefore reconfigurable for the desired spectral and polarization properties of photon pairs. Such sources promise to outperform standard nonlinear optical materials in terms of functionality, brightness and the tunability of the generated quantum state. The concepts developed here can be extended to complex topological structures, macroscopic devices and multi-pixel tunable quantum light sources.

Protected gap closing and reopening in topological-insulator Josephson junctions

Jakob Schluck, Ella Nikodem, Anton Montag, Alexander Ziesen, Mahasweta Bagchi, Fabian Hassler, Yoichi Ando

In the seminal proposal by Fu and Kane, the superconducting proximity effect was predicted to transform the surface state of a topological insulator (TI) into a topological superconduc- tor, forming a nonchiral 1D Majorana state within a linear Josephson junction on the TI surface. The hallmark of this 1D Majorana state is a robust gap closing as a function of the superconducting phase difference φ across the junction, which alternates in and out of the topological phase. These topological phase-transitions occur at φ = (2n + 1)π with integer n, leading to a 4π-periodicity of the ground state. While the 4π-periodicity has been indirectly inferred in the AC Josephson effect, the direct observation of the 1D Majorana state in a TI Josephson junction has remained contentious. Here, we report the direct observation of topological phase-transitions in a TI Josephson junction, where the local density of states is probed via tunnel contacts and φ is controlled by a flux loop. The observed transitions are independent of the chemical potential, reinforcing their topological origin. Under an applied perpendicular magnetic field, Josephson vortices form, making φ position-dependent. In this case, the gap closing occurs locally at the Josephson vortex cores where φ = (2n + 1)π, which we also observe. Our findings provide direct confirmation of the Fu-Kane proposal and ro- bust evidence for the emergence of topological superconductivity in a TI Josephson junction.

Quantum Equilibrium Propagation for efficient training of quantum systems based on Onsager reciprocity

Clara C. Wanjura, Florian Marquardt

The widespread adoption of machine learning and artificial intelligence in all branches of science and technology has created a need for energy-efficient, alternative hardware platforms. While such neuromorphic approaches have been proposed and realised for a wide range of platforms, physically extracting the gradients required for training remains challenging as generic approaches only exist in certain cases. Equilibrium propagation (EP) is such a procedure that has been introduced and applied to classical energy-based models which relax to an equilibrium. Here, we show a direct connection between EP and Onsager reciprocity and exploit this to derive a quantum version of EP. This can be used to optimize loss functions that depend on the expectation values of observables of an arbitrary quantum system. Specifically, we illustrate this new concept with supervised and unsupervised learning examples in which the input or the solvable task is of quantum mechanical nature, e.g., the recognition of quantum many-body ground states, quantum phase exploration, sensing and phase boundary exploration. We propose that in the future quantum EP may be used to solve tasks such as quantum phase discovery with a quantum simulator even for Hamiltonians which are numerically hard to simulate or even partially unknown. Our scheme is relevant for a variety of quantum simulation platforms such as ion chains, superconducting qubit arrays, neutral atom Rydberg tweezer arrays and strongly interacting atoms in optical lattices.

Training of Physical Neural Networks

Ali Momeni, Babak Rahmani, Benjamin Scellier, Logan G. Wright, Peter L. McMahon, Clara C. Wanjura, Yuhang Li, Anas Skalli, Natalia G. Berloff, et al.

Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research area with small-scale laboratory demonstrations, they are arguably one of the most underappreciated important opportunities in modern AI. Could we train AI models 1000x larger than current ones? Could we do this and also have them perform inference locally and privately on edge devices, such as smartphones or sensors? Research over the past few years has shown that the answer to all these questions is likely "yes, with enough research": PNNs could one day radically change what is possible and practical for AI systems. To do this will however require rethinking both how AI models work, and how they are trained - primarily by considering the problems through the constraints of the underlying hardware physics. To train PNNs at large scale, many methods including backpropagation-based and backpropagation-free approaches are now being explored. These methods have various trade-offs, and so far no method has been shown to scale to the same scale and performance as the backpropagation algorithm widely used in deep learning today. However, this is rapidly changing, and a diverse ecosystem of training techniques provides clues for how PNNs may one day be utilized to create both more efficient realizations of current-scale AI models, and to enable unprecedented-scale models.

Meta-Designing Quantum Experiments with Language Models

Sören Arlt, Haonan Duan, Felix Li, Sang Michael Xie, Yuhuai Wu, Mario Krenn

Artificial Intelligence (AI) has the potential to sig- nificantly advance scientific discovery by finding solutions beyond human capabilities. However, these super-human solutions are often unintuitive and require considerable effort to uncover under- lying principles, if possible at all. Here, we show how a code-generating language model trained on synthetic data can not only find solutions to specific problems but can create meta-solutions, which solve an entire class of problems in one shot and simultaneously offer insight into the underlying design principles. Specifically, for the design of new quantum physics experiments, our sequence-to-sequence transformer architec- ture generates interpretable Python code that de- scribes experimental blueprints for a whole class of quantum systems. We discover general and pre- viously unknown design rules for infinitely large classes of quantum states. The ability to automat- ically generate generalized patterns in readable computer code is a crucial step toward machines that help discover new scientific understanding – one of the central aims of physics.

Neural-network-supported basis optimizer for the configuration interaction problem in quantum many-body clusters: Feasibility study and numerical proof

Pavlo Bilous, Louis Thirion, Henri Menke, Maurits W. Haverkort, Adriana Pálffy, Philipp Hansmann

A deep-learning approach to optimize the selection of Slater determinants in configuration interaction calculations for condensed-matter quantum many-body systems is developed. We exemplify our algorithm on the discrete version of the single-impurity Anderson model with up to 299 bath sites. Employing a neural network classifier and active learning, our algorithm enhances computational efficiency by iteratively identifying the most relevant Slater determinants for the ground-state wave- function. We benchmark our results against established methods and investigate the efficiency of our approach as compared to other basis truncation schemes. Our algorithm demonstrates a substantial improvement in the efficiency of determinant selection, yielding a more compact and computationally manageable basis without compromising accuracy. Given the straightforward application of our neural network-supported selection scheme to other model Hamiltonians of quantum many-body clusters, our algorithm can significantly advance selective configuration interaction calculations in the context of correlated condensed matter.

Covariant operator bases for continuous variables

Aaron Z. Goldberg, Andrei B. Klimov, Gerd Leuchs, Luis Sanchez-Soto

Coherent-state representations are a standard tool to deal with continuous-variable systems, as they allow one to efficiently visualize quantum states in phase space. Here, we work out an alternative basis consisting of monomials on the basic observables, with the crucial property of behaving well under symplectic transformations. This basis is the analogue of the irreducible tensors widely used in the context of SU(2) symmetry. Given the density matrix of a state, the expansion coefficients in that basis constitute the multipoles, which describe the state in a canonically covariant form that is both concise and explicit. We use these quantities to assess properties such as quantumness or Gaussianity and to furnish direct connections between tomographic measurements and quasiprobability distribution reconstructions.

Solar lasers: Why not?

Michael Küblböck, Jonathan Will, Hanieh Fattahi

In this paper, we investigate the role of solar laser technology as a pivotal element in advancing sustainable and renewable energy. We begin by examining its wide-ranging applications across diverse fields, including remote communication, energy storage through magnesium production, and space exploration and communication. We address the current challenges faced by solar laser technology, which include the necessity for miniaturization, operation at natural sunlight intensity without the need for concentrated power, and efficient energy conversion. These improvements are essential to elevate their operational performance, beam quality, and cost-effectiveness. The promising prospects of space-based solar-pumped lasers and their potential role in magnesium generation for a sustainable energy future highlight some of the vast application opportunities that this novel technology could offer.

Generation and human-expert evaluation of interesting research ideas using knowledge graphs and large language models

Xuemei Gu, Mario Krenn

Advanced artificial intelligence (AI) systems with access to millions of research papers could inspire new research ideas that may not be conceived by humans alone. However, how interesting are these AI-generated ideas, and how can we improve their quality? Here, we introduce SciMuse, a system that uses an evolving knowledge graph built from more than 58 million scientific papers to generate personalized research ideas via an interface to GPT-4. We conducted a large-scale human evaluation with over 100 research group leaders from the Max Planck Society, who ranked more than 4,000 personalized research ideas based on their level of interest. This evaluation allows us to understand the relationships between scientific interest and the core properties of the knowledge graph. We find that data-efficient machine learning can predict research interest with high precision, allowing us to optimize the interest-level of generated research ideas. This work represents a step towards an artificial scientific muse that could catalyze unforeseen collaborations and suggest interesting avenues for scientists.

Transfer learning in predicting quantum many-body dynamics: from physical observables to entanglement entropy

Philipp Schmidt, Florian Marquardt, Naeimeh Mohseni

Deep neural networks have demonstrated remarkable efficacy in extracting meaningful representations from complex datasets. This has propelled representation learning as a compelling area of research across diverse fields. One interesting open question is how beneficial representation learning can be for quantum many-body physics, with its notouriosly high-dimensional state space. In this work, we showcase the capacity of a neural network that was trained on a subset of physical observables of a many-body system to partially acquire an implicit representation of the wave function. We illustrate this by demonstrating the effectiveness of reusing the representation learned by the neural network to enhance the learning process of another quantity derived from the quantum state. In particular, we focus on how the pre-trained neural network can enhance the learning of entanglement entropy. This is of particular interest as directly measuring the entanglement in a many-body system is very challenging, while a subset of physical observables can be easily measured in experiments. We show the pre-trained neural network learns the dynamics of entropy with fewer resources and higher precision in comparison with direct training on the entanglement entropy.

Hybrid architectures for terahertz molecular polaritonics

Ahmed Jaber, Michael Reitz, Avinash Singh, Ali Maleki, Yongbao Xin, Brian T. Sullivan, Ksenia Dolgaleva, Robert W. Boyd, Claudiu Genes, et al.

Atoms and their different arrangements into molecules are nature’s building blocks. In a regime of strong coupling, matter hybridizes with light to modify physical and chemical properties, hence creating new building blocks that can be used for avant-garde technologies. However, this regime relies on the strong confinement of the optical field, which is technically challenging to achieve, especially at terahertz frequencies in the far-infrared region. Here we demonstrate several schemes of electromagnetic field confinement aimed at facilitating the collective coupling of a localized terahertz photonic mode to molecular vibrations. We observe an enhanced vacuum Rabi splitting of 200 GHz from a hybrid cavity architecture consisting of a plasmonic metasurface, coupled to glucose, and interfaced with a planar mirror. This enhanced light-matter interaction is found to emerge from the modified intracavity field of the cavity, leading to an enhanced zero-point electric field amplitude. Our study provides key insight into the design of polaritonic platforms with organic molecules to harvest the unique properties of hybrid light-matter states.

Symmetry-induced higher-order exceptional points in two dimensions

Anton Montag, Flore K. Kunst

Exceptional points of order n (EPns) appear in non-Hermitian systems as points where the eigen- values and eigenvectors coalesce. Whereas EP2s generically appear in two dimensions (2D), higher- order EPs require a higher-dimensional parameter space to emerge. In this work, we provide a complete characterization the appearance of symmetry-induced higher-order EPs in 2D parameter space. We find that besides EP2s only EP3s, EP4s, and EP5s can be stabilized in 2D. Moreover, these higher-order EPs must always appear in pairs with their dispersion determined by the sym- metries. Upon studying the complex spectral structure around these EPs, we find that depending on the symmetry, EP3s are accompanied by EP2 arcs, and 2- and 3-level open Fermi structures. Similarly, EP4s and closely related EP5s, which arise due to multiple symmetries, are accompanied by exotic EP arcs and open Fermi structures. For each case, we provide an explicit example. We also comment on the topological charge of these EPs, and discuss similarities and differences between symmetry-protected higher-order EPs and EP2s.

Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning

Maximilian Nägele, Jan Olle, Thomas Fösel, Remmy Zen, Florian Marquardt

Markov decision processes (MDPs) are used to model a wide variety of applications ranging from game playing over robotics to finance. Their optimal policy typically maximizes the expected sum of rewards given at each step of the decision process. However, a large class of problems does not fit straightforwardly into this framework: Non-cumulative Markov decision processes (NCMDPs), where instead of the expected sum of rewards, the expected value of an arbitrary function of the rewards is maximized. Example functions include the maximum of the rewards or their mean divided by their standard deviation. In this work, we introduce a general mapping of NCMDPs to standard MDPs. This allows all techniques developed to find optimal policies for MDPs, such as reinforcement learning or dynamic programming, to be directly applied to the larger class of NCMDPs. Focusing on reinforcement learning, we show applications in a diverse set of tasks, including classical control, portfolio optimization in finance, and discrete optimization problems. Given our approach, we can improve both final performance and training time compared to relying on standard MDPs.

Nonlinear dynamics of femtosecond laser interaction with the central nervous system in zebrafish

Soyeon Jun, Andreas Herbst, Kilian Scheffter, Nora John, Julia Kolb, Daniel Wehner, Hanieh Fattahi

Understanding the photodamage mechanism underlying the highly nonlinear dynamic of femtosecond laser pulses at the second transparent window of tissue is crucial for label-free microscopy. Here, we report the identification of two cavitation regimes from 1030 nm pulses when interacting with the central nervous system in zebrafish. We show that at low repetition rates, the damage is confined due to plasma-based ablation and sudden local temperature rise. At high repetition rates, the damage becomes collateral due to plasma-mediated photochemistry. Furthermore, we investigate the role of fluorescence labels with linear and nonlinear absorption pathways in optical breakdown. To verify our findings, we examined cell death and cellular responses to tissue damage, including the recruitment of fibroblasts and immune cells after irradiation. These findings contribute to advancing the emerging nonlinear optical microscopy techniques and provide a strategy for inducing precise, and localized injuries using near-infrared femtosecond laser pulses.

Generalized energy gap law: An open system dynamics approach to non-adiabatic phenomena in molecules

Nico S. Baßler, Michael Reitz, Raphael Holzinger, A. Vibók, G. J. Halász, Burak Gurlek, Claudiu Genes

Non-adiabatic molecular phenomena, arising from the breakdown of the Born-Oppenheimer approximation, govern the fate of virtually all photo-physical and photochemical processes and limit the quantum efficiency of molecules and other solid-state embedded quantum emitters. A simple and elegant description, the energy gap law, was derived five decades ago, predicting that the non-adiabatic coupling between the excited and ground potential landscapes lead to non-radiative decay with a quasi-exponential dependence on the energy gap. We revisit and extend this theory to account for crucial aspects such as vibrational relaxation, dephasing, and radiative loss. We find a closed analytical solution with general validity which indicates a direct proportionality of the non-radiative rate with the vibrational relaxation rate at low temperatures, and with the dephasing rate of the electronic transition at high temperatures. Our work establishes a connection between nanoscale quantum optics, open quantum system dynamics and non-adiabatic molecular physics.

Compressed Sensing of Field-Resolved Molecular Fingerprints Beyond the Nyquist Frequency

Kilian Scheffter, Jonathan Will, Claudius Riek, Jousselin Herve, Sébastien Coudreau, Nicolas Forget, Hanieh Fattahi

Ultrashort time-domain spectroscopy and field-resolved spectroscopy of molecular fingerprints are gold standards for detecting samples’ constituents and internal dynamics. However, they are hindered by the Nyquist criterion, leading to prolonged data acquisition, processing times, and sizable data volumes. In this work, we present the first experimental demonstration of compressed sensing on field-resolved molecular fingerprinting by employing random scanning. Our measurements enable pinpointing the primary absorption peaks of atmospheric water vapor in response to terahertz light transients while sampling beyond the Nyquist limit. By drastically undersampling the electric field of the molecular response at a Nyquist frequency of 0.8 THz, we could successfully identify water absorption peaks up to 2.5 THz with a mean squared error of 12 × 10−4. To our knowledge, this is the first experimental demonstration of time-domain compressed sensing, paving the path toward real-time field-resolved fingerprinting and acceleration of advanced spectroscopic techniques.

Performance analysis of tabletop single-pulse terahertz detection at rates up to 1.1 MHz

Nicolas Couture, Markus Lippl, Wei Cui, Angela Gamouras, Nicolas Joly, Jean-Michel Ménard

Standard terahertz time-domain spectroscopy uses a relatively slow multidata acquisition process that has hindered the technique’s ability to resolve “fast” dynamics occurring on the microsecond timescale. This timescale, inaccessible to most ultrafast pump-probe techniques, hosts a range of phenomena that has been left unexplored due to a lack of proper real-time monitoring techniques. In this work, chirped-pulse spectral encoding, a photonic time-stretch technique, and high-speed electronics are used to demonstrate time-resolved terahertz detection at a rate up to 1.1 MHz. This configuration relies on a tabletop optical source and a setup able to resolve every terahertz transient generated by the same source. We investigate the performance of this single-pulse terahertz detection system at different acquisition rates in terms of experimental noise, dynamic range, and signal-to-noise ratio. Our results pave the way towards single-pulse terahertz time-domain spectroscopy at arbitrarily fast rates to monitor complex dynamics in real time.

Cooperative effects in dense cold atomic gases including magnetic dipole interactions

Nico S. Baßler, I. Varma, M. Proske, P. Windpassinger, K. P. Schmidt, Claudiu Genes

We theoretically investigate cooperative effects in cold atomic gases exhibiting both electric and magnetic dipole-dipole interactions, such as occurs, for example, in clouds of dysprosium atoms. After introducing a general framework capturing both the quantum degenerate and nondenegerate cases, we focus on the emergence of tailorable spin models in the quantum nondegenerate regime. In the low-excitation limit, we provide analytical and numerical results detailing the effect of magnetic interactions on the directionality of scattered light and characterize sub and superradiant effects.

Quantum squeezing via self-induced transparency in a photonic crystal fiber

Mojdeh S. Najafabadi, Luis Sanchez-Soto, J. F. Corney, Nikolay Kalinin, A. A. Sorokin, Gerd Leuchs

We study the quantum squeezing produced in self-induced transparency in a photonic crystal fiber by performing a fully quantum simulation based on the positive P representation. The amplitude squeezing depends on the area of the initial pulse: When the area is 2 pi, there is no energy absorption and no amplitude squeezing. However, when the area is between 2 pi and 3 pi, one observes amplitude-dependent energy absorption and a significant amount of squeezing. We also investigate the effect of damping, detuning, and temperature: The results indicate that a heightened atom-pulse coupling, caused by an increase in the spontaneous emission ratio, reduces the amplitude squeezing.

Discovering Quantum Circuit Components with Program Synthesis

Leopoldo Sarra, Kevin Ellis, Florian Marquardt

Despite rapid progress in the field, it is still challenging to discover new ways to leverage quantum computation: all quantum algorithms must be designed by hand, and quantum mechanics is notoriously counterintuitive. In this paper, we study how artificial intelligence, in the form of program synthesis, may help overcome some of these difficulties, by showing how a computer can incrementally learn concepts relevant to quantum circuit synthesis with experience, and reuse them in unseen tasks. In particular, we focus on the decomposition of unitary matrices into quantum circuits, and show how, starting from a set of elementary gates, we can automatically discover a library of useful new composite gates and use them to decompose increasingly complicated unitaries.

Brillouin light storage for 100 pulse widths

Birgit Stiller, Kevin Jaksch, Johannes Piotrowski, Moritz Merklein, Mikolaj K. Schmidt, Khu Vu, Pan Ma, Stephen Madden, Michael J. Steel, et al.

Signal processing based on stimulated Brillouin scattering (SBS) is limited by the narrow linewidth of the optoacoustic response, which confines many Brillouin applications to continuous wave signals or optical pulses longer than several nanoseconds. In this work, we experimentally demonstrate Brillouin interactions at the 150 ps time scale and a delay for a record 15 ns which corresponds to a delay of 100 pulse widths. This breakthrough experimental result was enabled by the high local gain of the chalcogenide waveguides as the optoacoustic interaction length reduces with pulse width. We successfully transfer 150 ps-long pulses to traveling acoustic waves within a Brillouin-based memory setup. The information encoded in the optical pulses is stored for 15 ns in the acoustic field. We show the retrieval of eight amplitude levels, multiple consecutive pulses, and low distortion in pulse shape. The extension of Brillouin-based storage to the ultra-short pulse regime is an important step for the realization of practical Brillouin-based delay lines and other optical processing applications.

Valleytronics in bulk MoS2 with a topologic optical field

Igor Tyulnev, Álvaro Jiménez-Galán, Julita Poborska, Lenard Vamos, Philip Russell, Francesco Tani, Olga Smirnova, Misha Ivanov, Rui E. F. Silva, et al.

The valley degree of freedom of electrons in materials promises routes towards energy-efficient information storage with enticing prospects for quantum information processing. Current challenges in utilizing valley polarization are symmetry conditions that require monolayer structures or specific material engineering non-resonant optical control to avoid energy dissipation and the ability to switch valley polarization at optical speed. We demonstrate all-optical and non-resonant control over valley polarization using bulk MoS2, a centrosymmetric material without Berry curvature at the valleys. Our universal method utilizes spin angular momentum-shaped trefoil optical control pulses to switch the material’s electronic topology and induce valley polarization by transiently breaking time and space inversion symmetry through a simple phase rotation. We confirm valley polarization through the transient generation of the second harmonic of a non-collinear optical probe pulse, depending on the trefoil phase rotation. The investigation shows that direct optical control over the valley degree of freedom is not limited to monolayer structures. Indeed, such control is possible for systems with an arbitrary number of layers and for bulk materials. Non-resonant valley control is universal and, at optical speeds, unlocks the possibility of engineering efficient multimaterial valleytronic devices operating on quantum coherent timescales.

Estimation of the mass density of biological matter from refractive index measurements

Conrad Möckel, Timon Beck, Sara Kaliman, Shada Abuhattum Hofemeier, Kyoohyun Kim, Julia Kolb, Daniel Wehner, Vasily Zaburdaev, Jochen Guck

The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms. One of the basic biophysical properties is the mass density (MD). It affects the dynamics in sub-cellular compartments and plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge, as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for assumptions about the biochemical composition of the sample and respective RI measurements. To this aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations and Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well-characterized complex mixtures given by bovine milk and intralipid emulsion and employ it to estimate the MD of living zebrafish (Danio rerio) larvae trunk tissue. Our results illustrate the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.

Automated Discovery of Coupled Mode Setups

Jonas Landgraf, Vittorio Peano, Florian Marquardt

In optics and photonics, a small number of building blocks, like resonators, waveguides, arbitrary couplings, and parametric interactions, allow the design of a broad variety of devices and func- tionalities, distinguished by their scattering properties. These include transducers, amplifiers, and nonreciprocal devices, like isolators or circulators. Usually, the design of such a system is hand- crafted by an experienced scientist in a time-consuming process where it remains uncertain whether the simplest possibility has indeed been found. In our work, we develop a discovery algorithm that automates this challenge. By optimizing the continuous and discrete system properties our auto- mated search identifies the minimal resources required to realize the requested scattering behavior. In the spirit of artificial scientific discovery, it produces a complete list of interpretable solutions and leads to generalizable insights, as we illustrate in several examples. This now opens the door to rapid design in areas like photonic and microwave architectures or optomechanics.

185 mW, 1 MHz, 15 fs carrier-envelope phase-stable pulse generation via polarization-optimized down-conversion from gas-filled hollow-core fiber

Anchit Srivastava, Kilian Scheffter, Soyeon Jun, Andreas Herbst, Hanieh Fattahi

Gas-filled hollow core fibers allow the generation of single-cycle pulses at megahertz repetition rates. When coupled with difference frequency generation, they can be an ideal driver for the generation of carrier-envelope phase stable, octave-spanning pulses in the short-wavelength infrared. In this work, we investigate the dependence of the polarization state in gas-filled hollow-core fibers on the subsequent difference frequency generation stage. We show that by adjusting the input polarization state of light in geometrically symmetric systems, such as hollow-core fibers, one can achieve precise control over the polarization state of the output pulses. Importantly, this manipulation preserves the temporal characteristics of the ultrashort pulses generated, especially when operating near the single-cycle regime. We leverage this property to boost the down-conversion efficiency of these pulses in a type I difference frequency generation stage. Our technique overcomes the bandwidth and dispersion constraints of the previous methods that rely on broadband waveplates or adjustment of crystal axes relative to the laboratory frame. This advancement is crucial for experiments demanding pure polarization states in the eigenmodes of the laboratory frame.

Topologically Protected Transport in Engineered Mechanical Systems

Tirth Shah, Christian Brendel, Vittorio Peano, Florian Marquardt

Mechanical vibrations are being harnessed for a variety of purposes and at many length scales, from the macroscopic world down to the nanoscale. The considerable design freedom in mechanical structures allows to engineer new<br>functionalities. In recent years, this has been exploited to generate setups that offer topologically protected transport of vibrational waves, both in the solid state and in fluids. Borrowing concepts from electronic physics and being cross-fertilized by concurrent studies for cold atoms and electromagnetic waves, this field of topological transport in engineered mechanical systems offers a rich variety of phenomena and platforms. In this review, we provide a unifying overview of the various ideas employed in this area, summarize the different approaches and experimental implementations, and comment on the challenges as well as the prospects.

Membrane to cortex attachment determines different mechanical phenotypes in LGR5+ and LGR5- colorectal cancer cells

Sefora Conti, Valeria Venturini, Adrià Cañellas-Socias, Carmen Cortina, Juan F. Abenza, Camille Stephan-Otto Attolini, Emily Middendorp Guerra, Catherine Xu, Jia Hui Li, et al.

Colorectal cancer (CRC) tumors are composed of heterogeneous and plastic cell populations, including a pool of cancer stem cells that express LGR5. Whether these distinct cell populations display different mechanical properties, and how these properties might contribute to metastasis is poorly understood. Using CRC patient derived organoids (PDOs), we find that compared to LGR5- cells, LGR5+ cancer stem cells are stiffer, adhere better to the extracellular matrix (ECM), move slower both as single cells and clusters, display higher nuclear YAP, show a higher survival rate in response to mechanical confinement, and form larger transendothelial gaps. These differences are largely explained by the downregulation of the membrane to cortex attachment proteins Ezrin/Radixin/Moesin (ERMs) in the LGR5+ cells. By analyzing single cell RNA-sequencing (scRNA-seq) expression patterns from a patient cohort, we show that this downregulation is a robust signature of colorectal tumors. Our results show that LGR5- cells display a mechanically dynamic phenotype suitable for dissemination from the primary tumor whereas LGR5+ cells display a mechanically stable and resilient phenotype suitable for extravasation and metastatic growth.

An optoacoustic field-programmable perceptron for recurrent neural networks

Steven Becker, Dirk Englund, Birgit Stiller

Recurrent neural networks (RNNs) can process contextual information such as time series signals and language. But their tracking of internal states is a limiting factor, motivating research on analog implementations in photonics. While photonic unidirectional feedforward neural networks (NNs) have demonstrated big leaps, bi-directional optical RNNs present a challenge: the need for a short-term memory that (i) programmable and coherently computes optical inputs, (ii) minimizes added noise, and (iii) allows scalability. Here, we experimentally demonstrate an optoacoustic recurrent operator (OREO) which meets (i, ii, iii). OREO contextualizes the information of an optical pulse sequence via acoustic waves. The acoustic waves link different optical pulses, capturing their information and using it to manipulate subsequent operations. OREO’s all-optical control on a pulse-by-pulse basis offers simple reconfigurability and is used to implement a recurrent drop-out and pattern recognition of 27 optical pulse patterns. Finally, we introduce OREO as bi-directional perceptron for new classes of optical NNs.

Multiphoton electron emission with non-classical light

Jonas Heimerl, Alexander Mikhaylov, Stefan Meier, Henrick Höllerer, Ido Kaminer, Maria Chekhova, Peter Hommelhoff

Photon number distributions of classical and non-classical light sources have been studied extensively, yet their impact on photoemission processes is largely unexplored. In this article, we present measurements of electron number distributions from metal needle tips illuminated with ultrashort light pulses with various photon quantum statistics. By varying the photon statistics of the exciting light field between classical (Poissonian) and quantum (super-Poissonian), we demonstrate that the measured electron distributions are changed substantially. Using single-mode bright squeezed vacuum light, we measure extreme statistics events with up to 65 electrons from one light pulse at a mean of 0.27 electrons per pulse—the likelihood for such an event equals 10−128 with Poissonian statistics. By changing the number of modes of the exciting bright squeezed vacuum, we can tailor the electron number distribution on demand. Most importantly, our results demonstrate that the photon statistics is imprinted from the driving light to the emitted electrons, opening the door to new sensor devices and to strong-field optics with quantum light and electrons.

Linear and Nonlinear Coupling of Twin-Resonators with Kerr Nonlinearity

Arghadeep Pal, Alekhya Ghosh, Shuangyou Zhang, Lewis Hill, Haochen Yan, Hao Zhang, Toby Bi, Abdullah Alabbadi, Pascal Del'Haye

Nonlinear effects in microresonators are efficient building blocks for all-optical computing and telecom systems. With the latest advances in microfabrication, coupled microresonators are used in a rapidly growing number of applications. In this work, we investigate the coupling between twin-resonators in the presence of Kerr-nonlinearity. We use an experimental setup with controllable coupling between two high-Q resonators and discuss the effects caused by the simultaneous presence of linear and non-linear coupling between the optical fields. Linear-coupling-induced mode splitting is observed at low input powers, with the controllable coupling leading to a tunable mode splitting. At high input powers, the hybridized resonances show spontaneous symmetry breaking (SSB) effects, in which the optical power is unevenly distributed between the resonators. Our experimental results are supported by a detailed theoretical model of nonlinear twin-resonators. With the recent interest in coupled resonator systems for neuromorphic computing, quantum systems, and optical frequency comb generation, our work provides important insights into the behavior of these systems at high circulating powers.<br>

Detailed balance in non-equilibrium dynamics of granular matter: derivation and implications

Clara C. Wanjura, Amelie Mayländer, Othmar Marti, Raphael Blumenfeld

Discovering fundamental principles governing the dynamics of granular media has been a long-standing challenge. Recent predictions of detailed balance steady states (DBSS), supported by experimental observations in cyclic shear experiments of planar granular systems, called into question the common belief that the detailed balance principle is only a feature of equilibrium. Here, we first show analytically that DBSS in planar granular dynamics arise when a certain conditional cell order distribution is independent of the condition. We then demonstrate that this condition is met in rotational shear experiments, which indeed also give rise to robust DBSS. This suggests that DBSS not only exist but are also quite common. We also show that, when the unconditional cell order distribution maximises the entropy, as has been found recently, then this distribution is determined by a single parameter - the ratio of splitting and merging rates of cells of any arbitrary order. These results simplify the modelling of the complex dynamics of planar granular systems to the solution of recently proposed evolution equations, demonstrating their predictive power.<br>

Quantitative analysis of the intensity distribution of optical rogue waves

Éva Rácz, Kirill Spasibko, Mathieu Manceau, László Ruppert, Maria Chekhova, Radim Filip

The field of optical rogue waves is a rapidly expanding topic with a focus on explaining their emergence. To complement this research, instead of providing a microscopic model that generates extreme events, we concentrate on a general quantitative description of the observed behavior. We explore two complementary top-down approaches to estimating the exponent describing the power-law decaying distribution of optical rogue waves observed in supercontinuum generated in a single-mode fiber in the normal-dispersion regime by applying a highly fluctuating pump. The two distinct approaches provide consistent results, outperforming the standard Hill estimator. Further analysis of the distributions reveals the breakdown of power-law behavior due to pump depletion and detector saturation. Either of our methods is adaptable to analyze extreme-intensity events from arbitrary experimental data.

Three perspectives on entropy dynamics in a non-Hermitian two-state system

Alexander Felski, Alireza Beygi, Christos Karapoulitidis, S. P. Klevansky

A comparative study of entropy dynamics as an indicator of physical behavior in an open two- state system with balanced gain and loss is presented. We distinguish the perspective taken in utilizing the conventional framework of Hermitian-adjoint states from an approach that is based on biorthogonal-adjoint states and a third case based on an isospectral mapping. In this it is demonstrated that their differences are rooted in the treatment of the environmental coupling mode. For unbroken PT symmetry of the system, a notable characteristic feature of the perspective taken is the presence or absence of purity oscillations, with an associated entropy revival. The description of the system is then continued from its PT -symmetric pseudo-Hermitian phase into the regime of spontaneously broken symmetry, in the latter two approaches through a non-analytic operator- based continuation, yielding a Lindblad master equation based on the PT charge operator C. This phase transition indicates a general connection between the pseudo-Hermitian closed-system and the Lindbladian open-system formalism through a spontaneous breakdown of the underlying physical reflection symmetry.

Scaling Law for Kasha’s Rule in Photoexcited Molecular Aggregates

Raphael Holzinger, Nico S. Baßler, Helmut Ritsch, Claudiu Genes

We study the photophysics of molecular aggregates from a quantum optics perspective, with emphasis on deriving scaling laws for the fast nonradiative relaxation of collective electronic excitations, referred to as Kasha’s rule. Aggregates exhibit an energetically broad manifold of collective states with delocalized electronic excitations originating from near-field dipole–dipole exchanges between neighboring monomers. Photoexcitation at optical wavelengths, much larger than the monomer–monomer average separation, addresses almost exclusively symmetric collective states, which for an arrangement known as H-aggregate show an upward hypsochromic shift. The extremely fast subsequent nonradiative relaxation via intramolecular vibrational modes populates lower energy, subradiant states, resulting in effective inhibition of fluorescence. Our analytical treatment allows for the derivation of an approximate scaling law of this relaxation process, linear in the number of available low-energy vibrational modes and directly proportional to the dipole–dipole interaction strength between neighboring monomers.

Reservoir Engineering for Classical Nonlinear Fields

Benedikt Tissot, Hugo Ribeiro, Florian Marquardt

Reservoir engineering has become a prominent tool to control quantum systems. Recently, there have been first experiments applying it to many-body systems, especially with a view to engineer particle-conserving dissipation for quantum simulations using bosons. In this work, we explore the dissipative dynamics of these systems in the classical limit. We derive a general equation of motion capturing the effective nonlinear dissipation introduced by the bath and apply it to the special case of a Bose-Hubbard model, where it leads to an unconventional type of dissipative nonlinear Schr ̈odinger equation. Building on that, we study the dynamics of one and two solitons in such a dissipative classical field theory.

High-throughput viscoelastic characterization of cells in hyperbolic microchannels

Felix Reichel, Ruchi Goswami, Salvatore Girardo, Jochen Guck

Extensive research has demonstrated the potential of cell viscoelastic properties as intrinsic indicators of cell state, functionality, and disease. For this, several microfluidic techniques have been developed to measure cell viscoelasticity with high-throughput. However, current microchannel designs introduce complex stress distributions on cells, leading to inaccuracies in determining the stress-strain relationship and, consequently, the viscoelastic properties. Here, we introduce a novel approach using hyperbolic microchannels that enable precise measurements under a constant extensional stress and offer a straightforward stress-strain relationship, while operating at a measurement rate of up to 100 cells per second. We quantified the stresses acting in the channels using mechanical calibration particles made from polyacrylamide (PAAm) and found that the measurement buffer, a solution of methyl cellulose and phosphate buffered saline, has a constant extensional viscosity of 0.5 Pa s up to 200 s-1. By measuring oil droplets with varying viscosities, we successfully detected changes in the relaxation time of the droplets and our approach could be used to get the interfacial tension and viscosity of liquid-liquid droplet systems from the same measurement. We further applied this methodology to PAAm microgel beads, demonstrating the accurate recovery of Young’s moduli and the near-ideal elastic behavior of the beads. To explore the influence of altered cell viscoelasticity, we treated HL60 human leukemia cells with Latrunculin B and Nocodazole, resulting in clear changes in cell stiffness while relaxation times were only minimally affected. In conclusion, our approach offers a streamlined and time-efficient solution for assessing the viscoelastic properties of large cell populations and other microscale soft particles.

Optomechanical realization of the bosonic Kitaev chain

Jesse J. Slim, Clara C. Wanjura, Matteo Brunelli, Javier del Pino, Andreas Nunnenkamp, Ewold Verhagen

The fermionic Kitaev chain is a canonical model featuring topological Majorana zero modes. We report the experimental realization of its bosonic analogue in a nanooptomechanical network, in which the parametric interactions induce beam-splitter coupling and two-mode squeezing among the nanomechanical modes, analogous to hopping and p-wave pairing in the fermionic case, respectively. This specific structure gives rise to a set of extraordinary phenomena in the bosonic dynamics and transport. We observe quadrature-dependent chiral amplification, exponential scaling of the gain with system size and strong sensitivity to boundary conditions. All these are linked to the unique non-Hermitian topological nature of the bosonic Kitaev chain.<br>We probe the topological phase transition and uncover a rich dynamical phase diagram by controlling interaction phases and amplitudes. Finally, we present an experimental demonstration of an exponentially enhanced response to a small perturbation. These results represent the demonstration of a new synthetic phase of matter whose bosonic dynamics do not have fermionic parallels, and we have established a powerful system for studying non-Hermitian topology and its applications for signal manipulation and sensing.

Supervised Training of Neural-Network Quantum States for the Next Nearest Neighbor Ising model

Zheyu Wu, Remmy Augusta Menzata Zen, Heitor P. Casagrande, Stéphane Bressan, Dario Poletti

Different neural network architectures can be unsupervisedly or supervis- edly trained to represent quantum states. We explore and compare different strategies for the supervised training of feed forward neural network quan- tum states. We empirically and comparatively evaluate the performance of feed forward neural network quantum states in different phases of matter for variants of the architecture, for different hyper-parameters, and for two different loss functions, to which we refer as mean-squared error and over- lap, respectively. We consider the next-nearest neighbor Ising model for the diversity of its phases and focus on its paramagnetic, ferromagnetic, and pair-antiferromagnetic phases. We observe that the overlap loss function al- lows better training of the model across all phases, provided a rescaling of the neural network.

Frequency Comb Enhancement via the Self-Crystallization of Vectorial Cavity Solitons

Graeme Neil Campbell, Lewis Hill, Pascal Del'Haye, Gian-Luca Oppo

Long range interactions between dark vectorial temporal cavity solitons are induced though the spontaneous symmetry breaking of orthogonally polarized fields in ring resonators. Turing patterns of alternating polarizations form between adjacent solitons, pushing them apart so that a random distribution of solitons along the cavity length reaches equal equilibrium distances. Enhancement of the frequency comb is achieved through the spontaneous formation of regularly spaced soliton crystals, 'self-crystallization', with greater power and spacing of the spectral lines for increasing soliton numbers.<br>

An optofluidic antenna for enhancing the sensitivity of single-emitter measurements

Luis Morales-Inostroza, Julian Folz, Ralf Kühnemuth, Suren Felekyan, Franz Wieser, Claus A.M. Seidel, Stephan Götzinger, Vahid Sandoghdar

Many single-molecule investigations are performed in fluidic environments, e.g., to avoid unwanted consequences of contact with surfaces. Diffusion of molecules in this arrangement limits the observation time and the number of collected photons, thus, compromising studies of processes with fast or slow dynamics. Here, we introduce a planar optofluidic antenna (OFA), which enhances the fluorescence signal from molecules by about 5 times per passage, leads to about 7-fold more frequent returns to the observation volume, and significantly lengthens the diffusion time within one passage. We use single-molecule multi-parameter fluorescence detection (sm-MFD), fluorescence correlation spectroscopy (FCS) and Förster resonance energy transfer (FRET) measurements to characterize our OFAs. The antenna advantages are showcased by examining both the slow (ms) and fast (50μs) dynamics of DNA four-way (Holliday) junctions with real-time resolution. The FRET trajectories provide evidence for the absence of an intermediate conformational state and introduce an upper bound for its lifetime. The ease of implementation and compatibility with various microscopy modalities make OFAs broadly applicable to a diverse range of studies.

A deep‐learning workflow to predict upper tract urothelial carcinoma protein‐based subtypes fromH&Eslides supporting the prioritization of patients for molecular testing

Miriam Angeloni, Thomas van Doeveren, Sebastian Lindner, Patrick Volland, Jorina Schmelmer, Sebastian Foersch, Christian Matek, Robert Stoehr, Carol I Geppert, et al.

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (N = 80) and basal (N = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67–0.99), 0.8 (95% CI: 0.62–0.99), and 0.81 (95% CI: 0.65–0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (p < 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (p < 0.001) and FGFR3 mutational status (p = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of FGFR3-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&E slides.

Quantum interference between distant creation processes

Johannes Pseiner, Manuel Erhard, Mario Krenn

The search for macroscopic quantum phenomena is a fundamental pursuit in quantum mechanics. It allows us to test the limits of quantum physics and provides new avenues for exploring the interplay between quantum mechanics and relativity. In this work, we introduce a novel approach to generate macroscopic quantum systems by demonstrating that the creation process of a quantum system can span a macroscopic distance. Specifically, we generate photon pairs in a coherent superposition of two origins separated by up to 70 meters. This new approach not only provides an exciting opportunity for foundational experiments in quantum physics, but also has practical applications for high-precision measurements of distributed properties such as pressure and humidity of air or gases.

Exceptional points of any order in a generalized Hatano-Nelson model

Julius Gohsrich, Jacob Fauman, Flore K. Kunst

Exceptional points (EPs) are truly non-Hermitian (NH) degeneracies where matrices become defective. The order of such an EP is given by the number of coalescing eigenvectors. On the one hand, most work focusses on studying Nth-order EPs in N≤4-dimensional NH Bloch Hamiltonians. On the other hand, some works have remarked on the existence of EPs of orders scaling with systems size in models exhibiting the NH skin effect. In this letter, we introduce a new type of EP and provide a recipe on how to realize EPs of arbitrary order not scaling with system size. We introduce a generalized version of the paradigmatic Hatano-Nelson model with longer-range hoppings. The EPs existing in this system show remarkable physical features: Their associated eigenstates are localized on a subset of sites and are exhibiting the NH skin effect. Furthermore, the EPs are robust against generic perturbations in the hopping strengths as well as against a specific form of on-site disorder.

A Bohmian trajectory analysis of singular wave functions

Ángel S. Sanz, Luis Sanchez-Soto, Andrea Aiello

The Schrödinger equation admits smooth and finite solutions that spontaneously evolve into a singularity, even for a free particle. This blowup is generally ascribed to the intrinsic dispersive character of the associated time evolution. We resort to the notion of quantum Bohmian trajectories to relate this singular behavior to local phase variations, which generate an underlying velocity field responsible for driving the quantum flux toward the singular region.

Symmetry broken vectorial Kerr frequency combs from Fabry-Pérot resonators

Lewis Hill, Eva-Maria Hirmer, Graeme Campbell, Toby Bi, Alekhya Ghosh, Pascal Del'Haye, Gian-Luca Oppo

Spontaneous symmetry breaking of a pair of vector temporal cavity solitons has been established as a paradigm to modulate optical frequency combs, and finds many applications in metrology, frequency standards, communications, and photonic devices. While this phenomenon has successfully been observed in Kerr ring resonators, the counterpart exploiting linear Fabry-Pérot cavities is still unexplored. Here, we consider field polarization properties and describe a vector comb generation through the spontaneous symmetry breaking of temporal cavity solitons within coherently driven, passive, Fabry-Pérot cavities with Kerr nonlinearity. Global coupling effects due to the interactions of counter-propagating light restrict the maximum number of soliton pairs within the cavity - even down to a single soliton pair - and force long range polarization conformity in trains of vector solitons.

Essential implications of similarities in non-Hermitian systems

Anton Montag, Flore K. Kunst

In this paper, we show that three different generalized similarities enclose all unitary and anti-unitary symmetries that induce exceptional points in lower-dimensional non-Hermitian systems. We prove that the generalized similarity conditions result in a larger class of systems than any class defined by a unitary or anti-unitary symmetry. Further we highlight that the similarities enforce spectral symmetry on the Hamiltonian resulting in a reduction of the codimension of exceptional points. As a consequence we show that the similarities drive the emergence of exceptional points in lower dimensions without the more restrictive need for a unitary and/or anti-unitary symmetry.

Quantum Circuit Discovery for Fault-Tolerant Logical State Preparation with Reinforcement Learning

Remmy Zen, Jan Olle, Luis Colmenarez, Matteo Puviani, Markus Müller, Florian Marquardt

One of the key aspects in the realization of large-scale fault-tolerant quantum computers is quan- tum error correction (QEC). The first essential step of QEC is to encode the logical state into physical qubits in a fault-tolerant manner. Recently, flag-based protocols have been introduced that use ancillary qubits to flag harmful errors. However, there is no clear recipe for finding a compact quantum circuit with flag-based protocols for fault-tolerant logical state preparation. It is even more difficult when we consider the hardware constraints, such as qubit connectivity and gate set. In this work, we propose and explore reinforcement learning (RL) to automatically discover compact and hardware-adapted quantum circuits that fault-tolerantly prepare the logical state of a QEC code. We show that RL discovers circuits with fewer gates and ancillary qubits than published results without and with hardware constraints of up to 15 physical qubits. Furthermore, RL allows for straightforward exploration of different qubit connectivities and the use of transfer learning to accelerate the discovery. More generally, our work opens the door towards the use of RL for the discovery of fault-tolerant quantum circuits for addressing tasks beyond state preparation, including magic state preparation, logical gate synthesis, or syndrome measurement.

Real-time imaging of standing-wave patterns in microresonators

Haochen Yan, Alekhya Ghosh, Arghadeep Pal, Hao Zhang, Toby Bi, George N. Ghalanos, Shuangyou Zhang, Lewis Hill, Yaojing Zhang, et al.

Real-time characterization of microresonator dynamics is important for many applications. In particular, it is critical for near-field sensing and understanding light–matter interactions. Here, we report camera-facilitated imaging and analysis of standing wave patterns in optical ring resonators. The standing wave pattern is generated through bidirectional pumping of a microresonator, and the scattered light from the microresonator is collected by a short-wave infrared (SWIR) camera. The recorded scattering patterns are wavelength dependent, and the scattered intensity exhibits a linear relation with the circulating power within the microresonator. By modulating the relative phase between the two pump waves, we can control the generated standing waves’ movements and characterize the resonator with the SWIR camera. The visualized standing wave enables subwavelength distance measurements of scattering targets with nanometer-level accuracy. This work opens broad avenues for applications in on-chip near-field (bio)sensing, real-time characterization of photonic integrated circuits, and backscattering control in telecom systems.<br>

Exploring the Physics of Basic Medical Research

Vahid Sandoghdar

The 20th century witnessed the emergence of many paradigm-shifting technologies from the physics community, which have revolutionized medical diagnostics and patient care. However, fundamental medical research has been mostly guided by methods from areas such as cell biology, biochemistry, and genetics, with fairly small contributions from physicists. In this Essay, I outline some key phenomena in the human body that are based on physical principles and yet govern our health over a vast range of length and time scales. I advocate that research in life sciences can greatly benefit from the methodology, know-how, and mindset of the physics community and that the pursuit of basic research in medicine is compatible with the mission of physics.<br><br>

invited essay

Single-Cell Mechanics: Structural Determinants and Functional Relevance

Marta Urbanska, Jochen Guck

The mechanical phenotype of a cell determines its ability to deform under force and is therefore relevant to cellular functions that require changes in cell shape, such as migration or circulation through the microvasculature. On the practical level, the mechanical phenotype can be used as a global readout of the cell's functional state, a marker for disease diagnostics, or an input for tissue modeling. We focus our review on the current knowledge of structural components that contribute to the determination of the cellular mechanical properties and highlight the physiological processes in which the mechanical phenotype of the cells is of critical relevance. The ongoing efforts to understand how to efficiently measure and control the mechanical properties of cells will define the progress in the field and drive mechanical phenotyping toward clinical applications.

Nonlinear optovibronics in molecular systems

Q. Zhang, M. Asjad, Michael Reitz, Christian Sommer, Burak Gurlek, Claudiu Genes

We analytically tackle optovibronic interactions in molecular systems driven by either classical or quantum light fields. In particular, we examine a simple model of molecules with two relevant electronic levels, characterized by potential landscapes with different positions of minima along the internuclear coordinates and of varying curvatures. Such systems exhibit an electron-vibron interaction, which can be composed of linear and quadratic terms in the vibrational displacement. By employing a combination of conditional displacement and squeezing operators, we present analytical expressions based on a quantum Langevin equations approach, to describe the emission and absorption spectra of such nonlinear molecular systems. Furthermore, we examine the imprint of the quadratic interactions onto the transmission properties of a cavity-molecule system within the collective strong-coupling regime of cavity quantum electrodynamics.

Virtual Reality for Understanding Artificial-Intelligence-driven Scientific Discovery with an Application in Quantum Optics

Philipp Schmidt, Sören Arlt, Carlos Ruiz-Gonzalez, Xuemei Gu, Carla Rodríguez, Mario Krenn

Generative Artificial Intelligence (AI) models can propose solutions to scientific problems beyond human capability. To truly make conceptual contributions, researchers need to be capable of understanding the AI-generated structures and extracting the underlying concepts and ideas. When algorithms provide little explanatory reasoning alongside the output, scientists have to reverse-engineer the fundamental insights behind proposals based solely on examples. This task can be challenging as the output is often highly complex and thus not immediately accessible to humans. In this work we show how transferring part of the analysis process into an immersive Virtual Reality (VR) environment can assist researchers in developing an understanding of AI-generated solutions. We demonstrate the usefulness of VR in finding interpretable configurations of abstract graphs, representing Quantum Optics experiments. Thereby, we can manually discover new generalizations of AI-discoveries as well as new understanding in experimental quantum optics. Furthermore, it allows us to customize the search space in an informed way - as a human-in-the-loop - to achieve significantly faster subsequent discovery iterations. As concrete examples, with this technology, we discover a new resource-efficient 3-dimensional entanglement swapping scheme, as well as a 3-dimensional 4-particle Greenberger-Horne-Zeilinger-state analyzer. Our results show the potential of VR for increasing a human researcher's ability to derive knowledge from graph-based generative AI that, which is a common abstract data representation used in diverse fields of science.

Controlled light distribution with coupled microresonator chains via Kerr symmetry breaking

Alekhya Ghosh, Arghadeep Pal, Lewis Hill, Graeme N Campbell, Toby Bi, Yaojing Zhang, Abdullah Alabbadi, Shuangyou Zhang, Gian-Luca Oppo, et al.

Within optical microresonators, the Kerr interaction of photons can lead to symmetry breaking of optical modes. In a ring resonator, this leads to the interesting effect that light preferably circulates in one direction or in one polarization state. Applications of this effect range from chip-integrated optical diodes to nonlinear polarization controllers and optical gyroscopes. In this work, we study Kerr-nonlinearity-induced symmetry breaking of light states in coupled resonator optical waveguides (CROWs). We discover a new type of controllable symmetry breaking that leads to emerging patterns of dark and bright resonators within the chains. Beyond stationary symmetry broken states, we observe periodic oscillations, switching and chaotic fluctuations of circulating powers in the resonators. Our findings are of interest for controlled multiplexing of light in photonic integrated circuits, neuromorphic computing, topological photonics and soliton frequency combs in coupled resonators.

Non-Hermitian chiral anomalies in interacting systems

Sharareh Sayyad

The emergence of chiral anomaly entails various fascinating phenomena such as anomalous quantum Hall effect and chiral magnetic effect in different branches of (non-)Hermitian physics. While in the single-particle picture, anomalous currents merely appear due to the coupling of massless particles with background fields, many-body interactions can also be responsible for anomalous transport in interacting systems. In this Letter, we study anomalous chiral currents in systems where interacting massless fermions with complex Fermi velocities are coupled to complex gauge fields. Our results reveal that incorporating non-Hermiticity and many-body interactions gives rise to additional terms in anomalous relations beyond their Hermitian counterparts. We further present that many-body corrections in the subsequent non-Hermitian chiral magnetic field or anomalous Hall effect are nonvanishing in nonequilibrium or inhomogeneous systems. Our findings advance efforts in understanding anomalous transport in interacting non-Hermitian systems.<br>

Deep Quantum Graph Dreaming: Deciphering Neural Network Insights into Quantum Experiments

Tareq Jaouni, Sören Arlt, Carlos Ruiz-Gonzalez, Ebrahim Karimi, Xuemei Gu, Mario Krenn

Despite their promise to facilitate new scientific discoveries, the opaqueness of neural networks presents a challenge in interpreting the logic behind their findings. Here, we use a eXplainable-AI (XAI) technique called inception or deep dreaming, which has been invented in machine learning for computer vision. We use this techniques to explore what neural networks learn about quantum optics experiments. Our story begins by training a deep neural networks on the properties of quantum systems. Once trained, we "invert" the neural network – effectively asking how it imagines a quantum system with a specific property, and how it would continuously modify the quantum system to change a property. We find that the network can shift the initial distribution of properties of the quantum system, and we can conceptualize the learned strategies of the neural network. Interestingly, we find that, in the first layers, the neural network identifies simple properties, while in the deeper ones, it can identify complex quantum structures and even quantum entanglement. This is in reminiscence of long-understood properties known in computer vision, which we now identify in a complex natural science task. Our approach could be useful in a more interpretable way to develop new advanced AI-based scientific discovery techniques in quantum physics.

Training Coupled Phase Oscillators as a Neuromorphic Platform using Equilibrium Propagation

Qingshan Wang, Clara C. Wanjura, Florian Marquardt

Given the rapidly growing scale and resource requirements of machine learning applications, the idea of building more efficient learning machines much closer to the laws of physics is an attractive proposition. One central question for identifying promising candidates for such neuromorphic platforms is whether not only infer- ence but also training can exploit the physical dynamics. In this work, we show that it is possible to successfully train a system of coupled phase oscillators—one of the most widely investigated nonlinear dynamical systems with a multitude of physical implementations, comprising laser arrays, coupled mechanical limit cycles, super- fluids, and exciton-polaritons. To this end, we apply the approach of equilibrium propagation, which permits to extract training gradients via a physical realization of backpropagation, based only on local interactions. The complex energy landscape of the XY/ Kuramoto model leads to multistability, and we show how to address this challenge. Our study identifies coupled phase oscillators as a new general-purpose neuromorphic platform and opens the door towards future experimental implementations.

Forecasting high-impact research topics via machine learning on evolving knowledge graphs

Xuemei Gu, Mario Krenn

The exponential growth in scientific publications poses a severe challenge for human researchers. It forces attention to more narrow sub-fields, which makes it challenging to discover new impactful research ideas and collaborations outside one’s own field. While there are ways to predict a scientific paper’s future citation counts, they need the research to be finished and the paper written, usually assessing impact long after the idea was conceived. Here we show how to predict the impact of onsets of ideas that have never been published by researchers. For that, we developed a large evolving knowledge graph built from more than 21 million scientific papers. It combines a semantic network created from the content of the papers and an impact network created from the historic citations of papers. Using machine learning, we can predict the dynamic of the evolving network into the future with high accuracy, and thereby the impact of new research directions. We envision that the ability to predict the impact of new ideas will be a crucial component of future artificial muses that can inspire new impactful and interesting scientific ideas.

A paintbrush for delivery of nanoparticles and molecules to live cells with precise spatiotemporal control

Cornelia Holler, Richard W. Taylor, Alexandra Schambony, Leonhard Möckl, Vahid Sandoghdar

Delivery of very small amounts of reagents to the near-field of cells with micrometer spatial precision and millisecond time resolution is currently out of reach. Here we present μkiss as a micropipette-based scheme for brushing a layer of small molecules and nanoparticles onto the live cell membrane from a subfemtoliter confined volume of a perfusion flow. We characterize our system through both experiments and modeling, and find excellent agreement. We demonstrate several applications that benefit from a controlled brush delivery, such as a direct means to quantify local and long-range membrane mobility and organization as well as dynamical probing of intercellular force signaling.

Transfer learning from Hermitian to non-Hermitian quantum many-body physics

Sharareh Sayyad, Jose L. Lado

Identifying phase boundaries of interacting systems is one of the key steps to understanding quantum many-body models. The development of various numerical and analytical methods has allowed exploring the phase diagrams of many Hermitian interacting systems. However, numerical challenges and scarcity of analytical solutions hinder obtaining phase boundaries in non-Hermitian many-body models. Recent machine learning methods have emerged as a potential strategy to learn phase boundaries from various observables without having access to the full many-body wavefunc- tion. Here, we show that a machine learning methodology trained solely on Hermitian correlation functions allows identifying phase boundaries of non-Hermitian interacting models. These results demonstrate that Hermitian machine learning algorithms can be redeployed to non-Hermitian mod- els without requiring further training to reveal non-Hermitian phase diagrams. Our findings es- tablish transfer learning as a versatile strategy to leverage Hermitian physics to machine learning non-Hermitian phenomena.

Brillouin microscopy

Irina Kabakova, Jitao Zhang, Yuchen Xiang, Silvia Caponi, Alberto Bilenca, Jochen Guck, Guiliano Scarcelli

The field of Brillouin microscopy and imaging was established approximately 20 years ago, thanks to the development of non-scanning high-resolution optical spectrometers. Since then, the field has experienced rapid expansion, incorporating technologies from telecommunications, astrophotonics, multiplexed microscopy, quantum optics and machine learning. Consequently, these advancements have led to much-needed improvements in imaging speed, spectral resolution and sensitivity. The progress in Brillouin microscopy is driven by a strong demand for label-free and contact-free methods to characterize the mechanical properties of biomaterials at the cellular and subcellular scales. Understanding the local biomechanics of cells and tissues has become crucial in predicting cellular fate and tissue pathogenesis. This Primer aims to provide a comprehensive overview of the methods and applications of Brillouin microscopy. It includes key demonstrations of Brillouin microscopy and imaging that can serve as a reference for the existing research community and new adopters of this technology. The article concludes with an outlook, presenting the authors’ vision for future developments in this vibrant field. The Primer also highlights specific examples where Brillouin microscopy can have a transformative impact on biology and biomedicine.

p21 Prevents the Exhaustion of CD4+ T Cells Within the Antitumor Immune Response Against Colorectal Cancer

Oana-Maria Thoma, Elisabeth Naschberger, Markéta Kubánková, Imen Larafa, Viktoria Kramer, Bianca Menchicchi, Susanne Merkel, Nathalie Britzen-Laurent, André Jefremow, et al.

BACKGROUND & AIMS: T cells are crucial for the antitumor response against colorectal cancer (CRC). T-cell reactivity to CRC is nevertheless limited by T-cell exhaustion. However, molecular mechanisms regulating T-cell exhaustion are only poorly understood. METHODS: We investigated the functional role of cyclin-dependent kinase 1a (Cdkn1a or p21) in cluster of differentiation (CD) 4+ T cells using murine CRC models. Furthermore, we evaluated the expression of p21 in patients with stage I to IV CRC. In vitro coculture models were used to understand the effector function of p21-deficient CD4+ T cells. RESULTS: We observed that the activation of cell cycle regulator p21 is crucial for CD4+ T-cell cytotoxic function and that p21 deficiency in type 1 helper T cells (Th1) leads to increased tumor growth in murine CRC. Similarly, low p21 expression in CD4+ T cells infiltrated into tumors of CRC patients is associated with reduced cancer-related survival. In mouse models of CRC, p21-deficient Th1 cells show signs of exhaustion, where an accumulation of effector/effector memory T cells and CD27/CD28 loss are predominant. Immune reconstitution of tumor-bearing Rag1−/− mice using ex vivo-treated p21-deficient T cells with palbociclib, an inhibitor of cyclin-dependent kinase 4/6, restored cytotoxic function and prevented exhaustion of p21-deficient CD4+ T cells as a possible concept for future immunotherapy of human disease. CONCLUSIONS: Our data reveal the importance of p21 in controlling the cell cycle and preventing exhaustion of Th1 cells. Furthermore, we unveil the therapeutic potential of cyclin-dependent kinase inhibitors such as palbociclib to reduce T-cell exhaustion for future treatment of patients with colorectal cancer.

Where bacteria and eukaryotes meet

Liraz Chai, Elizabeth A. Shank, Vasily Zaburdaev, Mohamed Y. El-Naggar

The international workshop “Interdisciplinary life of microbes: from single cells to multicellular aggregates,” following a virtual preassembly in November 2021, was held in person in Dresden, from 9 to 13 November 2022. It attracted not only prominent experts in biofilm research but also researchers from broadly neighboring disciplines, such as medicine, chemistry, and theoretical and experimental biophysics, both eukaryotic and prokaryotic. Focused brainstorming sessions were the special feature of the event and are at the heart of this commentary.<br>

Beyond comparison: Brillouin microscopy and AFM-based indentation reveal divergent insights into the mechanical profile of the murine retina

Stephanie Möllmert, Marcus Gutmann, Paul Müller, Kyoohyun Kim, Jana Bachir Salvador, Serhii Aif, Lorenz Meinel, Jochen Guck

Mechanical tissue properties increasingly serve as pivotal phenotypic characteristics that are subject to change during development or pathological progression. The quantification of such material properties often relies on physical contact between a load-applying probe and an exposed sample surface. For most tissues, these requirements necessitate animal sacrifice, tissue dissection and sectioning. These invasive procedures bear the risk of yielding mechanical properties that do not portray the physiological mechanical state of a tissue within a functioning organism. Brillouin microscopy has emerged as a non-invasive, optical technique that allows to assess mechanical cell and tissue properties with high spatio-temporal resolution. In optically transparent specimens, this technique does not require animal sacrifice, tissue dissection or sectioning. However, the extent to which results obtained from Brillouin microscopy allow to infer conclusions about potential results obtained with a contact-based technique, and vice versa, is unclear. Potential sources for discrepancies include the varying characteristic temporal and spatial scales, the directionality of measurement, environmental factors, and mechanical moduli probed. In this work, we addressed those aspects by quantifying the mechanical properties of acutely dissected murine retinal tissues using Brillouin microscopy and atomic force microscopy (AFM)-based indentation measurements. Our results show a distinct mechanical profile of the retinal layers with respect to the Brillouin frequency shift, the Brillouin linewidth and the apparent Young’s modulus. Contrary to previous reports, our findings do not support a simple correlative relationship between Brillouin frequency shift and apparent Young’s modulus. Additionally, the divergent sensitivity of Brillouin microscopy and AFM-indentation measurements to cross-linking or changes post mortem underscores the dangers of assuming both methods can be generally used interchangeably. In conclusion, our study advocates for viewing Brillouin microscopy and AFM-based indentation measurements as complementary tools, discouraging direct comparisons a priori and suggesting their combined use for a more comprehensive understanding of tissue mechanical properties.<br><br>

Metasurface-Based Hybrid Optical Cavities for Chiral Sensing

Nico S. Baßler, Andrea Aiello, Kai P. Schmidt, Claudiu Genes, Michael Reitz

Quantum metasurfaces, i.e., two-dimensional subwavelength arrays of quantum emitters, can be employed as mirrors towards the design of hybrid cavities, where the optical response is given by the interplay of a cavity-confined field and the surface modes supported by the arrays. We show that stacked layers of quantum metasurfaces with orthogonal dipole orientation can serve as helicity-preserving cavities. These structures exhibit ultranarrow resonances and can enhance the intensity of the incoming field by orders of magnitude, while simultaneously preserving the handedness of the field circulating inside the resonator, as opposed to conventional cavities. The rapid phase shift in the cavity transmission around the resonance can be exploited for the sensitive detection of chiral scatterers passing through the cavity. We discuss possible applications of these resonators as sensors for the discrimination of chiral molecules. Our approach describes a new way of chiral sensing via the measurement of particle-induced phase shifts.

AI-driven projection tomography with multicore fibre-optic cell rotation

Jiawei Sun, Bin Yang, Nektarios Koukourakis, Jochen Guck, Juergen W. Czarske

Optical tomography has emerged as a non-invasive imaging method, providing three-dimensional insights into subcellular structures and thereby enabling a deeper understanding of cellular functions, interactions, and processes. Conventional optical tomography methods are constrained by a limited illumination scanning range, leading to anisotropic resolution and incomplete imaging of cellular structures. To overcome this problem, we employ a compact multi-core fibre-optic cell rotator system that facilitates precise optical manipulation of cells within a microfluidic chip, achieving full-angle projection tomography with isotropic resolution. Moreover, we demonstrate an AI-driven tomographic reconstruction workflow, which can be a paradigm shift from conventional computational methods, often demanding manual processing, to a fully autonomous process. The performance of the proposed cell rotation tomography approach is validated through the three-dimensional reconstruction of cell phantoms and HL60 human cancer cells. The versatility of this learning-based tomographic reconstruction workflow paves the way for its broad application across diverse tomographic imaging modalities, including but not limited to flow cytometry tomography and acoustic rotation tomography. Therefore, this AI-driven approach can propel advancements in cell biology, aiding in the inception of pioneering therapeutics, and augmenting early-stage cancer diagnostics.

Long-range three-dimensional tracking of nanoparticles using interferometric scattering (iSCAT) microscopy

Kiarash Kasaian, Mahdi Mazaheri, Vahid Sandoghdar

Tracking nanoparticle movement is highly desirable in many scientific areas, and various imaging methods have been employed to achieve this goal. Interferometric scattering (iSCAT) microscopy has been particularly successful in combining very high spatial and temporal resolution for tracking small nanoparticles in all three dimensions. However, previous works have been limited to an axial range of only a few hundred nanometers. Here, we present a robust and efficient strategy for localizing nanoparticles recorded in high-speed iSCAT videos in three dimensions over tens of micrometers. We showcase the performance of our algorithm by tracking gold nanoparticles as small as 10 nm diffusing in water while maintaining 5 {\mu}s temporal resolution and nanometer axial localization precision. Our results hold promise for applications in cell biology and material science, where the three-dimensional motion of nanoparticles in complex media is of interest.<br>

Multipoles from Majorana constellations

J. L. Romero, A. B. Klimov, A. Z. Goldberg, Gerd Leuchs, Luis Sanchez-Soto

Majorana stars, the 2S spin coherent states that are orthogonal to a spin-S state, offer an elegant method to visualize quantum states, disclosing their intrinsic symmetries. These states are naturally described by the corresponding multipoles. These quantities can be experimentally determined and allow for an SU(2)-invariant analysis. We investigate the relationship between Majorana constellations and state multipoles, thus providing insights into the underlying symmetries of the system. We illustrate our approach with some relevant and informative examples.

Optoacoustic entanglement in a continuous Brillouin-active solid state system

Changlong Zhu, Claudiu Genes, Birgit Stiller

Entanglement in hybrid quantum systems comprised of fundamentally different degrees of freedom, such as light and mechanics is of interest for a wide range of applications in quantum technologies. Here, we propose to engineer bipartite entanglement between traveling acoustic phonons in a Brillouin active solid state system and the accompanying light wave. The effect is achieved by applying optical pump pulses to state-of-the-art waveguides, exciting a Brillouin Stokes process. This pulsed approach, in a system operating in a regime orthogonal to standard optomechanical setups, allows for the generation of entangled photon-phonon pairs, resilient to thermal fluctuations. We propose an experimental platform where readout of the optoacoustics entanglement is done by the simultaneous detection of Stokes and Anti-Stokes photons in a two-pump configuration. The proposed mechanism presents an important feature in that it does not require initial preparation of the quantum ground state of the phonon mode.<br>

Tensed axons are on fire

Kristian Franze

Eavesdropper localization for quantum and classical channels via nonlinear scattering

Alexandra Popp, Florian Sedlmeir, Birgit Stiller, Christoph Marquardt

Optical fiber networks are part of the important critical infrastructure and known to be prone to eavesdropping attacks. Hence, cryptographic methods have to be used to protect communication. Quantum key distribution (QKD), at its core, offers information theoretical security based on the laws of physics. In deployments, one has to take into account practical security and resilience. The latter includes the localization of a possible eavesdropper after an anomaly has been detected by the QKD system to avoid denial-of-service. Here, we present an approach to eavesdropper location that can be employed in quantum as well as classical channels using stimulated Brillouin scattering. The tight localization of the acoustic wave inside the fiber channel using correlated pump and probe waves allows discovery of the coordinates of a potential threat within centimeters. We demonstrate that our approach outperforms conventional optical time-domain reflectometry (OTDR) in the task of localizing an evanescent outcoupling of 1% with centimeter precision inside standard optical fibers. The system is furthermore able to clearly distinguish commercially available standard SMF28 from different manufacturers, paving the way for fingerprinted fibers in high-security environments.

Catch and release of propagating bosonic field with non-Markovian giant atom

Luting Xu, Lingzhen Guo

The non-Markovianity of physical systems is considered to be a valuable resource that has potential applications to quantum information processing. The control of traveling quantum fields encoded with information (flying qubit) is crucial for quantum networks. In this work, we propose to catch and release the propagating photon/phonon with a non-Markovian giant atom, which is coupled to the environment via multiple coupling points. Based on the Heisenberg equation of motion for the giant atom and field operators, we calculate the time- dependent scattering coefficients from the linear response theory and define the criteria for the non-Markovian giant atom. We analyze and numerically verify that the field bound states due to non-Markovianity can be harnessed to catch and release the propagating bosonic field on demand by tuning the parameters of giant atom.

Optoacoustic Cooling of Traveling Hypersound Waves

Laura Blázquez Martínez, Philipp Wiedemann, Changlong Zhu, Andreas Geilen, Birgit Stiller

We experimentally demonstrate optoacoustic cooling via stimulated Brillouin-Mandelstam scattering in a 50 cm long tapered photonic crystal fiber. For a 7.38 GHz acoustic mode, a cooling rate of 219 K from room temperature has been achieved. As anti-Stokes and Stokes Brillouin processes naturally break the symmetry of phonon cooling and heating, resolved sideband schemes are not necessary. The experiments pave the way to explore the classical to quantum transition for macroscopic objects and could enable new quantum technologies in terms of storage and repeater schemes.

Engineering Arbitrary Hamiltonians in Phase Space

Lingzhen Guo, Vittorio Peano

We introduce a general method to engineer arbitrary Hamiltonians in the Floquet phase space of a periodically driven oscillator, based on the noncommutative Fourier transformation technique. We establish the relationship between an arbitrary target Floquet Hamiltonian in phase space and the periodic driving potential in real space. We obtain analytical expressions for the driving potentials in real space that can generate novel Hamiltonians in phase space, e.g., rotational lattices and sharp-boundary wells. Our protocol can be realized in a range of experimental platforms for nonclassical state generation and bosonic quantum computation.

Merging automatic differentiation and the adjoint method for photonic inverse design

Alexander Luce, Rasoul Alaee, Fabian Knorr, Florian Marquardt

Optimizing the shapes and topology of physical devices is crucial for both scientific and technological advancements, given their wide-ranging implications across numerous industries and research areas. Innovations in shape and topology optimization have been observed across a wide range of fields, notably structural mechanics, fluid mechanics, and more recently, photonics. Gradient-based inverse design techniques have been particularly successful for photonic and optical problems, resulting in integrated, miniaturized hardware that has set new standards in device performance. To calculate the gradients, there are typically two approaches: namely, either by implementing specialized solvers using automatic differentiation (AD) or by deriving analytical solutions for gradient calculation and adjoint sources by hand. In this work, we propose a middle ground and present a hybrid approach that leverages and enables the benefits of AD for handling gradient derivation while using existing, proven but black-box photonic solvers for numerical solutions. Utilizing the adjoint method, we make existing numerical solvers differentiable and seamlessly integrate them into an AD framework. Further, this enables users to integrate the optimization environment seamlessly with other autodifferentiable components such as machine learning, geometry generation, or intricate post-processing which could lead to better photonic design workflows. We illustrate the approach through two distinct photonic optimization problems: optimizing the Purcell factor of a magnetic dipole in the vicinity of an optical nanocavity and enhancing the light extraction efficiency of a µLED.

Flying Particle Thermosensor in Hollow-Core Fiber Based on Fluorescence Lifetime Measurements

Jasper Freitag, Max Koeppel, Maria N. Romodina, Nicolas Joly, Bernhard Schmauß

Thermosensitive fluorescence lifetime measurements enable accurate thermometry independent of intensity fluctuations along the optical path. Here, we report lifetime-based temperature measurements of a single europium-doped particle optically trapped in an air-filled hollow-core fiber. A frequency-domain fluorescence lifetime measurement setup was integrated into a dual-beam optical trap. The measured apparent lifetime shows a linear temperature dependence of −1.8 µs/K for excitation at 400Hz . The results were repeatable over multiple cooling and heating cycles. In addition to temperature sensing, the influence of the high-power trapping laser on the measured apparent lifetime and fluorescence intensity was investigated. The observed laser-induced particle heating can be exploited to increase the fluorophore's sensitivity and operating range for low-temperature sensing. Fluorescence lifetime measurements of optically trapped particles inside a hollow-core fiber are promising for temperature sensing with micrometer spatial resolution over meter-scale distances.

Discovering Quantum Circuit Components with Program Synthesis

Leopoldo Sarra, Kevin Ellis, Florian Marquardt

Despite rapid progress in the field, it is still challenging to discover new ways to leverage quantum computation: all quantum algorithms must be designed by hand, and quantum mechanics is notoriously counterintuitive. In this paper, we study how artificial intelligence, in the form of program synthesis, may help overcome some of these difficulties, by showing how a computer can incrementally learn concepts relevant to quantum circuit synthesis with experience, and reuse them in unseen tasks. In particular, we focus on the decomposition of unitary matrices into quantum circuits, and show how, starting from a set of elementary gates, we can automatically discover a library of useful new composite gates and use them to decompose increasingly complicated unitaries.

Low-Temperature Sputtered Ultralow-Loss Silicon Nitride for Hybrid Photonic Integration

Shuangyou Zhang, Toby Bi, Irina Harder, Olga Ohletz, Florentina Gannott, Alexander Gumann, Eduard Butzen, Yaojing Zhang, Pascal Del'Haye

Silicon-nitride-on-insulator (Si3N4) photonic circuits have seen tremendous advances in many applications, such as on-chip frequency combs, Lidar, telecommunications, and spectroscopy. So far, the best film quality has been achieved with low pressure chemical vapor deposition (LPCVD) and high-temperature annealing (1200°C). However, high processing temperatures pose challenges to the cointegration of Si3N4 with pre-processed silicon electronic and photonic devices, lithium niobate on insulator (LNOI), and Ge-on-Si photodiodes. This limits LPCVD as a front-end-of-line process. Here, ultralow-loss Si3N4 photonics based on room-temperature reactive sputtering is demonstrated. Propagation losses as low as 5.4 dB m−1 after 400°C annealing and 3.5 dB m−1 after 800°C annealing are achieved, enabling ring resonators with highest optical quality factors of > 10 million and an average quality factor of 7.5 million. To the best of the knowledge, these are the lowest propagation losses achieved with low temperature Si3N4. This ultralow loss enables the generation of microresonator soliton frequency combs with threshold powers of 1.1 mW. The introduced sputtering process offers full complementary metal oxide semiconductor (CMOS) compatibility with front-end silicon electronics and photonics. This could enable hybrid 3D integration of low loss waveguides with integrated lasers and lithium niobate on insulator.

Model-aware reinforcement learning for high-performance Bayesian experimental design in quantum metrology

Federico Belliardo, Fabio Zoratti, Florian Marquardt, Vittorio Giovannetti

Quantum sensors offer control flexibility during estimation by allowing manipulation by the experimenter across various parameters. For each sensing platform, pinpointing the optimal controls to enhance the sensor’s precision remains a challenging task. While an analytical solution might be out of reach, machine learning offers a promising avenue for many systems of interest, especially given the capabilities of contemporary hardware. We have introduced a versatile procedure capable of optimizing a wide range of problems in quantum metrology, estimation, and hypothesis testing by combining model-aware reinforcement learning (RL) with Bayesian estimation based on particle filtering. To achieve this, we had to address the challenge of incorporating the many non-differentiable steps of the estimation in the training process, such as measurements and the resampling of the particle filter. Model-aware RL is a gradient-based method, where the derivatives of the sensor’s precision are obtained through automatic differentiation (AD) in the simulation of the experiment. Our approach is suitable for optimizing both non-adaptive and adaptive strategies, using neural networks or other agents. We provide an implementation of this technique in the form of a Python library called qsensoropt, alongside several pre-made applications for relevant physical platforms, namely NV centers, photonic circuits, and optical cavities. This library will be released soon on PyPI. Leveraging our method, we’ve achieved results for many examples that surpass the current state-of-the-art in experimental design. In addition to Bayesian estimation, leveraging model-aware RL, it is also possible to find optimal controls for the minimization of the Cram ́er-Rao bound, based on Fisher information.

Broadband Spectroscopy and Interferometry with Undetected Photons at Strong Parametric Amplification

Kazuki Hashimoto, Dmitri B. Horoshko, Maria Chekhova

Nonlinear interferometry with entangled photons allows for characterizing a sample without detecting the photons interacting with it. This method enables highly sensitive optical sensing in the wavelength regions where efficient detectors are still under development. Recently, nonlinear interferometry has been applied to interferometric measurement techniques with broadband light sources, such as Fourier-transform infrared spectroscopy and infrared optical coherence tomography. However, they have been demonstrated with photon pairs produced through spontaneous parametric down-conversion (SPDC) at a low parametric gain, where the average number of photons per mode is much smaller than one. The regime of high-gain SPDC offers several important advantages, such as the amplification of light after its interaction with the sample and a large number of photons per mode at the interferometer output. This work presents broadband spectroscopy and high-resolution optical coherence tomography with undetected photons generated via high-gain SPDC in an aperiodically poled lithium niobate crystal. To prove the principle, reflective Fourier-transform near-infrared spectroscopy with a spectral bandwidth of 17 THz and optical coherence tomography with an axial resolution of 11 µm are demonstrated.<br>

Microresonator soliton frequency combs via cascaded Brillouin scattering

Hao Zhang, Shuangyou Zhang, Toby Bi, George N. Ghalanos, Yaojing Zhang, Haochen Yan, Arghadeep Pal, Jijun He, Shilong Pan, et al.

We demonstrate Kerr soliton frequency comb generation that is seeded by a cascaded Brillouin scattering process. In this process, a pump laser is used to generate multiple orders of Brillouin sidebands in a microresonator, which in turn generate the soliton. In such a process, even orders of Brillouin scattering sidebands are co-propagating with respect to the pump laser while odd orders of Brillouin scattering are backwards propagating. In this work we present the generation of forward propagating Kerr solitons via a forward propagating second order Brillouin scattering process in a fused silica rod resonator. Importantly, we show that the Brillouin scattering process can bridge the gap between different microresonator mode families, such that the repetition rate of the Kerr soliton is independent from the Brillouin gain frequency shift (about 10 GHz in fused silica). In our work we demonstrate this by generating soliton pulse trains with a repetition rate of 107 GHz. Our work opens up a new way for using cascaded Brillouin lasing as a seed for microresonator frequency comb generation. This can be of particular interest for the realization of soliton frequency combs with low noise properties from Brillouin lasing while still having arbitrary repetition rates that are determined by the resonator size. Applications range from optical communication to LIDAR systems and photonic signal generation.

Residual cells and nutrient availability guide wound healing in bacterial biofilms

Yusong Ye, Mnar Ghrayeb, Sarah Miercke, Sania Arif, Susann Müller, Thorsten Mascher, Liraz Chai, Vasily Zaburdaev

Biofilms are multicellular heterogeneous bacterial communities characterized by social-like division of labor, and remarkable robustness with respect to external stresses. Increasingly often an analogy between biofilms and arguably more complex eukaryotic tissues is being drawn. One illustrative example of where this analogy can be practically useful is the process of wound healing. While it has been extensively studied in eukaryotic tissues, the mechanism of wound healing in biofilms is virtually unexplored. Combining experiments in Bacillus subtilis bacteria, a model organism for biofilm formation, and a lattice-based theoretical model of biofilm growth, we studied how biofilms recover after macroscopic damage. We suggest that nutrient gradients and the abundance of proliferating cells are key factors augmenting wound closure. Accordingly, in the model, cell quiescence, nutrient fluxes, and biomass represented by cells and self-secreted extracellular matrix are necessary to qualitatively recapitulate the experimental results for damage repair. One of the surprising experimental findings is that residual cells, persisting in a damaged area after removal of a part of the biofilm, prominently affect the healing process. Taken together, our results outline the important roles of nutrient gradients and residual cells on biomass regrowth on macroscopic scales of the whole biofilm. The proposed combined experiment–simulation framework opens the way to further investigate the possible relation between wound healing, cell signaling and cell phenotype alternation in the local microenvironment of the wound.

Temporally Distilled High-Dimensional Biphotonic States from Thin Sources

Vitaliy Sultanov, Maria Chekhova

Generation of entangled photons through spontaneous parametric down-conversion (SPDC) from micro- and nanoscale sources offers unprecedented freedom in quantum state engineering, including the ability to generate two-photon states with high-dimensional hyperentanglement. However, as the source of SPDC gets smaller, the role of photoluminescence increases, which leads to the contamination of two-photon states with a thermal background. Here we propose and implement a solution to this problem: by using pulsed SPDC and time distillation, we increase the purity and the heralding efficiency of the photon pairs. In the experiment, we increased the purity of the two-photon states generated in a 7 μm film of lithium niobate from 0.002 to 0.99. With the higher purity we were able to observe and characterize different polarization states of photon pairs generated simultaneously due to relaxed phase matching. In particular, we showed the presence of orthogonally polarized photons that are potentially usable for the generation of polarization entanglement.

Spectral splitting of a stimulated Raman transition in a single molecule

Johannes Zirkelbach, Burak Gürlek, Masoud Mirzaei, Alexey Shkarin, Tobias Utikal, Stephan Götzinger, Vahid Sandoghdar

The small cross-section of Raman scattering poses a great challenge for its direct study at the single-molecule level. By exploiting the high Franck-Condon factor of a common-mode resonance, choosing a large vibrational frequency difference in electronic ground and excited states and operating at T<2K, we succeed at driving a coherent stimulated Raman transition in individual molecules. We observe and model a spectral splitting that serves as a characteristic signature of the phenomenon at hand. Our study sets the ground for exploiting the intrinsic optomechanical degrees of freedom of molecules for applications in solid-state quantum optics and information processing.

Experimental Solutions to the High-Dimensional Mean King's Problem

Tareq Jaouni, Xiaoqin Gao, Sören Arlt, Mario Krenn, Ebrahim Karimi

Vaidman, Aharanov, and Albert [Phys. Rev. Lett. 58(14), 1385 (1987)] put forward a puzzle called the mean king’s problem (MKP) that can be solved only by harnessing quantum entanglement. Prime-powered solutions to the problem have been shown to exist, but they have not yet been experimentally realized for any dimension beyond two. We propose a general first-of-its-kind experimental scheme for solving the MKP in prime dimensions (D). Our search is guided by the digital discovery framework Pytheus, which finds highly interpretable graph-based representations of quantum optical experimental setups; using it, we find specific solutions and generalize to higher dimensions through human insight. As proof of principle, we present a detailed investigation of our solution for the three-, five-, and seven-dimensional cases. We obtain maximum success probabilities of 82.3%, 56.2%, and 35.5%, respectively. We therefore posit that our computer-inspired scheme yields solutions that implement Alice’s strategy with quantum advantage, demonstrating its promise for experimental implementation in quantum communication tasks.

Digital Discovery of 100 diverse Quantum Experiments with PyTheus

Carlos Ruiz-Gonzalez, Sören Arlt, Jan Petermann, Sharareh Sayyad, Tareq Jaouni, Ebrahim Karimi, Nora Tischler, Xuemei Gu, Mario Krenn

Photons are the physical system of choice for performing experimental tests of the foundations of quantum mechanics. Furthermore, photonic quantum technology is a main player in the second quantum revolution, promising the development of better sensors, secure communications, and quantum-enhanced computation. These endeavors require generating specific quantum states or efficiently performing quantum tasks. The design of the corresponding optical experiments was historically powered by human creativity but is recently being automated with advanced computer algorithms and artificial intelligence. While several computer-designed experiments have been experimentally realized, this approach has not yet been widely adopted by the broader photonic quantum optics community. The main roadblocks consist of most systems being closed-source, inefficient, or targeted to very specific use-cases that are difficult to generalize. Here, we overcome these problems with a highly-efficient, open-source digital discovery framework PyTheus, which can employ a wide range of experimental devices from modern quantum labs to solve various tasks. This includes the discovery of highly entangled quantum states, quantum measurement schemes, quantum communication protocols, multi-particle quantum gates, as well as the optimization of continuous and discrete properties of quantum experiments or quantum states. PyTheus produces interpretable designs for complex experimental problems which human researchers can often readily conceptualize. PyTheus is an example of a powerful framework that can lead to scientific discoveries -- one of the core goals of artificial intelligence in science. We hope it will help accelerate the development of quantum optics and provide new ideas in quantum hardware and technology.

Boosting the Gottesman-Kitaev-Preskill quantum error correction with non-Markovian feedback

Matteo Puviani, Sangkha Borah, Remmy Zen, Jan Olle, Florian Marquardt

Bosonic codes allow the encoding of a logical qubit in a single component device, utilizing the infinitely large Hilbert space of a harmonic oscillator. In particular, the Gottesman-Kitaev-Preskill code has recently been demonstrated to be correctable well beyond the break-even point of the best passive encoding in the same system. Current approaches to quantum error correction (QEC) for this system are based on protocols that use feedback, but the response is based only on the latest measurement outcome. In our work, we use the recently proposed Feedback-GRAPE (Gra- dient Ascent Pulse Engineering with Feedback) method to train a recurrent neural network that provides a QEC scheme based on memory, responding in a non-Markovian way to the full history of previous measurement outcomes, optimizing all subsequent unitary operations. This approach sig- nificantly outperforms current strategies and paves the way for more powerful measurement-based QEC protocols.

Digital Discovery of interferometric Gravitational Wave Detectors

Mario Krenn, Yehonathan Drori, Rana X Adhikari

Gravitational waves, detected a century after they were first theorized, are spacetime distortions caused by some of the most cataclysmic events in the universe, including black hole mergers and supernovae. The successful detection of these waves has been made possible by ingenious detectors designed by human experts. Beyond these successful designs, the vast space of experimental config- urations remains largely unexplored, offering an exciting territory potentially rich in innovative and unconventional detection strategies. Here, we demonstrate the application of artificial intelligence (AI) to systematically explore this enormous space, revealing novel topologies for gravitational wave (GW) detectors that outperform current next-generation designs under realistic experimental con- straints. Our results span a broad range of astrophysical targets, such as black hole and neutron star mergers, supernovae, and primordial GW sources. Moreover, we are able to conceptualize the initially unorthodox discovered designs, emphasizing the potential of using AI algorithms not only in discovering but also in understanding these novel topologies. We’ve assembled more than 50 superior solutions in a publicly available Gravitational Wave Detector Zoo which could lead to many new surprising techniques. At a bigger picture, our approach is not limited to gravitational wave detectors and can be extended to AI-driven design of experiments across diverse domains of fundamental physics.

Topological Properties of a Non-Hermitian Quasi-1D Chainwith a Flat Band

C. Martínez-Strasser, M. A. J. Herrera, G. Palumbo, Flore K. Kunst, D. Bercioux

The spectral properties of a non-Hermitian quasi-1D lattice in two of the possible dimerization configurations are investigated. Specifically, it focuses on a non-Hermitian diamond chain that presents a zero-energy flat band. The flat band originates from wave interference and results in eigenstates with a finite contribution only on two sites of the unit cell. To achieve the non-Hermitian characteristics, the system under study presents non-reciprocal hopping terms in the chain. This leads to the accumulation of eigenstates on the boundary of the system, known as the non-Hermitian skin effect. Despite this accumulation of eigenstates, for one of the two considered configurations, it is possible to characterize the presence of non-trivial edge states at zero energy by a real-space topological invariant known as the biorthogonal polarization. This work shows that this invariant, evaluated using the destructive interference method, characterizes the non-trivial phase of the non-Hermitian diamond chain. For the second non-Hermitian configuration, there is a finite quantum metric associated with the flat band. Additionally, the system presents the skin effect despite the system having a purely real or imaginary spectrum. The two non-Hermitian diamond chains can be mapped into two models of the Su-Schrieffer-Heeger chains, either non-Hermitian, and Hermitian, both in the presence of a flat band. This mapping allows to draw valuable insights into the behavior and properties of these systems.<br><br>

Optimizing ZX-Diagrams with Deep Reinforcement Learning

Maximilian Nägele, Florian Marquardt

ZX-diagrams are a powerful graphical language for the description of quantum processes with applications in fundamental quantum mechanics, quantum circuit optimization, tensor network simulation, and many more. The utility of ZX-diagrams relies on a set of local transformation rules that can be applied to them without changing the underlying quantum process they describe. These rules can be exploited to optimize the structure of ZX-diagrams for a range of applications. However, finding an optimal sequence of transformation rules is generally an open problem. In this work, we bring together ZX-diagrams with reinforcement learning, a machine learning technique designed to discover an optimal sequence of actions in a decision-making problem and show that a trained reinforcement learning agent can significantly outperform other optimization techniques like a greedy strategy or simulated annealing. The use of graph neural networks to encode the policy of the agent enables generalization to diagrams much bigger than seen during the training phase.

On-chip interference of scattering from two individual molecules

Dominik Rattenbacher, Alexey Shkarin, Jan Renger, Tobias Utikal, Stephan Götzinger, Vahid Sandoghdar

Integrated photonic circuits offer a promising route for studying coherent cooperative effects of a controlled collection of quantum emitters. However, spectral inhomogeneities, decoherence, and material incompatibilities in the solid state make this a nontrivial task. Here, we demonstrate efficient coupling of a pair of Fourier-limited organic molecules embedded in a polyethylene film to a TiO2 microdisc resonator on a glass chip. Moreover, we tune the resonance frequencies of the emitters with respect to that of the microresonator by employing nanofabricated electrodes. For two molecules separated by a distance of about 8 µm and an optical phase difference of about pi/2, we report on a large collective extinction of the incident light in the forward direction and the destructive interference of its scattering in the backward direction. Our work sets the ground for coherent coupling of several quantum emitters via a common mode and realization of polymer-based hybrid quantum photonic circuits.

Symmetry-protected exceptional and nodal points in non-Hermitian systems

Sharareh Sayyad, Marcus Stålhammar, Lukas Rødland, Flore K. Kunst

One of the unique features of non-Hermitian (NH) systems is the appearance of non-Hermitian degeneracies known as exceptional points~(EPs). The occurrence of EPs in NH systems requires satisfying constraints whose number can be reduced in the presence of some symmetries. This results in stabilizing the appearance of EPs. Even though two different types of EPs, namely defective and non-defective EPs, may emerge in NH systems, exploring the possibilities of stabilizing EPs has been only addressed for defective EPs, at which the Hamiltonian becomes non-diagonalizable. In this letter, we show that certain discrete symmetries, namely parity-time, parity-particle-hole, and pseudo-Hermitian symmetry, may guarantee the occurrence of both defective and non-defective EPs. We extend this list of symmetries by including the non-Hermitian time-reversal symmetry in the two-band systems. <br>We further show that the non-defective EPs manifest themselves by i) the diagonalizability of non-Hermitian Hamiltonian at these points and ii) the non-diagonalizability of the Hamiltonian along certain intersections of non-defective EPs. Two-band and four-band models exemplify our findings. Through an example, we further reveal that ordinary (Hermitian) nodal points may coexist with defective EPs in non-Hermitian models when the above symmetries are relaxed.

Geometry optimization for dark soliton combs in thin multimode silicon nitride microresonators

Yaojing Zhang, Shuangyou Zhang, Toby Bi, Pascal Del'Haye

Silicon nitride (Si3N4) has been well established as an ultralow-loss material for integrated photonics, particularly for the generation of dissipative Kerr soliton frequency combs, enabling various applications for optical metrology, biological imaging, and coherent telecommunications. Typically, bright soliton generation in Si3N4 devices requires thick (>600 nm) films to fulfill the condition of anomalous dispersion at telecom wavelengths. However, thick films of ultralow-loss Si3N4 (>400 nm) often suffer from high internal stress, leading to cracks. As an alternative approach, thin Si3N4 films (<400 nm) provide the advantage of one-step deposition and are widely applied for commercial use. Here, we provide insights into engineering an integrated Si3N4 structure that achieves optimal effective nonlinearity and maintains a compact footprint. A comparative analysis of Si3N4 resonators with varying waveguide thicknesses is conducted and reveals that a 400-nm thin Si3N4 film emerges as a promising solution that strikes a balance among the aforementioned criteria. Based on a commercially available 400-nm Si3N4 film, we experimentally demonstrate the generation of low-noise coherent dark pulses with a repetition rate of 25 GHz in a multimode Si3N4 resonator. The compact spiral-shaped resonator has a footprint of 0.28 mm2 with a high-quality factor of 4 × 106. Our demonstrated dark combs with mode spacings of tens of GHz have applications in microwave photonics, optical spectroscopy, and telecommunication systems.

No-Collapse Accurate Quantum Feedback Control via Conditional State Tomography

Sangkha Borah, Bijita Sarma

The effectiveness of measurement-based feedback control (MBFC) protocols is hindered by the presence of measurement noise, which impairs the ability to accurately infer the underlying dynamics of a quantum system from noisy continuous measurement records. To circumvent this limitation, a real-time stochastic state estimation approach is proposed in this work, that enables noise-free monitoring of the conditional dynamics, including the full density matrix of the quantum system, despite using noisy measurement data. This, in turn, enables the development of precise MBFC strategies that leads to effective control of quantum systems by essentially mitigating the constraints imposed by measurement noise, and has potential applications in various feedback quantum control scenarios. This approach is particularly important for machine learning-based control, where the AI controller can be trained with arbitrary conditional averages of observables, including the full density matrix, to quickly and accurately learn control strategies.

Massive quantum systems as interfaces of quantum mechanics and gravity

Sougato Bose, Ivette Fuentes, Andrew A. Geraci, Saba Mehsar Khan, Sofia Qvarfort, Markus Rademacher, Muddassar Rashid, Marko Toroš, Hendrik Ulbricht, et al.

The traditional view from particle physics is that quantum gravity effects should only become detectable at extremely high energies and small length scales. Due to the sig- nificant technological challenges involved, there has been limited progress in identifying experimentally detectable effects that can be accessed in the foreseeable future. How- ever, in recent decades, the size and mass of quantum systems that can be controlled in the laboratory have reached unprecedented scales, enabled by advances in ground-state cooling and quantum-control techniques. Preparations of massive systems in quantum states paves the way for the explorations of a low-energy regime in which gravity can be both sourced and probed by quantum systems. Such approaches constitute an in- creasingly viable alternative to accelerator-based, laser-interferometric, torsion-balance, and cosmological tests of gravity. In this review, we provide an overview of propos- als where massive quantum systems act as interfaces between quantum mechanics and gravity. We discuss conceptual difficulties in the theoretical description of quantum systems in the presence of gravity, review tools for modeling massive quantum systems in the laboratory, and provide an overview of the current state-of-the-art experimen- tal landscape. Proposals covered in this review include, among others, precision tests of gravity, tests of gravitationally-induced wavefunction collapse and decoherence, as well as gravity-mediated entanglement. We conclude the review with an outlook and discussion of future questions.

Insights into protein structure using cryogenic light microscopy

Hisham Mazal, Franz Wieser, Vahid Sandoghdar

Fluorescence microscopy has witnessed many clever innovations in the last two decades, leading to new methods such as structured illumination and super-resolution microscopies. The attainable resolution in biological samples is, however, ultimately limited by residual motion within the sample or in the microscope setup. Thus, such experiments are typically performed on chemically fixed samples. Cryogenic light microscopy (Cryo-LM) has been investigated as an alternative, drawing on various preservation techniques developed for cryogenic electron microscopy (Cryo-EM). Moreover, this approach offers a powerful platform for correlative microscopy. Another key advantage of Cryo-LM is the strong reduction in photobleaching at low temperatures, facilitating the collection of orders of magnitude more photons from a single fluorophore. This results in much higher localization precision, leading to Angstrom resolution. In this review, we discuss the general development and progress of Cryo-LM with an emphasis on its application in harnessing structural information on proteins and protein complexes.

Mechanics in the nervous system: From development to disease

Eva K. Pillai, Kristian Franze

Physical forces are ubiquitous in biological processes across scales and diverse contexts. This review highlights the significance of mechanical forces in nervous system development, homeostasis, and disease. We provide an overview of mechanical signals present in the nervous system and delve into mechanotransduction mechanisms translating these mechanical cues into biochemical signals. During development, mechanical cues regulate a plethora of processes, including cell proliferation, differentiation, migration, network formation, and cortex folding. Forces then continue exerting their influence on physiological processes, such as neuronal activity, glial cell function, and the interplay between these different cell types. Notably, changes in tissue mechanics manifest in neurodegenerative diseases and brain tumors, potentially offering new diagnostic and therapeutic target opportunities. Understanding the role of cellular forces and tissue mechanics in nervous system physiology and pathology adds a new facet to neurobiology, shedding new light on many processes that remain incompletely understood.

Regenerative capacity of neural tissue scales with changes in tissue mechanics post injury

Alejandro Carnicer-Lombarte, Damiano G. Barone, Filip Wronowski, George G. Malliaras, James W. Fawcett, Kristian Franze

Spinal cord injuries have devastating consequences for humans, as mammalian neurons of the central nervous system (CNS) cannot regenerate. In the peripheral nervous system (PNS), however, neurons may regenerate to restore lost function following injury. While mammalian CNS tissue softens after injury, how PNS tissue mechanics changes in response to mechanical trauma is currently poorly understood. Here we characterised mechanical rat nerve tissue properties before and after in vivo crush and transection injuries using atomic force microscopy-based indentation measurements. Unlike CNS tissue, PNS tissue significantly stiffened after both types of tissue damage. This nerve tissue stiffening strongly correlated with an increase in collagen I levels. Schwann cells, which crucially support PNS regeneration, became more motile and proliferative on stiffer substrates in vitro, suggesting that changes in tissue stiffness may play a key role in facilitating or impeding nervous system regeneration.

Simultaneous Discovery of Quantum Error Correction Codes and Encoders with a Noise-Aware Reinforcement Learning Agent

Jan Olle, Remmy Zen, Matteo Puviani, Florian Marquardt

Finding optimal ways to protect quantum states from noise remains an outstanding challenge across all quantum technologies, and quantum error correction (QEC) is the most promising strategy to address this issue. Constructing QEC codes is a complex task that has historically been powered by human creativity with the discovery of a large zoo of families of codes. However, in the context of real-world scenarios there are two challenges: these codes have typically been categorized only for their performance under an idealized noise model and the implementation-specific optimal encoding circuit is not known. In this work, we train a Deep Reinforcement Learning agent that automatically discovers both QEC codes and their encoding circuits for a given gate set, qubit connectivity, and error model. We introduce the concept of a noise-aware meta-agent, which learns to produce encoding strategies simultaneously for a range of noise models, thus leveraging transfer of insights between different situations. Moreover, thanks to the use of the stabilizer formalism and a vectorized Clifford simulator, our RL implementation is extremely efficient, allowing us to produce many codes and their encoders from scratch within seconds, with code distances varying from 3 to 5 and with up to 20 physical qubits. Our approach opens the door towards hardware-adapted accelerated discovery of QEC approaches across the full spectrum of quantum hardware platforms of interest.

Realizing a deep reinforcement learning agent discovering real-time feedback control strategies for a quantum system

Kevin Reuer, Jonas Landgraf, Thomas Fösel, James O'Sullivan, Liberto Beltrán, Abdulkadir Akin, Graham J. Norris, Ants Remm, Michael Kerschbaum, et al.

Realizing the full potential of quantum technologies requires precise real-time control on time scales much shorter than the coherence time. Model-free reinforcement learning promises to discover efficient feedback strategies from scratch without relying on a description of the quantum system. However, developing and training a reinforcement learning agent able to operate in real-time using feedback has been an open challenge. Here, we have implemented such an agent for a single qubit as a sub-microsecond-latency neural network on a field-programmable gate array (FPGA). We demonstrate its use to efficiently initialize a superconducting qubit and train the agent based solely on measurements. Our work is a first step towards adoption of reinforcement learning for the control of quantum devices and more generally any physical device requiring low-latency feedback.<br>

Bile Is a Selective Elevator for Mucosal Mechanics and Transport

Simon Hanio, Stephanie Möllmert, Conrad Möckel, Susobhan Choudhury, Andreas I. Höpfel, Theresa Zorn, Sebastian Endres, Jonas Schlauersbach, Lena Scheller, et al.

Mucus mechanically protects the intestinal epithelium and impacts the absorption of drugs, with a largely unknown role for bile. We explored the impacts of bile on mucosal biomechanics and drug transport within mucus. Bile diffused with square-root-of-time kinetics and interplayed with mucus, leading to transient stiffening captured in Brillouin images and a concentration-dependent change from subdiffusive to Brownian-like diffusion kinetics within the mucus demonstrated by differential dynamic microscopy. Bile-interacting drugs, Fluphenazine and Perphenazine, diffused faster through mucus in the presence of bile, while Metoprolol, a drug with no bile interaction, displayed consistent diffusion. Our findings were corroborated by rat studies, where co-dosing of a bile acid sequestrant substantially reduced the bioavailability of Perphenazine but not Metoprolol. We clustered over 50 drugs based on their interactions with bile and mucin. Drugs that interacted with bile also interacted with mucin but not vice versa. This study detailed the dynamics of mucus biomechanics under bile exposure and linked the ability of a drug to interact with bile to its abbility to interact with mucus.

Near-Petahertz Fieldoscopy of Liquid

Anchit Srivastava, Andreas Herbst, Mahdi M. Bidhendi, Max Kieker, Francesco Tani, Hanieh Fattahi

Measuring transient optical field is pivotal not only for understanding ultrafast phenomena but also for quantitative detection of various molecular species in a sample. In this work, we demonstrate near-petahertz electric field detection of a few femtosecond pulses with 2oo attosecond temporal resolution, 10 detection dynamic range in electric field and sub-femtojoule detection sensitivity, exceeding those reported by the current methods. By field-resolved detection of the impulsively excited molecules in the liquid phase, termed 'femtosecond fieldoscopy', we demonstrate temporal isolation of the response of the target molecules from those of the environment and the excitation pulse. In a proof-of-concept analysis of aqueous and liquid samples, we demonstrate field-sensitive detection of combination bands of 4.13 {\mu}mol ethanol for the first time. This method expands the scope of aqueous sample analysis to higher detection sensitivity and dynamic range, while the simultaneous direct measurements of phase and intensity information pave the path towards high-resolution biological spectro-microscopy

Deep Bayesian Experimental Design for Quantum Many-Body Systems

Leopoldo Sarra, Florian Marquardt

Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain. Recent developments in deep neural networks and normalizing flows allow for a more efficient approximation of the posterior and thus the extension of this technique to complex high-dimensional situations. In this paper, we show how this approach holds promise for adaptive measurement strategies to characterize present-day quantum technology platforms. In particular, we focus on arrays of coupled cavities and qubit arrays. Both represent model systems of high relevance for modern applications, like quantum simulations and computing, and both have been realized in platforms where measurement and control can be exploited to characterize and counteract unavoidable disorder. Thus, they represent ideal targets for applications of Bayesian experimental design.

Small leucine-rich proteoglycans inhibit CNS regeneration by modifying the structural and mechanical properties of the lesion environment

Julia Kolb, Vasiliki Tsata, Nora John, Kyoohyun Kim, Conrad Möckel, Gonzalo Rosso, Veronika Kurbel, Asha Parmar, Gargi Sharma, et al.

Extracellular matrix (ECM) deposition after central nervous system (CNS) injury leads to inhibitory scarring in humans and other mammals, whereas it facilitates axon regeneration in the zebrafish. However, the molecular basis of these different fates is not understood. Here, we identify small leucine-rich proteoglycans (SLRPs) as a contributing factor to regeneration failure in mammals. We demonstrate that the SLRPs chondroadherin, fibromodulin, lumican, and prolargin are enriched in rodent and human but not zebrafish CNS lesions. Targeting SLRPs to the zebrafish injury ECM inhibits axon regeneration and functional recovery. Mechanistically, we find that SLRPs confer mechano-structural properties to the lesion environment that are adverse to axon growth. Our study reveals SLRPs as inhibitory ECM factors that impair axon regeneration by modifying tissue mechanics and structure, and identifies their enrichment as a feature of human brain and spinal cord lesions. These findings imply that SLRPs may be targets for therapeutic strategies to promote CNS regeneration.

Restoration of the non-Hermitian bulk-boundary correspondence viatopological amplification

Matteo Brunelli, Clara C. Wanjura, Andreas Nunnenkamp

Non-Hermitian (NH) lattice Hamiltonians display a unique kind of energy gap and ex- treme sensitivity to boundary conditions. Due to the NH skin effect, the separation between edge and bulk states is blurred and the (conventional) bulk-boundary corre- spondence is lost. Here, we restore the bulk-boundary correspondence for the most paradigmatic class of NH Hamiltonians, namely those with one complex band and with- out symmetries. We obtain the desired NH Hamiltonian from the mean-field evolution of driven-dissipative cavity arrays, in which NH terms—in the form of non-reciprocal hopping amplitudes, gain and loss—are explicitly modeled via coupling to (engineered and non-engineered) reservoirs. This approach removes the arbitrariness in the defini- tion of the topological invariant, as point-gapped spectra differing by a complex-energy shift are not treated as equivalent; the origin of the complex plane provides a common reference (base point) for the evaluation of the topological invariant. This implies that topologically non-trivial Hamiltonians are only a strict subset of those with a point gap and that the NH skin effect does not have a topological origin. We analyze the NH Hamil- tonians so obtained via the singular value decomposition, which allows to express the NH bulk-boundary correspondence in the following simple form: an integer value ν of the topological invariant defined in the bulk corresponds to |ν| singular vectors exponen- tially localized at the system edge under open boundary conditions, in which the sign of ν determines which edge. Non-trivial topology manifests as directional amplification of a coherent input with gain exponential in system size. Our work solves an outstanding problem in the theory of NH topological phases and opens up new avenues in topological photonics.

Plasmon-enhanced circular dichroism spectroscopy of chiral drug solutions

Matteo Venturi, Raju Adhikary, Ambaresh Sahoo, Carino Ferrante, Isabella Daidone, Francesco Di Stasio, Andrea Toma, Francesco Tani, Hatice Altug, et al.

We investigate the potential of surface plasmon polaritons at noble metal interfaces for surface-enhanced chiroptical sensing of dilute chiral drug solutions with nl volume. The high quality factor of surface plasmon resonances in both Otto and Kretschmann configurations enables the enhancement of circular dichroism differenatial absorption thanks to the large near-field intensity of such plasmonic excitations. Further- more, the subwavelength confinement of surface plasmon polaritons is key to attain chiroptical sensitivity to small amounts of drug volumes placed around ≃ 100 nm by the metal surface. Our calculations focus on reparixin, a pharmaceutical molecule currently used in clinical studies for patients with community-acquired pneumonia, including COVID-19 and acute respiratory distress syndrome. Considering realistic dilute solutions of reparixin dissolved in water with concentration ≤5 mg/ml and nl volume, we find a circular-dichroism differential absorption enhancement factor of the order ≃20 and chirality-induced polarization distortion upon surface plasmon polariton excitation. Our results are relevant for the development of innovative chiroptical sensors capable of measuring the enantiomeric imbalance of chiral drug solutions with nl volume.

Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network

Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, Joao P. Moutinho, et al.

A tool that could suggest new personalized research directions and ideas by taking insights from the scientific literature could profoundly accelerate the progress of science. A field that might benefit from such an approach is artificial intelligence (AI) research, where the number of scientific publications has been growing exponentially over recent years, making it challenging for human researchers to keep track of the progress. Here we use AI techniques to predict the future research directions of AI itself. We introduce a graph-based benchmark based on real-world data—the Science4Cast benchmark, which aims to predict the future state of an evolving semantic network of AI. For that, we use more than 143,000 research papers and build up a knowledge network with more than 64,000 concept nodes. We then present ten diverse methods to tackle this task, ranging from pure statistical to pure learning methods. Surprisingly, the most powerful methods use a carefully curated set of network features, rather than an end-to-end AI approach. These results indicate a great potential that can be unleashed for purely ML approaches without human knowledge. Ultimately, better predictions of new future research directions will be a crucial component of more advanced research suggestion tools.

Experimental Optical Simulator of Reconfigurable and Complex Quantum Environment

P. Renault, J. Nokkala, G. Roeland, Nicolas Y. Joly, R. Zambrini, S. Maniscalco, J. Piilo, N. Treps, V. Parigi

No quantum system can be considered totally isolated from its environment. In most cases the interaction between the system of interest and the external degrees of freedom deeply changes its dynamics, as described by open quantum system theory. Nevertheless engineered environment can be turned into beneficial effects for some quantum information tasks. Here we demonstrate an optical simulator of a quantum system coupled to an arbitrary and reconfigurable environment built as a complex network of quantum interacting systems. We experimentally retrieve typical features of open quantum system dynamics like the spectral density and quantum non-Markovianity, by exploiting squeezing and entanglement correlation of a continuous-variable optical platform. This opens the way to the experimental tests of open quantum systems in reconfigurable environments that are relevant in, among others, quantum information, quantum thermodynamics, quantum transport, and quantum synchronization.

Four-field symmetry breakings in twin-resonator photonic isomers

Alekhya Ghosh, Lewis Hill, Gian-Luca Oppo , Pascal Del'Haye

Symmetry and symmetry breaking of light states play an important role in photonic integrated circuits and have recently attracted lots of research interest that is relevant to the manipulation of light polarization, telecommunications, all optical computing, and more. We consider four-field symmetry breaking within two different configurations of photonic dimer systems, both comprised of two identical Kerr ring resonators. In each configuration we observe multiple degrees and levels of spontaneous symmetry breaking between circulating photon numbers and further, a wide range of oscillatory dynamics, such as chaos and multiple variations of periodic switching. These dynamics are of interest for optical data processing, optical memories, telecommunication systems, and integrated photonic sensors.

Fast quantum control of cavities using an improved protocol without coherent errors

Jonas Landgraf, Christa Flühmann, Thomas Fösel, Florian Marquardt, Robert J. Schoelkopf

The selective number-dependent arbitrary phase (SNAP) gates form a powerful class of quantum gates, imparting arbitrarily chosen phases to the Fock modes of a cavity. However, for short pulses, coherent errors limit the performance. Here we demonstrate in theory and experiment that such errors can be completely suppressed, provided that the pulse times exceed a specific limit. The resulting shorter gate times also reduce incoherent errors. Our approach needs only a small number of frequency components, the resulting pulses can be interpreted easily, and it is compatible with fault-tolerant schemes.

XLuminA: An Auto-differentiating Discovery Framework for Super-Resolution Microscopy

Carla Rodríguez Mangues, Sören Arlt, Leonhard Möckl, Mario Krenn

In this work we introduce XLuminA, an original computational framework designed for the discovery of novel optical hardware in super-resolution microscopy. Our framework offers auto-differentiation capabilities, allowing for the fast and efficient simulation and automated design of entirely new optical setups from scratch. We showcase its potential by re-discovering three foundational experiments, each one covering different areas in optics: an optical telescope, STED microscopy and the focusing beyond the diffraction limit of a radially polarized light beam. Intriguingly, for this last experiment, the machine found an alternative solution following the same physical principle exploited for breaking the diffraction limit. With XLuminA, we can go beyond simple optimization and calibration of known experimental setups, opening the door to potentially uncovering new microscopy concepts within the vast landscape of experimental possibilities.

A probabilistic view of wave-particle duality for single photons

Andrea Aiello

One of the most puzzling consequences of interpreting quantum mechanics in terms of concepts borrowed from classical physics, is the so-called wave-particle duality. Usually, wave-particle duality is illustrated in terms of complementarity between path distinguishability and fringe visibility in interference experiments. In this work, we instead propose a new type of complementarity, that between the continuous nature of waves and the discrete character of particles. Using the probabilistic methods of quantum field theory, we show that the simultaneous measurement of the wave amplitude and the number of photons in the same beam of light is, under certain circumstances, prohibited by the laws of quantum mechanics. Our results suggest that the concept of “interferometric duality'' could be eventually replaced by the more general one of “continuous-discrete duality''.

Low-noise supercontinuum generation in chiral all-normal dispersion photonic crystal fibers

Markus Lippl, Michael H. Frosz, Nicolas Y. Joly

We present the advantages of supercontinuum generation in chiral, therefore circularly birefringent, all-normal dispersion fibers. Due to the absence of nonlinear power transfer between the polarization eigenstates of the fiber, chiral all-normal dispersion fibers do not exhibit any polarization instabilities and thus are an ideal platform for a low-noise supercontinuum generation. By pumping a chiral all-normal dispersion fiber at 802 nm, we obtained an octave-spanning, robustly circularly polarized supercontinuum with a low noise.

Quantum-enhanced interferometer using Kerr squeezing

Nikolay Kalinin, Thomas Dirmeier, Arseny A. Sorokin, Elena A. Anashkina, Luis Sanchez-Soto, Joel F. Corney, Gerd Leuchs, Alexey V. Andrianov

One of the prime applications of squeezed light is enhancing the sensitivity of an interferometer below the quantum shot-noise limit, but so far, no such experimental demonstration was reported when using the optical Kerr effect. In prior setups involving Kerr-squeezed light, the role of the interferometer was merely to characterize the noise pattern. The lack of such a demonstration was largely due to the cumbersome tilting of the squeezed ellipse in phase space. Here, we present the first experimental observation of phase-sensitivity enhancement in an interferometer using Kerr squeezing.

Deep-Learning Approach for the Atomic Configuration Interaction Problem on Large Basis Sets

Pavlo Bilous, Adriana Pálffy, Florian Marquardt

High-precision atomic structure calculations require accurate modeling of electronic correlations typically addressed via the configuration interaction (CI) problem on a multiconfiguration wave function expansion. The latter can easily become challenging or infeasibly large even for advanced supercomputers. Here, we develop a deep-learning approach which allows us to preselect the most relevant configurations out of large CI basis sets until the targeted energy precision is achieved. The large CI computation is thereby replaced by a series of smaller ones performed on an iteratively expanding basis subset managed by a neural network. While dense architectures as used in quantum chemistry fail, we show that a convolutional neural network naturally accounts for the physical structure of the basis set and allows for robust and accurate CI calculations. The method was benchmarked on basis sets of moderate size allowing for the direct CI calculation, and further demonstrated on prohibitively large sets where the direct computation is not possible.

Extreme thermodynamics in nanolitre volumes through stimulated Brillouin–Mandelstam scattering

Andreas Geilen, Alexandra Popp, Debavan Das, Saher Junaid, Christopher G. Poulton, Mario Chemnitz, Christoph Marquardt, Markus A. Schmidt, Birgit Stiller

Examining the physical properties of materials—particularly of toxic liquids—under a wide range of thermodynamic states is a challenging problem due to the extreme conditions the material has to experience. Such temperature and pressure regimes, which result in a change in the refractive index and sound velocity, can be accessed by optoacoustic interactions such as Brillouin–Mandelstam scattering. Here we demonstrate the Brillouin–Mandelstam measurements of nanolitre volumes of liquids in extreme thermodynamic regimes. This is enabled by a fully sealed liquid-core optical fibre containing carbon disulfide. Within this waveguide, which exhibits tight optoacoustic confinement and a high Brillouin gain, we are able to conduct spatially resolved measurements of the local Brillouin response, giving us access to a resolved image of the temperature and pressure values along the liquid channel. We measure the material properties of the liquid core at very large positive pressures (above 1,000 bar) and substantial negative pressures (below –300 bar), as well as explore the isobaric and isochoric regimes. The extensive thermodynamic control allows the tunability of the Brillouin frequency shift of more than 40% using only minute volumes of liquid.

Varying the Stiffness and Diffusivity of Rod-Shaped Microgels Independently through Their Molecular Building Blocks

Yonca Kittel, Luis P. B. Guerzoni, Carolina Itzin, Dirk Rommel, Matthias Mork, Céline Bastard, Bernhard Häßel, Abdolrahman Omidinia-Anarkoli, Silvia P. Centeno, et al.

Microgels are water-swollen, crosslinked polymers that are widely used as colloidal building blocks in scaffold materials for tissue engineering and regenerative medicine. Microgels can be controlled in their stiffness, degree of swelling, and mesh size depending on their polymer architecture, crosslink density, and fabrication method – all of which influence their function and interaction with the environment. Currently, there is a lack of understanding of how the polymer composition influences the internal structure of soft microgels and how this morphology affects specific biomedical applications. In this report, we systematically vary the architecture and molar mass of polyethylene glycol-acrylate (PEG-Ac) precursors, as well as their concentration and combination, to gain insight in the different parameters that affect the internal structure of rod-shaped microgels. We characterize the mechanical properties and diffusivity, as well as the conversion of acrylate groups during photopolymerization, in both bulk hydrogels and microgels produced from the PEG-Ac precursors. Furthermore, we investigate cell-microgel interaction, and we observe improved cell spreading on microgels with more accessible RGD peptide and with a stiffness in a range of 20 kPa to 50 kPa lead to better cell growth.

Dark solitons in Fabry-Pérot resonators with Kerr media and normal dispersion

Graeme, N. Campbell, Lewis Hill, Pascal Del'Haye, Gian-Luca Oppo

The ranges of existence and stability of dark cavity-soliton stationary states in a Fabry-Pérot resonator with a Kerr nonlinear medium and normal dispersion are determined. The Fabry-Pérot configuration introduces nonlocal coupling that shifts the cavity detuning by the round trip average power of the intracavity field. When compared with ring resonators described by the Lugiato-Lefever equation, nonlocal coupling leads to strongly detuned dark cavity solitons that exist over a wide range of detunings. This shift is a consequence of the counterpropagation of intracavity fields inherent to Fabry-Pérot resonators. In contrast with ring resonators, the existence and stability of dark soliton solutions are dependent on the size and number of solitons in the cavity. We investigate the effect of nonlocal coupling of Fabry-Pérot resonators on multiple dark solitons, and we demonstrate long-range interactions and synchronization of temporal oscillations.

Conserved nucleocytoplasmic density homeostasis drives cellular organization across eukaryotes

Abin Biswas, Omar Muñoz, Kyoohyun Kim, Carsten Hoege, Benjamin M. Lorton, David Shechter, Jochen Guck, Vasily Zaburdaev, Simone Reber

The packing and confinement of macromolecules in the cytoplasm and nucleoplasm has profound implications for cellular biochemistry. How intracellular density distributions vary and affect cellular physiology remains largely unknown. Here, we show that the nucleus is less dense than the cytoplasm and that living systems establish and maintain a constant density ratio between these compartments. Using label-free biophotonics and theory, we show that nuclear density is set by a pressure balance across the nuclear envelope in vitro, in vivo and during early development. Nuclear transport establishes a specific nuclear proteome that exerts a colloid osmotic pressure, which, assisted by entropic chromatin pressure, draws water into the nucleus. Using C. elegans, we show that while nuclear-to-cytoplasmic (N/C) volume ratios change during early development, the N/C density ratio is robustly maintained. We propose that the maintenance of a constant N/C density ratio is the biophysical driver of one of the oldest tenets of cell biology: the N/C volume ratio. In summary, this study reveals a previously unidentified homeostatic coupling of macromolecular densities that drives cellular organization with implications for pathophysiologies such as senescence and cancer.

RNA binding proteins and glycoRNAs form domains on the cell surface for cell penetrating peptide entry

Jonathan Perr, Andreas Langen, Karim Almahayni, Gianluca Nestola, Peiyuan Chai, Charlotta G. Lebedenko, Regan Volk, Reese M. Caldwell, Malte Spiekermann, et al.

The composition and organization of the cell surface determine how cells interact with their environment. Traditionally, glycosylated transmembrane proteins were thought to be the major constituents of the external surface of the plasma membrane. Here, we provide evidence that a group of RNA binding proteins (RBPs) are present on the surface of living cells. These cell surface RBPs (csRBPs) precisely organize into well-defined nanoclusters that are enriched for multiple RBPs, glycoRNAs, and their clustering can be disrupted by extracellular RNase addition. These glycoRNA-csRBP clusters further serve as sites of cell surface interaction for the cell penetrating peptide TAT. Removal of RNA from the cell surface, or loss of RNA binding activity by TAT, causes defects in TAT cell internalization. Together, we provide evidence of an expanded view of the cell surface by positioning glycoRNA-csRBP clusters as a regulator of communication between cells and the extracellular environment.

Periodic ethanol supply as a path toward unlimited lifespan of Caenorhabditis elegans dauer larvae

Xingyu Zhang, Sider Penkov, Teymuras V. Kurzchalia, Vasily Zaburdaev

The dauer larva is a specialized stage of worm development optimized for survival under harsh conditions that have been used as a model for stress resistance, metabolic adaptations, and longevity. Recent findings suggest that the dauer larva of Caenorhabditis elegans may utilize external ethanol as an energy source to extend their lifespan. It was shown that while ethanol may serve as an effectively infinite source of energy, some toxic compounds accumulating as byproducts of its metabolism may lead to the damage of mitochondria and thus limit the lifespan of larvae. A minimal mathematical model was proposed to explain the connection between the lifespan of a dauer larva and its ethanol metabolism. To explore theoretically if it is possible to extend even further the lifespan of dauer larvae, we incorporated two natural mechanisms describing the recovery of damaged mitochondria and elimination of toxic compounds, which were previously omitted in the model. Numerical simulations of the revised model suggested that while the ethanol concentration is constant, the lifespan still stays limited. However, if ethanol is supplied periodically, with a suitable frequency and amplitude, the dauer could survive as long as we observe the system. Analytical methods further help to explain how feeding frequency and amplitude affect lifespan extension. Based on the comparison of the model with experimental data for fixed ethanol concentration, we proposed the range of feeding protocols that could lead to even longer dauer survival and it can be tested experimentally.

Superresolution Enhancement in Biphoton Spatial-Mode Demultiplexing

Florence Grenapin, Dilip Paneru, Alessio D'Errico, Vincenzo Grillo, Gerd Leuchs, Ebrahim Karimi

Imaging systems measuring intensity in the far field succumb to Rayleigh's curse, a resolution limitation dictated by the finite aperture of the optical system. Many proof-of-principle and some two-dimensional imaging experiments have shown that, by using spatial mode demultiplexing (SPADE), the field information collected is maximal, and, thus, the resolution increases beyond the Rayleigh criterion. Hitherto, the SPADE approaches are based on resolving the lateral splitting of a Gaussian wave function. Here, we consider the case in which the light field originates from a biphoton source, i.e., spontaneous parametric down-conversion, and a horizontal separation is introduced in one of the two photons. We show that a separation induced in the signal photon arm can be superresolved using coincidence measurements after projecting both photons on Hermite-Gauss modes. Remarkably, the Fisher information associated with the measurement is enhanced compared to the ordinary SPADE techniques by root K, where K is the Schmidt number of the two-photon state that quantifies the amount of spatial entanglement between the two photons.

Cooling microwave fields into general multimode Gaussian states

Nahid Yazdi, Juan José García-Ripoll, Diego Porras, Carlos Navarrete-Benlloch

We show that a collection of lossy multi-chromatically modulated qubits can be used to dissipa- tively engineer arbitrary Gaussian states of a set of bosonic modes. Our ideas are especially suited to superconducting-circuit architectures, where all the required ingredients are experimentally avail- able. The generation of such multimode Gaussian states is necessary for many applications, most notably measurement-based quantum computation. We build upon some of our previous proposals, where we showed how to generate single-mode and two-mode squeezed states through cooling and lasing. Special care must be taken when extending these ideas to many bosonic modes, and we discuss here how to overcome all the limitations and hurdles that naturally appear. We illustrate our ideas with a fully worked out example consisting of GHZ states, but have also tested several other examples such as cluster states. All these examples allow us to show that it is possible to use a set of N lossy qubits to cool down a bosonic chain of N modes to any desired Gaussian state.

Roadmap on structured waves

Konstantin Y Bliokh, Ebrahim Karimi, Miles J Padgett, Miguel A Alonso, Mark R Dennis, Angela Dudley, Andrew Forbes, Sina Zahedpour, Scott W Hancock, et al.

Structured waves are ubiquitous for all areas of wave physics, both classical and quantum, where the wavefields are inhomogeneous and cannot be approximated by a single plane wave. Even the interference of two plane waves, or of a single inhomogeneous (evanescent) wave, provides a number of nontrivial phenomena and additional functionalities as compared to a single plane wave. Complex wavefields with inhomogeneities in the amplitude, phase, and polarization, including topological structures and singularities, underpin modern nanooptics and photonics, yet they are equally important, e.g. for quantum matter waves, acoustics, water waves, etc. Structured waves are crucial in optical and electron microscopy, wave propagation and scattering, imaging, communications, quantum optics, topological and non-Hermitian wave systems, quantum condensed-matter systems, optomechanics, plasmonics and metamaterials, optical and acoustic manipulation, and so forth. This Roadmap is written collectively by prominent researchers and aims to survey the role of structured waves in various areas of wave physics. Providing background, current research, and anticipating future developments, it will be of interest to a wide cross-disciplinary audience.

All-in-One Photoactivated Inhibition of Butyrylcholinesterase Combined with Luminescence as an Activation and Localization Indicator: Carbon Quantum Dots@Phosphonate Hybrids

Gulia Bikbaeva, Anna Pilip, Anastasia Egorova, Ilya Kolesnikov, Dmitrii Pankin, Kirill Laptinskiy, Alexey Vervald, Tatiana Dolenko, Gerd Leuchs, et al.

Photopharmacology is a booming research area requiring a new generation of agents possessing simultaneous functions of photoswitching and pharmacophore. It is important that any practical implementation of photopharmacology ideally requires spatial control of the medicinal treatment zone. Thus, advances in the study of substances meeting all the listed requirements will lead to breakthrough research in the coming years. In this study, CQDs@phosphonate nanohybrids are presented for the first time and combine biocompatible and nontoxic luminescent carbon quantum dots (CQDs) with photoactive phosphonate enabling inhibition of butyrylcholinesterase (BChE), which is a prognostic marker of numerous diseases. The conjunction of these components in hybrids maintains photoswitching and provides enhancement of BChE inhibition. After laser irradiation with a wavelength of 266 nm, CQDs@phosphonate hybrids demonstrate a drastic increase of butyrylcholinesterase inhibition from 38% up to almost 100% and a simultaneous luminescence decrease. All the listed hybrid properties are demonstrated not only for in vitro experiments but also for complex biological samples, i.e., chicken breast. Thus, the most important achievement is the demonstration of hybrids characterized by a remarkable combination of all-in-one properties important for photopharmacology: (i) bioactivity toward butyrylcholinesterase inhibition, (ii) strong change of inhibition degree as a result of laser irradiation, luminescence as an indicator of (iii) bioactivity state, and of (iv) spatial localization on the surface of a sample.

Classical phase synchronization in dissipative non-Hermitian coupled systems

Jonas Rohn, Kai Phillip Schmidt, Claudiu Genes

We study the interplay between non-Hermitian dynamics and classical phase synchronization in a system of N bosonic modes commonly coupled to an auxiliary, driven mode. For any set of non-Hermitian bipartite interactions between the auxiliary and other modes, the system evolves towards a phase synchronized state. We provide analytical and numerical evidence of such classical phase synchronization for systems ranging from a few modes to the macroscopic limit of large N and analyze the effects of inhomogeneous frequency broadening and robustness under the action of external thermal noise.

Label-free composition determination for biomolecular condensates with an arbitrarily large number of components

Patrick McCall, Kyoohyun Kim, Martine Ruer-Gruß, Jan Peychl, Jochen Guck, Anthony A. Hyman, Jan Brugués

Biomolecular condensates are membrane-less organelles made of multiple components, often including several distinct proteins and nucleic acids. However, current tools to measure condensate composition are limited and cannot capture this complexity quantitatively, as they either require fluorescent labels, which we show can perturb composition, or can distinguish only 1-2 components. Here, we describe a label-free method based on quantitative phase microscopy to measure the composition of condensates with an arbitrarily large number of components. We first validate the method empirically in binary mixtures, revealing sequence-encoded density variation and complex aging dynamics for condensates composed of full-length proteins. In simplified multi-component protein/RNA condensates, we uncover a regime of constant condensate density and a large range of protein:RNA stoichiometry when varying average composition. The unexpected decoupling of density and composition highlights the need to determine molecular stoichiometry in multi-component condensates. We foresee this approach enabling the study of compositional regulation of condensate properties and function.

Wigner function tomography via optical parametric amplification

Mahmoud Kalash, Maria V. Chekhova

Wigner function tomography is indispensable for characterizing quantum states, but its commonly used version, balanced homodyne detection, suffers from several weaknesses. First, it requires efficient detection, which is critical for measuring fragile non-Gaussian states, especially bright ones. Second, it needs a local oscillator, tailored to match the spatiotemporal properties of the state under test, and fails for multimode and broadband states. Here we propose Wigner function tomography based on optical parametric amplification followed by direct detection. The method is immune to detection inefficiency and loss, and suitable for broadband, spatially and temporally multimode quantum states. To prove the principle, we experimentally reconstruct the Wigner function of squeezed vacuum occupying a single mode of a strongly multimode state. We obtain a squeezing of −7.5±0.4dB and purity of 0.91(+0.09−0.08) despite more than 97% loss caused mainly by filtering. Theoretically, we also consider the reconstruction of a squeezed single photon—a bright non-Gaussian state. Due to multimode parametric amplification, the method allows for simultaneous tomography of multiple modes. This makes it a powerful tool for optical quantum information processing.

Sensing Rotations with Multiplane Light Conversion

M. Eriksson, A. Z. Goldberg, M. Hiekkamaki, F. Bouchard, J. Rehacek, Z. Hradil, Gerd Leuchs, R. Fickler, Luis Sanchez-Soto

We report an experiment estimating the three parameters of a general rotation. The scheme uses quantum states attaining the ultimate precision dictated by the quantum Cramer-Rao bound. We realize the states experimentally using the orbital angular momentum of light and implement the rotations with a multiplane light-conversion setup, which allows one to perform arbitrary unitary transformations on a finite set of spatial modes. The observed performance suggests a range of potential applications in the next generation of rotation sensors.

Self-learning Machines based on Hamiltonian Echo Backpropagation

Victor Lopez-Pastor, Florian Marquardt

A physical self-learning machine can be defined as a nonlinear dynamical system that can be trained on data (similar to artificial neural networks), but where the update of the internal degrees of freedom that serve as learnable parameters happens autonomously. In this way, neither external processing and feedback nor knowledge of (and control of) these internal degrees of freedom is required. We introduce a general scheme for self-learning in any time-reversible Hamiltonian system. We illustrate the training of such a self-learning machine numerically for the case of coupled nonlinear wave fields.

Human T cells loaded with superparamagnetic iron oxide nanoparticles retain antigen-specific TCR functionality

Felix Pfister, Jan Dörrie, Niels Schaft, Vera Buchele, Harald Unterweger, Lucas R. Carnell, Patrick Schreier, Rene Stein, Markéta Kubánková, et al.

BACKGROUND: Immunotherapy of cancer is an emerging field with the potential to improve long-term survival. Thus far, adoptive transfer of tumor-specific T cells represents an effective treatment option for tumors of the hematological system such as lymphoma, leukemia or myeloma. However, in solid tumors, treatment efficacy is low owing to the immunosuppressive microenvironment, on-target/off-tumor toxicity, limited extravasation out of the blood vessel, or ineffective trafficking of T cells into the tumor region. Superparamagnetic iron oxide nanoparticles (SPIONs) can make cells magnetically controllable for the site-specific enrichment. METHODS: In this study, we investigated the influence of SPION-loading on primary human T cells for the magnetically targeted adoptive T cell therapy. For this, we analyzed cellular mechanics and the T cell response after stimulation via an exogenous T cell receptor (TCR) specific for the melanoma antigen MelanA or the endogenous TCR specific for the cytomegalovirus antigen pp65 and compared them to T cells that had not received SPIONs. RESULTS: SPION-loading of human T cells showed no influence on cellular mechanics, therefore retaining their ability to deform to external pressure. Additionally, SPION-loading did not impair the T cell proliferation, expression of activation markers, cytokine secretion, and tumor cell killing after antigen-specific activation mediated by the TCR. CONCLUSION: In summary, we demonstrated that SPION-loading of T cells did not affect cellular mechanics or the functionality of the endogenous or an exogenous TCR, which allows future approaches using SPIONs for the magnetically enrichment of T cells in solid tumors.

Amphiphiles Formed from Synthetic DNA-Nanomotifs Mimic the Stepwise Dispersal of Transcriptional Clusters in the Cell Nucleus

Xenia Tschurikow, Aaron Gadzekpo, Mai P. Tran, Rakesh Chatterjee, Marcel Sobucki, Vasily Zaburdaev, Kerstin Göpfrich, Lennart Hilbert

Stem cells exhibit prominent clusters controlling the transcription of genes into RNA. These clusters form by a phase-separation mechanism, and their size and shape are controlled via an amphiphilic effect of transcribed genes. Here, we construct amphiphile-nanomotifs purely from DNA, and we achieve similar size and shape control for phase-separated droplets formed from fully synthetic, self-interacting DNA-nanomotifs. Increasing amphiphile concentrations induce rounding of droplets, prevent droplet fusion, and, at high concentrations, cause full dispersal of droplets. Super-resolution microscopy data obtained from zebrafish embryo stem cells reveal a comparable transition for transcriptional clusters with increasing transcription levels. Brownian dynamics and lattice simulations further confirm that the addition of amphiphilic particles is sufficient to explain the observed changes in shape and size. Our work reproduces key aspects of transcriptional cluster formation in biological cells using relatively simple DNA sequence-programmable nanostructures, opening novel ways to control the mesoscopic organization of synthetic nanomaterials.

Highly Nonlinear Dynamics of In Vivo Deep-Tissue Interaction with Femtosecond Laser Pulses at 1030 nm

Soyeon Jun, Andreas Herbst, Kilian Scheffter, Nora John, Julia Kolb, Daniel Wehner, Hanieh Fattahi

We report on the highly nonlinear behavior observed in the central nervous system tissue of zebrafish (Danio rerio) when exposed to femtosecond pulses at 1030 nm. At this irradiation wavelength, photo damage becomes detectable only after exceeding a specific peak intensity threshold, which is independent of the photon flux and irradiation time, distinguishing it from irradiation at shorter wavelengths. Furthermore, we investigate and quantify the role of excessive heat in reducing the damage threshold, particularly during high-repetition-rate operations, which are desirable for label-free and multi-dimensional microscopy techniques. To verify our findings, we examined cellular responses to tissue damage, including apoptosis and the recruitment of macrophages and fibroblasts at different time points post-irradiation. These findings substantially contribute to advancing the emerging nonlinear optical microscopy techniques and provide a strategy for inducing deep-tissue, precise and localized injuries using near-infrared femtosecond laser pulses.

Brain tissue mechanics is governed by microscale relations of the tissue constituents

P. Sáez, C. Borau, N. Antonovaite, Kristian Franze

Local mechanical tissue properties are a critical regulator of cell function in the central nervous system (CNS) during development and disorder. However, we still don't fully understand how the mechanical properties of individual tissue constituents, such as cell nuclei or myelin, determine tissue mechanics. Here we developed a model predicting local tissue mechanics, which induces non-affine deformations of the tissue components. Using the mouse hippocampus and cerebellum as model systems, we show that considering individual tissue components alone, as identified by immunohistochemistry, is not sufficient to reproduce the local mechanical properties of CNS tissue. Our results suggest that brain tissue shows a universal response to applied forces that depends not only on the amount and stiffness of the individual tissue constituents but also on the way how they assemble. Our model may unify current incongruences between the mechanics of soft biological tissues and the underlying constituents and facilitate the design of better biomedical materials and engineered tissues. To this end, we provide a freely-available platform to predict local tissue elasticity upon providing immunohistochemistry images and stiffness values for the constituents of the tissue.

Multi-stage spontaneous symmetry breaking of light in Kerr ring resonators

Lewis Hill, Gian-Luca Oppo, Pascal Del'Haye

Symmetry breaking of light states is of interest for the understanding of nonlinear optics, photonic circuits, telecom applications and optical pulse generation. Here we demonstrate multi-stage symmetry breaking of the resonances of ring resonators with Kerr nonlinearity. This multi-stage symmetry breaking naturally occurs in a resonator with bidirectionally propagating light with orthogonal polarization components. The derived model used to theoretically describe the system shows that the four circulating field components can display full symmetry, full asymmetry, and multiple versions of partial symmetry, and are later shown to result in complex oscillatory dynamics - such as four-field self-switching, and unusual pulsing with extended delays between subsequent peaks. To highlight a few examples, our work has application in the development of photonic devices like isolators and circulators, logic gates, and random numbers generators, and could also be used for optical-sensors, e.g. by further enhancing the Sagnac effect.

IL-3 receptor signalling suppresses chronic intestinal inflammation by controlling mechanobiology and tissue egress of regulatory T cells

Karen Anne-Marie Ullrich, Julia Derdau, Carsten Baltes, Alice Battistella, Gonzalo Rosso, Stefan Uderhardt, Lisa Lou Schulze, Li-Juan Liu, Mark Dedden, et al.

IL-3 has been reported to be involved in various inflammatory disorders, but its role in inflammatory bowel disease (IBD) has not been addressed so far. Here, we determined IL-3 expression in samples from patients with IBD and studied the impact of Il3 or Il3r deficiency on T cell-dependent experimental colitis. We explored the mechanical, cytoskeletal and migratory properties of Il3r −/− and Il3r +/+ T cells using real-time deformability cytometry, atomic force microscopy, scanning electron microscopy, fluorescence recovery after photobleaching and in vitro and in vivo cell trafficking assays. We observed that, in patients with IBD, the levels of IL-3 in the inflamed mucosa were increased. In vivo, experimental chronic colitis on T cell transfer was exacerbated in the absence of Il-3 or Il-3r signalling. This was attributable to Il-3r signalling-induced changes in kinase phosphorylation and actin cytoskeleton structure, resulting in increased mechanical deformability and enhanced egress of Tregs from the inflamed colon mucosa. Similarly, IL-3 controlled mechanobiology in human Tregs and was associated with increased mucosal Treg abundance in patients with IBD. Collectively, our data reveal that IL-3 signaling exerts an important regulatory role at the interface of biophysical and migratory T cell features in intestinal inflammation and suggest that this might be an interesting target for future intervention.

Collectively Enhanced Giant Circular Dichroism of Germanium Nanohelix Square Lattice Arrays

Günter Ellrott, Paul Beck, Vitaliy Sultanov, Sergej Rothau, Norbert Lindlein, Maria Chekhova, Vojislav Kristic

Circular dichroism is a unique chiroptical signature of the chirality of a system and is a prevalent way to characterize and distinguish systems on a fundamental level and for their technological applicability. Thus, engineering and maximizing the chiroptical response of a single chiral object or a metasurface composed of chiral entities is a formidable task. Current efforts strongly focus on individual metallic nanostructures and their periodic ensembles to harvest on (resonant) plasmonic properties and interactions. This route, however, waives the advantages of high-refractive-index nanoscale materials embracing low dissipative losses at optical wavelengths and electromagnetic fields penetrating and propagating in such materials. Herein, a strong circular dichroism is demonstrated in square lattices of nanohelices made of the high-refractive-index semiconductor germanium, with dissymmetry factors outperforming metal-based ensembles. The observation of a much higher dissymmetry emerges for illumination with spatially coherent light, in comparison to spatially incoherent light. High dissymmetry is attributed to cooperative coupling between single helices, resulting from the combination of dielectric resonances of both the individual helical building blocks and the highly ordered lattice.

Label-free discrimination of extracellular vesicles from large lipoproteins

Anna D. Kashkanova, Martin Blessing, Marie Reischke, Jan-Ole Baur, Andreas S. Baur, Vahid Sandoghdar, Jan Van Deun

Extracellular vesicles (EVs) are increasingly gaining interest as biomarkers and therapeutics. Accurate sizing and quantification of EVs remain problematic, given their nanometre size range and small scattering cross-sections. This is compounded by the fact that common EV isolation methods result in co-isolation of particles with comparable features. Especially in blood plasma, similarly-sized lipoproteins outnumber EVs to a great extent. Recently, interferometric nanoparticle tracking analysis (iNTA) was introduced as a particle analysis method that enables determining the size and refractive index of nanoparticles with high sensitivity and precision. In this work, we apply iNTA to differentiate between EVs and lipoproteins, and compare its performance to conventional nanoparticle tracking analysis (NTA). We show that iNTA can accurately quantify EVs in artificial EV-lipoprotein mixtures and in plasma-derived EV samples of varying complexity. Conventional NTA could not report on EV numbers, as it was not able to distinguish EVs from lipoproteins. iNTA has the potential to become a new standard for label-free EV characterization in suspension.

Revolutionizing microfluidics with artificial intelligence: a new dawn for lab-on-a-chip technologies

Keisuke Goda, Hang Lu, Peng Fei, Jochen Guck

Time-domain Compressed Sensing

Kilian Scheffter, Jonathan Will, Caudius Riek, Herve Jousselin, Sébastien Coudreau, Nicolas Forget, Hanieh Fattahi

Ultrashort time-domain spectroscopy, particularly field-resolved spectroscopy, are established methods for identifying the constituents and internal dynamics of samples. However, these techniques are often encumbered by the Nyquist criterion, leading to prolonged data acquisition and processing times as well as sizable data volumes. To mitigate these issues, we have successfully implemented the first instance of time-domain compressed sensing, enabling us to pinpoint the primary absorption peaks of atmospheric water vapor in response to tera-hertz light transients that exceed the Nyquist limit. Our method demonstrates successful identification of water absorption peaks up to 2.5 THz, even for sampling rates where the Nyquist frequency is as low as 0.75 THz, with a mean squared error of 12*10-4. Time-domain sparse sampling achieves considerable data compression while also expediting both the measurement and data processing time, representing a significant stride towards the realm of real-time spectroscopy

Gradient Ascent Pulse Engineering with Feedback

Riccardo Porotti, Vittorio Peano, Florian Marquardt

Efficient approaches to quantum control and feedback are essential for quantum technologies, from sensing to quantum computation. Open-loop control tasks have been successfully solved using optimization techniques, including methods such as gradient-ascent pulse engineering (GRAPE) , relying on a differentiable model of the quantum dynamics. For feedback tasks, such methods are not directly applicable, since the aim is to discover strategies conditioned on measurement outcomes. In this work, we introduce feedback GRAPE, which borrows some concepts from model-free reinforcement learning to incorporate the response to strong stochastic (discrete or continuous) measurements, while still performing direct gradient ascent through the quantum dynamics. We illustrate its power considering various scenarios based on cavity-QED setups. Our method yields interpretable feedback strategies for state preparation and stabilization in the presence of noise. Our approach could be employed for discovering strategies in a wide range of feedback tasks, from calibration of multiqubit devices to linear-optics quantum computation strategies, quantum enhanced sensing with adaptive measurements, and quantum error correction.

Quadrature nonreciprocity in bosonic networks without breaking time-reversal symmetry

Clara C. Wanjura, Jesse J. Slim, Javier del Pino, Matteo Brunelli, Ewold Verhagen, Andreas Nunnenkamp

Nonreciprocity means that the transmission of a signal depends on its direction of propagation. Despite vastly different platforms and underlying working principles, the realizations of nonreciprocal transport in linear, time-independent systems rely on Aharonov–Bohm interference among several pathways and require breaking time-reversal symmetry. Here we extend the notion of nonreciprocity to unidirectional bosonic transport in systems with a time-reversal symmetric Hamiltonian by exploiting interference between beamsplitter (excitation-preserving) and two-mode-squeezing (excitation non-preserving) interactions. In contrast to standard nonreciprocity, this unidirectional transport manifests when the mode quadratures are resolved with respect to an external reference phase. Accordingly, we dub this phenomenon ‘quadrature nonreciprocity’. We experimentally demonstrate it in the minimal system of two coupled nanomechanical modes orchestrated by optomechanical interactions. Next, we develop a theoretical framework to characterize the class of networks exhibiting quadrature nonreciprocity based on features of their particle–hole graphs. In addition to unidirectionality, these networks can exhibit an even–odd pairing between collective quadratures, which we confirm experimentally in a four-mode system, and an exponential end-to-end gain in the case of arrays of cavities.

De novo identification of universal cell mechanics gene signatures

Marta Urbanska, Yan Ge, Maria Winzi, Shada Abuhattum Hofemeier, Syed Shafat Ali, Maik Herbig, Martin Kräter, Nicole Toepfner, Joanna Durgan, et al.

Cell mechanical properties determine many physiological functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors that govern the mechanical properties is therefore a subject of great interest. Here we present a mechanomics approach for establishing links between single-cell mechanical phenotype changes and the genes involved in driving them. We combine mechanical characterization of cells across a variety of mouse and human systems with machine learning-based discriminative network analysis of associated transcriptomic profiles to infer a conserved network module of five genes with putative roles in cell mechanics regulation. We validate in silico that the identified gene markers are universal, trustworthy and specific to the mechanical phenotype, and demonstrate experimentally that a selected target, CAV1, changes the mechanical phenotype of cells accordingly when silenced or overexpressed. Our data-driven approach paves the way towards engineering cell mechanical properties on demand to explore their impact on physiological and pathological cell functions.

Plakoglobin is a mechanoresponsive regulator of naive pluripotency

Timo N. Kohler, Joachim De Jonghe, Anna L. Ellermann, Ayaka Yanagida, Michael Herger, Erin M. Slatery, Antonia Weberling, Clara Munger, Katrin Fischer, et al.

Biomechanical cues are instrumental in guiding embryonic development and cell differentiation. Understanding how these physical stimuli translate into transcriptional programs will provide insight into mechanisms underlying mammalian pre-implantation development. Here, we explore this type of regulation by exerting microenvironmental control over mouse embryonic stem cells. Microfluidic encapsulation of mouse embryonic stem cells in agarose microgels stabilizes the naive pluripotency network and specifically induces expression of Plakoglobin (Jup), a vertebrate homolog of β-catenin. Overexpression of Plakoglobin is sufficient to fully re-establish the naive pluripotency gene regulatory network under metastable pluripotency conditions, as confirmed by single-cell transcriptome profiling. Finally, we find that, in the epiblast, Plakoglobin was exclusively expressed at the blastocyst stage in human and mouse embryos - further strengthening the link between Plakoglobin and naive pluripotency in vivo. Our work reveals Plakoglobin as a mechanosensitive regulator of naive pluripotency and provides a paradigm to interrogate the effects of volumetric confinement on cell-fate transitions.

Topological phase diagrams of exactly solvable non-Hermitian interacting Kitaev chains

Sharareh Sayyad, Jose L. Lado

Many-body interactions give rise to the appearance of exotic phases in Hermitian physics. Despite their importance, many-body effects remain an open problem in non-Hermitian physics due to the complexity of treating many-body interactions. Here, we present a family of exact and numerical phase diagrams for non-Hermitian interacting Kitaev chains. In particular, we establish the exact phase boundaries for the dimerized Kitaev-Hubbard chain with complex-valued Hubbard interactions. Our results reveal that some of the Hermitian phases disappear as non-Hermiticity is enhanced. Based on our analytical findings, we explore the regime of the model that goes beyond the solvable regime, revealing regimes where non-Hermitian topological degeneracy remains. The combination of our exact and numerical phase diagrams provides an extensive description of a family of non-Hermitian interacting models. Our results provide a stepping stone toward characterizing non-Hermitian topology in realistic interacting quantum many-body systems.<br><br>

Recent advances in the Self-Referencing Embedding Strings (SELFIES) library

Alston Lo, Robert Pollice, AkshatKumar Nigam, Andrew D. White, Mario Krenn, Alán Aspuru-Guzik

String-based molecular representations play a crucial role in cheminformatics applications, and with the growing success of deep learning in chemistry, have been readily adopted into machine learning pipelines. However, traditional string-based representations such as SMILES are often prone to syntactic and semantic errors when produced by generative models. To address these problems, a novel representation, SELF-referencing embedded strings (SELFIES), was proposed that is inherently 100% robust, alongside an accompanying open-source implementation called selfies. Since then, we have generalized SELFIES to support a wider range of molecules and semantic constraints, and streamlined its underlying grammar. We have implemented this updated representation in subsequent versions of selfies, where we have also made major advances with respect to design, efficiency, and supported features. Hence, we present the current status of selfies (version 2.1.1) in this manuscript. Our library, selfies, is available at GitHub (https://github.com/aspuru-guzik-group/selfies).<br>

Constriction imposed by basement membrane regulates developmental cell migration

Ester Molina López, Anna Kabanova, Alexander Winkel, Kristian Franze, Isabel M. Palacios, María D. Martín-Bermudo

The basement membrane (BM) is a specialized extracellular matrix (ECM), which underlies or encases developing tissues. Mechanical properties of encasing BMs have been shown to profoundly influence the shaping of associated tissues. Here, we use the migration of the border cells (BCs) of the Drosophila egg chamber to unravel a new role of encasing BMs in cell migration. BCs move between a group of cells, the nurse cells (NCs), that are enclosed by a monolayer of follicle cells (FCs), which is, in turn, surrounded by a BM, the follicle BM. We show that increasing or reducing the stiffness of the follicle BM, by altering laminins or type IV collagen levels, conversely affects BC migration speed and alters migration mode and dynamics. Follicle BM stiffness also controls pairwise NC and FC cortical tension. We propose that constraints imposed by the follicle BM influence NC and FC cortical tension, which, in turn, regulate BC migration. Encasing BMs emerge as key players in the regulation of collective cell migration during morphogenesis.

Quasiclassical approach to the nonlinear Kerr dynamics

Mojdeh S. Najafabadi, Andrei B. Klimov, Luis Sanchez-Soto, Gerd Leuchs

We examine the quasiclassical approximation to the self-Kerr nonlinear effect. The corresponding dynamics appears as classical trajectories, with the quantumness of the state included via its Wigner function. We obtain analytical estimates of the optimal squeezing attainable that compare fairly well with the numerical quantum solution. We delimit the range of parameters for which the quasiclassical solution retains relevant quantum features.<br><br>

Alcohol-sourced acetate impairs T cell function by promoting cortactin acetylation

Vugar Azizov, Michael Hübner, Michael Frech, Jörg Hofmann, Markéta Kubánková, Dennis Lapuente, Matthias Tenbusch, Jochen Guck, Georg Schett, et al.

Alcohol is among the most widely consumed dietary substances. Excessive alcohol consumption damages the liver, heart, and brain. Alcohol also has strong immunoregulatory properties. Here, we report how alcohol impairs T cell function via acetylation of cortactin, a protein that binds filamentous actin and facilitates branching. Upon alcohol consumption, acetate, the metabolite of alcohol, accumulates in lymphoid organs. T cells exposed to acetate, exhibit increased acetylation of cortactin. Acetylation of cortactin inhibits filamentous actin binding and hence reduces T cell migration, immune synapse formation and activation. While mutated, acetylation-resistant cortactin rescues the acetate-induced inhibition of T cell migration, primary mouse cortactin knockout T cells exhibited impaired migration. Acetate-induced cytoskeletal changes effectively inhibited activation, proliferation, and immune synapse formation in T cells in vitro and in vivo in an influenza infection model in mice. Together these findings reveal cortactin as a possible target for mitigation of T cell driven autoimmune diseases.

Low-Volume Reaction Monitoring of Carbon Dot Light Absorbers in Optofluidic Microreactors

Takashi Lawson, Alexander S. Gentleman , Ava Lage, Carla Casadevall, Jie Xiao, Tristan Petit, Michael Frosz, Erwin Reisner, Tijmen G. Euser

Optical monitoring and screening of photocatalytic batch reactions using cuvettes ex situ is time-consuming, requires substantial amounts of samples, and does not allow the analysis of species with low extinction coefficients. Hollow-core photonic crystal fibers (HC-PCFs) provide an innovative approach for in situ reaction detection using ultraviolet–visible absorption spectroscopy, with the potential for high-throughput automation using extremely low sample volumes with high sensitivity for monitoring of the analyte. HC-PCFs use interference effects to guide light at the center of a microfluidic channel and use this to enhance detection sensitivity. They open the possibility of comprehensively studying photocatalysts to extract structure–activity relationships, which is unfeasible with similar reaction volume, time, and sensitivity in cuvettes. Here, we demonstrate the use of HC-PCF microreactors for the screening of the electron transfer properties of carbon dots (CDs), a nanometer-sized material that is emerging as a homogeneous light absorber in photocatalysis. The CD-driven photoreduction reaction of viologens (XV2+) to the corresponding radical monocation XV•+ is monitored in situ as a model reaction, using a sample volume of 1 μL per measurement and with a detectability of <1 μM. A range of different reaction conditions have been systematically studied, including different types of CDs (i.e., amorphous, graphitic, and graphitic nitrogen-doped CDs), surface chemistry, viologens, and electron donors. Furthermore, the excitation irradiance was varied to study its effect on the photoreduction rate. The findings are correlated with the electron transfer properties of CDs based on their electronic structure characterized by soft X-ray absorption spectroscopy. Optofluidic microreactors with real-time optical detection provide unique insight into the reaction dynamics of photocatalytic systems and could form the basis of future automated catalyst screening platforms, where samples are only available on small scales or at a high cost.

Fiber-Optical Sources of Quantum Squeezed Light

A. V. Andrianov, Nikolay Kalinin, A. A. Sorokin, E. A. Anashkina, Gerd Leuchs

Quantum squeezed states of light characterized by a reduced quantum uncertainty with respect to one of the quadrature variables smaller than the uncertainty of the vacuum state (the standard quantum limit) play an important role in the current fundamental and applied research. The main information concerning the proprieties and manifestations of the squeezed states are presented. A concise review of the methods for obtaining and detecting the quantum squeezed light is performed; at that, a special attention is payed to fiber-optical schemas. The Kerr mechanism of squeezed state generation that is realized in various variants of fiber-optic systems is considered in detail. An experimental scheme of generation of polarization-squeezed states based on a nonlinear polarization-maintaining fiber is presented. Different factors that limit squeezing are considered.

Spin-orbit interaction in nanofiber-based Brillouin scattering

Maxime Zerbib, Maxime Romanet, Thibaut Sylvestre, Christian Wolff, Birgit Stiller, Jean-Charles Beugnot, Kien Phan Huy

Angular momentum is an important physical property that plays a key role in light-matter interactions such as spin-orbit interaction. Here, we investigate theoretically and experimentally the spin-orbit interaction between a circularly polarized optical (spin) and a transverse vortex acoustic wave (orbital) using Brillouin backscattering in a silica optical nanofiber. We specifically explore the state of polarization of Brillouin backscattering induced by the TR21 torso-radial vortex acoustic mode that carries an orbital angular momentum. Using a full-vectorial theoretical model, we predict and observe two operating regimes for which the backscattered Brillouin signal is either depolarized or circularly polarized depending on the input pump polarization. We demonstrate that when the pump is circularly polarized and thus carries a spin angular momentum, the backscattered signal undergoes a handedness reversal of circular polarization due to optoacoustic spin-orbit interaction and the conservation of overall angular momentum.

Tunable fiber source of entangled UV-C and infrared photons

Santiago López-Huidrobro, Noureddin Mohammad, Maria V. Chekhova, Nicolas Y. Joly

Pairs of entangled photons—biphotons—are indispensable in quantum applications. However, some important spectral ranges, like the ultraviolet, have been inaccessible to them so far. Here, we use four-wave mixing in a xenon-filled single-ring photonic crystal fiber to generate biphotons with one of the photons in the ultraviolet and its entangled partner in the infrared spectral range. We tune the biphotons in frequency by varying the gas pressure inside the fiber and thus tailoring the fiber dispersion landscape. The ultraviolet photons are tunable from 271 nm to 231 nm and their entangled partners, from 764 nm to 1500 nm, respectively. Tunability up to 192 THz is achieved by adjusting the gas pressure by only 0.68 bar. At 1.43 bar, the photons of a pair are separated by more than 2 octaves. The access to ultraviolet wavelengths opens the possibility for spectroscopy and sensing with undetected photons in this spectral range.

Deep recurrent networks predicting the gap evolution in adiabatic quantum computing

Naeimeh Mohseni, Carlos Navarrete-Benlloch, Tim Byrnes, Florian Marquardt

One of the main challenges in quantum physics is predicting efficiently the dynamics of observables in many-body problems out of equilibrium. A particular example occurs in adiabatic quantum computing, where finding the structure of the instantaneous gap of the Hamiltonian is crucial in order to optimize the speed of the computation. Inspired by this challenge, in this work we explore the potential of deep learning for discovering a mapping from the parameters that fully identify a problem Hamiltonian to the full evolution of the gap during an adiabatic sweep applying different network architectures. Through this example, we find that a limiting factor for the learnability of the dynamics is the size of the input, that is, how the number of parameters needed to identify the Hamiltonian scales with the system size. We demonstrate that a long short-term memory network succeeds in predicting the gap when the parameter space scales linearly with system size. Remarkably, we show that once this architecture is combined with a convolutional neural network to deal with the spatial structure of the model, the gap evolution can even be predicted for system sizes larger than the ones seen by the neural network during training. This provides a significant speedup in comparison with the existing exact and approximate algorithms in calculating the gap.

Classical Phase Space Crystals in Open Environment

Ali Emami Kopaei, Krzysztof Sacha, Lingzhen Guo

It was recently discovered that a crystalline many-body state can exist in the phase space of a closed dynamical system. A phase space crystal can be an anomalous Chern insulator that supports chiral topological transport without breaking physical time-reversal symmetry [L. Guo et al., Phys. Rev. B 105, 094301 (2022)]. In this work, we further study the effects of an open dissipative environment with thermal noise and identify the existence condition of classical phase space crystals in realistic scenarios. By defining a crystal order parameter, we plot the phase diagram in the parameter space of dissipation rate, interaction, and temperature. Our present work paves the way to realize phase space crystals and explore anomalous chiral transport in experiments.

Organic Molecules as Origin of Visible-Range Single Photon Emission from Hexagonal Boron Nitride and Mica

Michael Neumann, Xu Wei, Luis Morales-Inostroza, Seunghyun Song, Sung-Gyu Lee, Kenji Watanabe, Takashi Taniguchi, Stephan Götzinger, Young Hee Lee

The discovery of room-temperature single-photon emitters (SPEs) hosted by two-dimensional hexagonal boron nitride (2D hBN) has sparked intense research interest. Although emitters in the vicinity of 2 eV have been studied extensively, their microscopic identity has remained elusive. The discussion of this class of SPEs has centered on point defects in the hBN crystal lattice, but none of the candidate defect structures have been able to capture the great heterogeneity in emitter properties that is observed experimentally. Employing a widely used sample preparation protocol but disentangling several confounding factors, we demonstrate conclusively that heterogeneous single-photon emission at ∼2 eV associated with hBN originates from organic molecules, presumably aromatic fluorophores. The appearance of those SPEs depends critically on the presence of organic processing residues during sample preparation, and emitters formed during heat treatment are not located within the hBN crystal as previously thought, but at the hBN/substrate interface. We further demonstrate that the same class of SPEs can be observed in a different 2D insulator, fluorophlogopite mica.

Quantum Efficiency of Single Dibenzoterrylene Molecules in p-Dichlorobenzene at Cryogenic Temperatures

Mohammad Musavinezhad, Alexey Shkarin, Dominik Rattenbacher, Jan Renger, Tobias Utikal, Stephan Götzinger, Vahid Sandoghdar

We measure the quantum efficiency (QE) of individual dibenzoterrylene (DBT) molecules embedded in p-dichlorobenzene at cryogenic temperatures. To achieve this, we combine two distinct methods based on the maximal photon emission and on the power required to saturate the zero-phonon line to compensate for uncertainties in some key system parameters. We find that the outcomes of the two approaches are in good agreement for reasonable values of the parameters involved, reporting a large fraction of molecules with QE values above 50%, with some exceeding 70%. Furthermore, we observe no correlation between the observed lower bound on the QE and the lifetime of the molecule, suggesting that most of the molecules have a QE exceeding the established lower bound. This confirms the suitability of DBT for quantum optics experiments. In light of previous reports of low QE values at ambient conditions, our results hint at the possibility of a strong temperature dependence of the QE.

Theory of phase-adaptive parametric cooling

Alekhya Ghosh, Pardeep Kumar, Christian Sommer, Fidel G. Jimenez, Vivishek Sudhir, Claudiu Genes

We propose an adaptive phase technique for the parametric cooling of mechanical oscillators. Our scheme calls for a sequence of periodic adjustments of the phase of a parametric modulation of the mechanical oscillator that is conditioned on measurements of its two quadratures. The technique indicates an exponential loss of thermal energy at initial high occupancies, similar in performance to other optomechanical techniques such as cold-damping or cavity self-cooling. As the quantum ground state is approached, the phase adaptive scheme leads to residual occupancies at the level of a few phonons owing to the competition between parametric amplification of quantum fluctuations and the feedback action.

Protecting Quantum Modes in Optical Fibers

Muhammad Abdullah Butt, Paul Roth, Gordon Wong, Michael Frosz, Luis Sanchez-Soto, E. A. Anashkina, A. V. Andrianov, Peter Banzer, Philip Russell, et al.

Polarization-preserving fibers maintain the two polarization states of an orthogonal basis. Quantum communication, however, requires sending at least two nonorthogonal states and these cannot both be preserved. We present an alternative scheme that allows for using polarization encoding in a fiber not only in the discrete, but also in the continuous-variable regime. For the example of a helically twisted photonic crystal fiber, we experimentally demonstrate that using appropriate nonorthogonal modes, the polarization-preserving fiber does not fully scramble these modes over the full Poincaré sphere, but that the output polarization will stay on a great circle; that is, within a one-dimensional protected subspace, which can be parametrized by a single variable. This allows for more efficient measurements of quantum excitations in nonorthogonal modes.

Single-pulse terahertz spectroscopy monitoring sub-millisecond time dynamics at a rate of 50 kHz

Nicolas Couture, Wei Cui, Markus Lippl, Rachel Ostic, Defi Junior Jubgang Fandio, Eeswar Kumar Yalavarthi, Aswin Vishnuradhan, Angela Gamouras, Nicolas Y. Joly, et al.

Slow motion movies allow us to see intricate details of the mechanical dynamics of complex phenomena. If the images in each frame are replaced by terahertz (THz) waves, such movies can monitor low-energy resonances and reveal fast structural or chemical transitions. Here, we combine THz spectroscopy as a non-invasive optical probe with a real-time monitoring technique to demonstrate the ability to resolve non-reproducible phenomena at 50k frames per second, extracting each of the generated THz waveforms every 20 μs. The concept, based on a photonic time-stretch technique to achieve unprecedented data acquisition speeds, is demonstrated by monitoring sub-millisecond dynamics of hot carriers injected in silicon by successive resonant pulses as a saturation density is established. Our experimental configuration will play a crucial role in revealing fast irreversible physical and chemical processes at THz frequencies with microsecond resolution to enable new applications in fundamental research as well as in industry.<br><br>

Quintic Dispersion Soliton Frequency Combs in a Microresonator

Shuangyou Zhang, Toby Bi, Pascal Del'Haye

Chip-scale optical frequency combs have attracted significant research interest and can be used in applications ranging from precision spectroscopy to telecom channel generators and lidar systems. In the time domain, microresonator based frequency combs correspond to self-stabilized soliton pulses. In two distinct regimes, microresonators are shown to emit either bright solitons in the anomalous dispersion regime or dark solitons (a short time of darkness in a bright background signal) in the normal dispersion regime. Here, the dynamics of continuous-wave-laser-driven soliton generation is investigated in the zero-group-velocity-dispersion regime as well as the generation of solitons that are spectrally crossing different dispersion regimes. In the measurements, zero-dispersion solitons with multipeak structures (soliton molecules) are observed with distinct and predictable spectral envelopes that are a result of fifth-order dispersion of the resonators. Numerical simulations and the analysis of bifurcation structures agree well with the observed soliton states. This is the first observation of soliton generation that is governed by fifth-order dispersion, which can have applications in ultrafast optics, telecom systems, and optical spectroscopy.

Simple, Economic, and Robust Rail-Based Setup for Super-Resolution Localization Microscopy

Karim Almahayni, Gianluca Nestola, Malte Spiekermann, Leonhard Möckl

Research during the past 2 decades has showcased the power of single-molecule localization microscopy (SMLM) as a tool for exploring the nanoworld. However, SMLM systems are typically available in specialized laboratories and imaging facilities, owing to their expensiveness as well as complex assembly and alignment procedure. Here, we lay out the blueprint of a sturdy, rail-based, cost-efficient, multicolor SMLM setup that is easy to construct and align in service of simplifying the accessibility of SMLM. We characterize the optical properties of the design and assess its capabilities, robustness, and stability. The performance of the system is assayed using super-resolution imaging of biological samples. We believe that this design will make SMLM more affordable and broaden its availability.<br>

Nonlinear Interferometry for Quantum-Enhanced Measurements of Multiphoton Absorption

Shahram Panahiyan, Carlos Sánchez Muñoz, Maria V. Chekhova, Frank Schlawin

Multiphoton absorption is of vital importance in many spectroscopic, microscopic, or lithographic applications. However, given that it is an inherently weak process, the detection of multiphoton absorption signals typically requires large field intensities, hindering its applicability in many practical situations. In this Letter, we show that placing a multiphoton absorbent inside an imbalanced nonlinear interferometer can enhance the precision of multiphoton cross section estimation with respect to strategies based on photon-number measurements using coherent or even squeezed light directly transmitted through the medium. In particular, the power scaling of the sensitivity with photon flux can be increased by 1 order compared with transmission measurements of the sample with coherent light, such that the measurement precision at any given intensity can be greatly enhanced. Furthermore, we show that this enhanced measurement precision is robust against experimental imperfections leading to photon losses, which usually tend to degrade the detection sensitivity. We trace the origin of this enhancement to an optimal degree of squeezing which has to be generated in a nonlinear SU(1,1) interferometer.

Electromagnetically induced transparency-like effect in a lithium niobate resonator via electronic control

Liu Yang, Yongyong Zhuang, Yifan Zhang, Yaojing Zhang, Shuangyou Zhang, Zhuo Xu, Pascal Del'Haye, Xiaoyong Wei

In this study, we theoretically proposed a method to achieve an electromagnetically induced transparency (EIT)-like effect in a whispering gallery mode resonator (WGMR) and experimentally validated the method in a lithium niobate (LN) device. Benefitting from the electro-optic and inverse piezoelectric effects of the LN material, two modes of the LN WGMR that are close in frequency can be tuned at different tuning rates, resulting in EIT-like resonance lineshapes. By varying the electric field applied to the LN WGMR, the full dynamic of the EIT-like phenomenon can be precisely controlled. The experimental results agreed well with the calculations based on the coupled mode theory. Moreover, we observed a hysteresis resulting from the photorefractive effect of LN. We believe our proposed method and demonstrated devices offer a way to control an EIT-like effect, which could have potential applications in light storage, quantum information processing, and enhanced sensing techniques.

Identification of a Distinct Monocyte-Driven Signature in Systemic Sclerosis Using Biophysical Phenotyping of Circulating Immune Cells

Alexandru-Emil Matei, Markéta Kubánková, Liyan Xu, Andrea-Hermina Györfi, Evgenia Boxberger, Despina Soteriou, Maria Papava, Julia Prater, Xuezhi Hong, et al.

OBJECTIVE: Pathologically activated circulating immune cells, including monocytes, play major roles in systemic sclerosis (SSc). Their functional characterization can provide crucial information with direct clinical relevance. However, tools for the evaluation of pathologic immune cell activation and, in general, of clinical outcomes in SSc are scarce. Biophysical phenotyping (including characterization of cell mechanics and morphology) provides access to a novel, mostly unexplored layer of information regarding pathophysiologic immune cell activation. We hypothesized that the biophysical phenotyping of circulating immune cells, reflecting their pathologic activation, can be used as a clinical tool for the evaluation and risk stratification of patients with SSc. METHODS: We performed biophysical phenotyping of circulating immune cells by real-time fluorescence and deformability cytometry (RT-FDC) in 63 SSc patients, 59 rheumatoid arthritis (RA) patients, 28 antineutrophil cytoplasmic antibody–associated vasculitis (AAV) patients, and 22 age- and sex-matched healthy donors. RESULTS: We identified a specific signature of biophysical properties of circulating immune cells in SSc patients that was mainly driven by monocytes. Since it is absent in RA and AAV, this signature reflects an SSc-specific monocyte activation rather than general inflammation. The biophysical properties of monocytes indicate current disease activity, the extent of skin or lung fibrosis, and the severity of manifestations of microvascular damage, as well as the risk of disease progression in SSc patients. CONCLUSION: Changes in the biophysical properties of circulating immune cells reflect their pathologic activation in SSc patients and are associated with clinical outcomes. As a high-throughput approach that requires minimal preparations, RT-FDC–based biophysical phenotyping of monocytes can serve as a tool for the evaluation and risk stratification of patients with SSc.

Setting the stage for universal pharmacological targeting of the glycocalyx

Karim Almahayni, Leonhard Möckl

All cells in the human body are covered by a complex meshwork of sugars as well as proteins and lipids to which these sugars are attached, collectively termed the glycocalyx. Over the past few decades, the glycocalyx has been implicated in a range of vital cellular processes in health and disease. Therefore, it has attracted considerable interest as a therapeutic target. Considering its omnipresence and its relevance for various areas of cell biology, the glycocalyx should be a versatile platform for therapeutic intervention, however, the full potential of the glycocalyx as therapeutic target is yet to unfold. This might be attributable to the fact that glycocalyx alterations are currently discussed mainly in the context of specific diseases. In this perspective review, we shift the attention away from a disease-centered view of the glycocalyx, focusing on changes in glycocalyx state. Furthermore, we survey important glycocalyx-targeted drugs currently available and finally discuss future steps. We hope that this approach will inspire a unified, holistic view of the glycocalyx in disease, helping to stimulate novel glycocalyx-targeted therapy strategies.

Dynamics of cell rounding during detachment

Agata Nyga, Katarzyna Plak, Martin Kräter, Marta Urbanska, Kyoohyun Kim, Jochen Guck, Buzz Baum

Animal cells undergo repeated shape changes, for example by rounding up and respreading as they divide. Cell rounding can be also observed in interphase cells, for example when cancer cells switch from a mesenchymal to an ameboid mode of cell migration. Nevertheless, it remains unclear how interphase cells round up. In this article, we demonstrate that a partial loss of substrate adhesion triggers actomyosin-dependent cortical remodeling and ERM activation, which facilitates further adhesion loss causing cells to round. Although the path of rounding in this case superficially resembles mitotic rounding in involving ERM phosphorylation, retraction fiber formation, and cortical remodeling downstream of ROCK, it does not require Ect2. This work provides insights into the way partial loss of adhesion actives cortical remodeling to drive cell detachment from the substrate. This is important to consider when studying the mechanics of cells in suspension, for example using methods like real-time deformability cytometry (RT-DC).

Confocal Interferometric Scattering Microscopy Reveals 3D Nanoscopic Structure and Dynamics in Live Cells

Michelle Küppers, David Albrecht, Anna D. Kashkanova, Jennifer Lühr, Vahid Sandoghdar

Bright-field light microscopy and related techniques continue to play a key role in life sciences because they provide a facile and label-free insight into biological specimen. However, lack of three-dimensional imaging and low sensitivity to nanoscopic features hamper their application in high-end quantitative studies. Here, we remedy these shortcomings by employing confocal interferometric scattering (iSCAT) microscopy. We demonstrate the performance of this label-free technique in a selection of case studies in live cells and benchmark our findings against simultaneously acquired fluorescence images. We reveal the nanometric topography of the nuclear envelope, quantify the dynamics of the endoplasmic reticulum, detect single microtubules, and map nanoscopic diffusion of clathrin-coated pits undergoing endocytosis. Furthermore, we introduce the combination of confocal and wide-field iSCAT modalities for simultaneous imaging of cellular structures and high-speed tracking of nanoscopic entities such as single SARS-CoV2 virions. Confocal iSCAT can be readily implemented as an additional contrast mechanism in existing laser scanning microscopes.

Rapid single-cell physical phenotyping of mechanically dissociated tissue biopsies

Despina Soteriou, Markéta Kubánková, Christine Schweitzer, Rocío López-Posadas, Rahmita Pradhan, Oana-Maria Thoma, Andrea-Hermina Györfi, Alexandru-Emil Matei, Maximilian Waldner, et al.

During surgery, rapid and accurate histopathological diagnosis is essential for clinical decision making. Yet the prevalent method of intra-operative consultation pathology is intensive in time, labour and costs, and requires the expertise of trained pathologists. Here we show that biopsy samples can be analysed within 30 min by sequentially assessing the physical phenotypes of singularized suspended cells dissociated from the tissues. The diagnostic method combines the enzyme-free mechanical dissociation of tissues, real-time deformability cytometry at rates of 100–1,000 cells s−1 and data analysis by unsupervised dimensionality reduction and logistic regression. Physical phenotype parameters extracted from brightfield images of single cells distinguished cell subpopulations in various tissues, enhancing or even substituting measurements of molecular markers. We used the method to quantify the degree of colon inflammation and to accurately discriminate healthy and tumorous tissue in biopsy samples of mouse and human colons. This fast and label-free approach may aid the intra-operative detection of pathological changes in solid biopsies.

Influence of Initial Surface Roughness on LIPSS Formation and Its Consecutive Impact on Cell/Bacteria Attachment for TiAl6V4 Surfaces

Lamborghini Sotelo, Tommaso Fontanot, Sanjana Vig, Patrick Herre, Peyman Yousefi, Maria Helena Fernandes, George Sarau, Gerd Leuchs, Silke Christiansen

The influence of the initial surface roughness of TiAl6V4 samples on the orientation and periodicity of the resulting laser-induced periodic surface structures (LIPSS), as well as the surface wettability and chemistry is reported here. Before LIPSS fabrication, initial sample surface roughness is adjusted by variations of finial polishing steps with polishing grain sizes of 18.3, 8.4, 5, and 0.5 mu m. A 3 x 3 irradiation matrix was defined and lasered on all samples by changing the laser power and distance between consecutive laser scans. The resulting structures were characterized by scanning electron microscopy (SEM), atomic force microscopy, Raman spectroscopy, and contact angle measurements. As a further step, three representative generated structures were chosen to explore their bone implant viability by resazurin assays, alkaline phosphatase activity, and direct SEM imaging of the induced cells (MG63) and bacteria (Escherichia coli and Staphylococcus aureus). Results show that initial surface roughness has big influence on the wettability of the resulting surface, as well as inducing small variations on the orientation of the generated LIPSS. Structures generated with a higher integrated fluence have also shown to enhance cell differentiation while reducing bacterial activity, making them a great candidate for improved bone implant compatibility and durability.

Modulational instability and spectral broadening of vortex modes in chiral photonic crystal fibers

Paul Roth, Philip Russell, Michael Frosz, Yang Chen, Gordon Wong

We report on intra- and inter-modal four-wave-mixing (FWM) in N-fold rotationally symmetric (C_N) single- and multi-core chiral photonic crystal fiber (PCF), created by spinning the preform during fiber drawing. The non-circular modal field is forced to rotate as it propagates along the fiber, resulting in circular birefringence and robust maintenance of circular polarization state. Multi-core chiral C_N PCF supports vortex-carrying helical Bloch modes (HBMs) in which the degeneracy between clockwise and counter-clockwise vortices is lifted. This makes possible new kinds of intermodal polarization modulational instability (PMI). We develop PMI theory for vortex HBMs, and illustrate the results by a series of experiments in which two or more PMI sidebands with different vorticities and polarization states are selectively generated by adjusting the polarization state and topological charge of the pump light. In every case both the topological charge and the spin of the pump light are conserved. We also report generation of a broadband supercontinuum in a single circularly polarized vortex mode.

On-the-fly precision spectroscopy with a dual-modulated tunable diode laser and Hz-level referencing to a cavity

Shuangyou Zhang, Toby Bi, Pascal Del'Haye

Advances in high-resolution laser spectroscopy have enabled many scientific breakthroughs in physics, chemistry, biology and astronomy. Optical frequency combs have pushed measurement limits with ultrahigh-frequency accuracy and fast-measurement speed while tunable diode laser spectroscopy is used in scenarios that require high power and continuous spectral coverage. Despite these advantages of tunable diode laser spectroscopy, it is challenging to precisely determine the instantaneous frequency of the laser because of fluctuations in the scan speed. Here we demonstrate a simple spectroscopy scheme with a frequency modulated diode laser that references the diode laser on-the-fly to a fiber cavity with sub-15 Hz frequency precision over an 11-THz range at a measurement speed of 1 THz/s. This is an improvement of more than two orders of magnitude compared to existing diode laser spectroscopy methods. Our scheme provides precise frequency calibration markers while simultaneously tracking the instantaneous scan speed of the laser. We demonstrate several applications, including dispersion measurement of an ultra-high-Q microresonator and spectroscopy of an HF gas cell, which can be used for absolute frequency referencing of the tunable diode laser. The simplicity, robustness and low costs of this spectroscopy scheme could prove extremely valuable for out-of-the-lab applications like LIDAR, gas spectroscopy and environmental monitoring.

Dynamic Brillouin cooling for continuous optomechanical systems

Changlong Zhu, Birgit Stiller

Up until now, ground state cooling using optomechanical interaction is realized in the regime where optical dissipation is higher than mechanical dissipation. Here, we demonstrate that optomechanical ground state cooling in a continuous optomechanical system is possible by using backward Brillouin scattering while mechanical dissipation exceeds optical dissipation which is the common case in optical waveguides. The cooling is achieved in an anti-Stokes backward Brillouin process by modulating the intensity of the optomechanical coupling via a pulsed pump to suppress heating processes in the strong coupling regime. With such dynamic modulation, a significant cooling factor can be achieved, which can be several orders of magnitude lower than for the steady-state case. This modulation scheme can also be applied to Brillouin cooling generated by forward intermodal Brillouin scattering.

Multiphoton non-local quantum interference controlled by an undetected photon

Kaiyi Qian, Kai Wang, Leizhen Chen, Hou Zhaohua, Mario Krenn, Shining Zhu, Xiao-Song Ma

The interference of quanta lies at the heart of quantum physics. The multipartite generalization<br>of single-quanta interference creates entanglement, the coherent superposition of states shared by several quanta. Entanglement allows non-local correlations between many quanta and hence is a key resource for quantum information technology. Entanglement is typically considered to be essential for creating non-local correlations, manifested by multipartite interference. Here, we show that this is not the case and demonstrate multiphoton non-local quantum interference without entanglement of any intrinsic properties of the photons. We harness the superposition of the physical origin of a four-photon product state, which leads to constructive and destructive interference of the photons’ mere existence. With the intrinsic indistinguishability in the generation process of photons, we realize four-photon frustrated quantum interference. We furthermore establish non-local control of multipartite quantum interference, in which we tune the phase of one undetected photon and observe the interference of the other three photons. Our work paves the way for fundamental studies of non-locality and potential applications in quantum technologies.

Impact of crowding on the diversity of expanding populations

Carl F. Schreck, Diana Fusco, Yuya Karita, Stephen Martis, Jona Kayser, Marie-Cécilia Duvernoy, Oskar Hallatschek

Crowding effects critically impact the self-organization of densely packed cellular assemblies, such as biofilms, solid tumors, and developing tissues. When cells grow and divide, they push each other apart, remodeling the structure and extent of the population’s range. Recent work has shown that crowding has a strong impact on the strength of natural selection. However, the impact of crowding on neutral processes, which controls the fate of new variants as long as they are rare, remains unclear. Here, we quantify the genetic diversity of expanding microbial colonies and uncover signatures of crowding in the site frequency spectrum. By combining Luria–Delbrück fluctuation tests, lineage tracing in a novel microfluidic incubator, cell-based simulations, and theoretical modeling, we find that the majority of mutations arise behind the expanding frontier, giving rise to clones that are mechanically “pushed out” of the growing region by the proliferating cells in front. These excluded-volume interactions result in a clone-size distribution that solely depends on where the mutation first arose relative to the front and is characterized by a simple power law for low-frequency clones. Our model predicts that the distribution depends on a single parameter—the characteristic growth layer thickness—and hence allows estimation of the mutation rate in a variety of crowded cellular populations. Combined with previous studies on high-frequency mutations, our finding provides a unified picture of the genetic diversity in expanding populations over the whole frequency range and suggests a practical method to assess growth dynamics by sequencing populations across spatial scales.

PT symmetry-protected exceptional cones and analogue Hawking radiation

Marcus Stålhammar, Jorge Larana-Aragon, Lucas Rødland, Flore K. Kunst

Non-Hermitian Hamiltonians, which effectively describe dissipative systems, and analogue gravity models, which simulate properties of gravitational objects, comprise seemingly different areas of current research. Here, we investigate the interplay between the two by relating parity-time- symmetric dissipative Weyl-type Hamiltonians to analogue Schwarzschild black holes emitting Hawking radiation. We show that the exceptional points of these Hamiltonians form tilted cones mimicking the behavior of the light cone of a radially infalling observer approaching a black hole horizon. We further investigate the presence of tunneling processes, reminiscent of those happening in black holes, in a concrete example model. We interpret the non-trivial result as the purely thermal contribution to analogue Hawking radiation in a Schwarzschild black hole. Assuming that our particular Hamiltonian models a photonic crystal, we discuss the concrete nature of the analogue Hawking radiation in this particular setup.

3D Nanocomposite with High Aspect Ratio Based on Polyaniline Decorated with Silver NPs: Synthesis and Application as Electrochemical Glucose Sensor

Anna A. Vasileva, Daria V. Mamonova, Vladimir Mikhailovskii, Yuri V. Petrov, Yana G. Toropova, Ilya E. Kolesnikov, Gerd Leuchs, Alina A. Manshina

In this paper, we present a new methodology for creating 3D ordered porous nanocomposites based on anodic aluminum oxide template with polyaniline (PANI) and silver NPs. The approach includes in situ synthesis of polyaniline on templates of anodic aluminum oxide nanomembranes and laser-induced deposition (LID) of Ag NPs directly on the pore walls. The proposed method allows for the formation of structures with a high aspect ratio of the pores, topological ordering and uniformity of properties throughout the sample, and a high specific surface area. For the developed structures, we demonstrated their effectiveness as non-enzymatic electrochemical sensors on glucose in a concentration range crucial for medical applications. The obtained systems possess high potential for miniaturization and were applied to glucose detection in real objects-laboratory rat blood plasma.

Control of Yu-Shiba-Rusinov States through a Bosonic Mode

Helene Müller, Martin Eckstein, Silvia Viola-Kusminskiy

We investigate the impact of a bosonic degree of freedom on Yu-Shiba-Rusinov states emerging from a magnetic impurity in a conventional superconductor. Starting from the Anderson impurity model, we predict that an additional p-wave conduction band channel opens up if a bosonic mode is coupled to the tunneling between impurity and host, which implies an additional pair of odd-parity Yu-Shiba-Rusinov states. The bosonic mode can be a vibrational mode or the electromagnetic field in a cavity. The exchange couplings in the two channels depend sensitively on the state of the bosonic mode (ground state, few quanta, or classically driven Floquet state), which opens possibilities for phononics or photonics control of such systems, with a rich variety of ground and excited states.

Quench-drive spectroscopy and high-harmonic generation in BCS superconductors

Matteo Puviani, Rafael Haenel, Dirk Manske

In pump-probe spectroscopies, THz pulses are used to quench a system, which is subsequently probed by either a THz or optical pulse. In contrast, third-harmonic generation experiments employ a single multicycle driving pulse and measure the induced third harmonic. In this work, we analyze a spectroscopy setup where both a quench and a drive are applied and two-dimensional spectra as a function of time and quench-drive delay are recorded. We calculate the time evolution of the nonlinear current generated in the superconductor within an Anderson-pseudospin framework and characterize all experimental signatures using a quasiequilibrium approach. We analyze the superconducting response in Fourier space with respect to both the frequencies corresponding to the real time and the quench-drive delay time. In particular, we show the presence of a transient modulation of higher harmonics, induced by a wave mixing process of the drive with the quench pulse, which probes both quasiparticle and collective excitations of the superconducting condensate.

Near single-photon imaging in the shortwave infrared using homodyne detection

O. Wolley, S. Mekhail, P. -A Moreau, T. Gregory, G. Gibson, Gerd Leuchs, M. J. Padgett

Low-light imaging is challenging in regimes where low-noise detectors are not yet available. One such regime is the shortwave infrared where even the best multipixel detector arrays typically have a noise floor in excess of 100 photons per pixel per frame. We present a homodyne imaging system capable of recovering both intensity and phase images of an object from a single frame despite an illumination intensity of ??? 1 photon per pixel. We interfere this weak signal which is below the noise floor of the detector with a reference beam that is ??? 300, 000 times brighter, record the resulting interference pattern in the spatial domain on a detector array, and use Fourier techniques to extract the intensity and phase images. We believe our approach could vastly extend the range of applications for low-light imaging by accessing domains where low-noise cameras are not currently available and for which low-intensity illumination is required.

Crystal superlattices for versatile and sensitive quantum spectroscopy

Zi S. D. Toa, Maria V. Chekhova, Leonid A. Krivitsky, Anna V. Paterova

Nonlinear interferometers with quantum correlated photons have been demonstrated to improve optical characterization and metrology. These interferometers can be used in gas spectroscopy, which is of particular interest for monitoring greenhouse gas emissions, breath analysis and industrial applications. Here, we show that gas spectroscopy can be further enhanced via the deployment of crystal superlattices. This is a cascaded arrangement of nonlinear crystals forming interferometers, allowing the sensitivity to scale with the number of nonlinear elements. In particular, the enhanced sensitivity is observed via the maximum intensity of interference fringes that scales with low concentration of infrared absorbers, while for high concentration the sensitivity is better in interferometric visibility measurements. Thus, a superlattice acts as a versatile gas sensor since it can operate by measuring different observables, which are relevant to practical applications. We believe that our approach offers a compelling path towards further enhancements for quantum metrology and imaging using nonlinear interferometers with correlated photons.

Self-supervised machine learning pushes the sensitivity limit in label-free detection of single proteins below 10 kDa

Mahyar Dahmardeh, Houman Mirzaalian Dastjerdi, Hisham Mazal, Harald Köstler, Vahid Sandoghdar

Interferometric scattering (iSCAT) microscopy is a label-free optical method capable of detecting single proteins, localizing their binding positions with nanometer precision, and measuring their mass. In the ideal case, iSCAT is limited by shot noise such that collection of more photons should extend its detection sensitivity to biomolecules of arbitrarily low mass. However, a number of technical noise sources combined with speckle-like background fluctuations have restricted the detection limit in iSCAT. Here, we show that an unsupervised machine learning isolation forest algorithm for anomaly detection pushes the mass sensitivity limit by a factor of 4 to below 10 kDa. We implement this scheme both with a user-defined feature matrix and a self-supervised FastDVDNet and validate our results with correlative fluorescence images recorded in total internal reflection mode. Our work opens the door to optical investigations of small traces of biomolecules and disease markers such as α-synuclein, chemokines and cytokines.<br><br>

Compact Yb fiber few-cycle pulse source based on precision pulse compression and shaping with an adaptive fiber Bragg grating

Jacob Lampen, Francesco Tani, Peng Li, Kevin F. Lee, Jie Jiang, Philip Russell, Martin E. Fermann

We generate bandwidth limited 10 µJ pulses of 92 fs pulse width using an adaptive fiber Bragg grating stretcher (FBG) in conjunction with a Lyot filter. The temperature controlled FBG is used to optimize the group delay, whereas the Lyot filter counteracts gain narrowing in the amplifier chain. Soliton compression in a hollow core fiber (HCF) allows for access to the few-cycle pulse regime. Adaptive control further enables the generation of nontrivial pulse shapes.

A new hyperelastic lookup table for RT-DC

Lukas Daniel Wittwer, Felix Reichel, Paul Mueller, Jochen Guck, Sebastian Aland

Real-time deformability cytometry (RT-DC) is an established method that quantifies features like size, shape, and stiffness for whole cell populations on a single-cell level in real-time. A lookup table (LUT) disentangles the experimentally derived steady-state cell deformation and the projected area to extract the cell stiffness in the form of the Young's modulus. So far, two lookup tables exist but are limited to simple linear material models and cylindrical channel geometries. Here, we present two new lookup tables for RT-DC based on a neo-Hookean hyperelastic material numerically derived by simulations based on the finite element method in square and cylindrical channel geometries. At the same time, we quantify the influence of the shear-thinning behavior of the surrounding medium on the stationary deformation of cells in RT-DC and discuss the applicability and impact of the proposed LUTs regarding past and future RT-DC data analysis. Additionally, we provide insights about the cell strain and stresses, as well as the influence resulting from the rotational symmetric assumption on the cell deformation and volume estimation. The new lookup tables and the numerical cell shapes are made freely available.

In situ Detection of Cobaloxime Intermediates During Photocatalysis Using Hollow-Core Photonic Crystal Fiber Microreactors

Takashi Lawson, Alexander S. Gentleman, Jonathan Pinnell, Annika Eisenschmidt, Daniel Antón-García, Michael Frosz, Erwin Reisner, Tijmen G. Euser

Hollow-core photonic crystal fibers (HC-PCFs) provide a novel approach for in situ UV/Vis spectroscopy with enhanced detection sensitivity. Here, we demonstrate that longer optical path lengths than afforded by conventional cuvette-based UV/Vis spectroscopy can be used to detect and identify the CoI and CoII states in hydrogen-evolving cobaloxime catalysts, with spectral identification aided by comparison with DFT-simulated spectra. Our findings show that there are two types of signals observed for these molecular catalysts; a transient signal and a steady-state signal, with the former being assigned to the CoI state and the latter being assigned to the CoII state. These observations lend support to a unimolecular pathway, rather than a bimolecular pathway, for hydrogen evolution. This study highlights the utility of fiber-based microreactors for understanding these and a much wider range of homogeneous photocatalytic systems in the future.

Machine learning assisted inverse design of microresonators

Arghadeep Pal, Alekhya Ghosh, Shuangyou Zhang, Toby Bi, Pascal Del'Haye

The high demand for fabricating microresonators with desired optical properties has led to various techniques to optimize geometries, mode structures, nonlinearities, and dispersion. Depending on applications, the dispersion in such resonators counters their optical nonlinearities and influences the intracavity optical dynamics. In this paper, we demonstrate the use of a machine learning (ML) algorithm as a tool to determine the geometry of microresonators from their dispersion profiles. The training dataset with ∼460 samples is generated by finite element simulations and the model is experimentally verified using integrated silicon nitride microresonators. Two ML algorithms are compared along with suitable hyperparameter tuning, out of which Random Forest yields the best results. The average error on the simulated data is well below 15%.

Local sampling of the SU(1,1) Wigner function

Nicolas Fabre, Andrei B. Klimov, Gerd Leuchs, Luis Sanchez-Soto

Despite its indisputable merits, the Wigner phase-space formulation has not been widely explored for systems with SU(1,1) symmetry, as a simple operational definition of the Wigner function has proved elusive in this case. We capitalize on unique properties of the parity operator, to derive in a consistent way a bona fide SU(1,1) Wigner function that faithfully parallels the structure of its continuous-variable counterpart. We propose an optical scheme, involving a squeezer and photon-number-resolving detectors, that allows for direct point-by-point sampling of that Wigner function. This provides an adequate framework to represent SU(1,1) states satisfactorily.

Selective phase filtering of charged beams with laser-driven antiresonant hollow-core fibers

Luca Genovese, Max Kellermeier, Frank Mayet, Klaus Floettmann, Gordon Wong, Michael Frosz, Ralph Assmann, Philip Russell, Francois Lemery

Emerging accelerator concepts increasingly rely on the combination of high-frequency electromagnetic radiation with electron beams, enabling longitudinal phase space manipulation which supports a variety of advanced applications. The handshake between electron beams and radiation is conventionally provided by magnetic undulators which unfortunately require a balance between the electron beam energy, undulator parameters, and laser wavelength. Here we propose a scheme using laser-driven large-core antiresonant optical fibers to manipulate electron beams. We explore two general cases using TM01 and HE11 modes. In the former, we show that large energy modulations O(100 keV). can be achieved while maintaining the overall electron beam quality. Further, we show that by using larger field strengths O(100 MV/m) the resulting transverse forces can be exploited with beam-matching conditions to filter arbitrary phases from the modulated electron bunch, leading to the production of ≈100 attosecond FWHM microbunches. Finally, we also investigate the application of the transverse dipole HE11 mode and find it suitable for supporting time-resolved electron beam measurements with sub-attosecond resolution. We expect the findings to be widely appealing to high-charge pump-probe experiments, metrology, and accelerator science.

Multicolor super-resolution imaging to study human coronavirus RNA during cellular infection

Anish R. Roy, Jiarui Wang, Mengting Han, Haifeng Wang, Leonhard Möckl, Leiping Zeng, William E. Moerner, Lei S. Qi

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human coronavirus within 20 years that gave rise to a life-threatening disease and the first to reach pandemic spread. While the scientific community has studied coronavirus biology using genomics, cryoelectron microscopy, and electron tomography, how coronavirus RNA is spatially organized in the cell at the different stages of the viral replication cycle at nanoscale resolution is largely unknown. To make therapeutic headway against current and future coronaviruses, the biology of coronavirus RNA during infection must be precisely understood. Here, we introduce a multicolor super-resolution (SR) fluorescence imaging framework to examine the spatial interactions between viral RNA and other viral factors during host cell infection. We demonstrate the efficacy of our approach using the HCoV-229E coronavirus in MRC5 lung fibroblasts and specifically label two key oligonucleotide viral players: viral genomic RNA (gRNA) and double-stranded RNA (dsRNA). The 10-nm resolution achieved by our approach uncovers a striking spatial organization of gRNA and dsRNA into three distinct RNA structures: (1) large gRNA clusters, (2) very tiny nanoscale gRNA puncta containing a single copy of the genome, and (3) round intermediate-sized puncta highlighted by the dsRNA label. Furthermore, we use our two-color SR approach to visualize the nanoscale spatial relationships between viral gRNA and the endoplasmic reticulum (ER), dsRNA and ER, gRNA and the spike protein, and gRNA and dsRNA. In particular, we observe two striking observations that provide insight into viral replication and export. First, spike proteins and gRNA rarely assemble into an assembled virion in the MRC5 cytoplasm. Second, in contrast to previous observations, dsRNA and gRNA spatially separate. Our approach provides a comprehensive imaging framework that will enable future investigations of coronavirus fundamental biology and the effects of therapeutics.

Learning Quantum Systems

Valentin Gebhart, Raffaele Santagati, Antonio Andrea Gentile, Erik Gauger, David Craig, Natalia Ares, Leonardo Banchi, Florian Marquardt, Luca Pezzè, et al.

The future development of quantum technologies relies on creating and manipulating quantum systems of increasing complexity, with key applications in computation, simulation and sensing. This poses severe challenges in the efficient control, calibration and validation of quantum states and their dynamics. Although the full simulation of large-scale quantum systems may only be possible on a quantum computer, classical characterization and optimization methods still play an important role. Here, we review different approaches that use classical post-processing techniques, possibly combined with adaptive optimization, to learn quantum systems, their correlation properties, dynamics and interaction with the environment. We discuss theoretical proposals and successful implementations across different multiple-qubit architectures such as spin qubits, trapped ions, photonic and atomic systems, and superconducting circuits. This Review provides a brief background of key concepts recurring across many of these approaches with special emphasis on the Bayesian formalism and neural networks.<br><br>

Physical Mechanisms Underpinning the Vacuum Permittivity

Gerd Leuchs, Margaret Hawton, Luis Sanchez-Soto

The debate about the emptiness of space goes back to the prehistory of science and is epitomized by the Aristotelian 'horror vacui', which can be seen as the precursor of the ether, whose modern version is the dynamical quantum vacuum. In this paper, we suggest to change a common view to 'gaudium vacui' and discuss how the vacuum fluctuations fix the value of the permittivity, e(0), and permeability, mu(0), by modelling their dynamical response by three-dimensional harmonic oscillators.

Tunneling-induced fractal transmission in Valley Hall waveguides

Tirth Shah, Florian Marquardt, Vittorio Peano

The valley Hall effect provides a popular route to engineer robust waveguides for bosonic excitations such as photons and phonons. The almost complete absence of backscattering in many experiments has its theoretical underpinning in a smooth-envelope approximation that neglects large momentum transfer and is accurate only for small bulk band gaps and/or smooth domain walls. For larger bulk band gaps and hard domain walls, backscattering is expected to become significant. Here, we show that in this experimentally relevant regime, the reflection of a wave at a sharp corner becomes highly sensitive to the orientation of the outgoing waveguide relative to the underlying lattice. Enhanced backscattering can be understood as being triggered by resonant tunneling transitions in quasimomentum space. Tracking the resonant tunneling energies as a function of the waveguide orientation reveals a self-repeating fractal pattern that is also imprinted in the density of states and the backscattering rate at a sharp corner.<br><br>

Investigation of inverse design of multilayer thin-films with conditional invertible Neural Networks

Alexander Luce, Ali Mahdavi, Heribert Wankerl, Florian Marquardt

In this work, we apply conditional invertible neural networks (cINN) to inversely design multilayer thin-films given an optical target in order to overcome limitations of state-of-the-art optimization approaches. Usually, state-of-the-art algorithms depend on a set of carefully chosen initial thin-film parameters or employ neural networks which must be retrained for every new application. We aim to overcome those limitations by training the cINN to learn the loss landscape of all thin-film configurations within a training dataset. We show that cINNs can generate a stochastic ensemble of proposals for thin-film configurations that are reasonably close to the desired target depending only on random variables. By refining the proposed configurations further by a local optimization, we show that the generated thin-films reach the target with significantly greater precision than comparable state-of-the-art approaches. Furthermore, we tested the generative capabilities on samples which are outside of the training data distribution and found that the cINN was able to predict thin-films for out-of-distribution targets, too. The results suggest that in order to improve the generative design of thin-films, it is instructive to use established and new machine learning methods in conjunction in order to obtain the most favorable results.<br><br>

Linear optical elements based on cooperative subwavelength emitter arrays

Nico S. Baßler, Michael Reitz, Kai P. Schmidt, Claudiu Genes

We describe applications of two-dimensional subwavelength quantum emitter arrays as efficient optical elements in the linear regime. For normally incident light, the cooperative optical response, stemming from emitter-emitter dipole exchanges, allows the control of the array’s transmission, its resonance frequency, and bandwidth. Operations on fully polarized incident light, such as generic linear and circular polarizers as well as phase retarders can be engineered and described in terms of Jones matrices. Our analytical approach and accompanying numerical simulations identify optimal regimes for such operations and reveal the importance of adjusting the array geometry and of the careful tuning of the external magnetic fields amplitude and direction.<br><br>

Proposal for a hybrid clock system consisting of passive and active optical clocks and a fully stabilized microcomb

Deshui Yu, Frank Vollmer, Pascal Del'Haye, Shougang Zhang

Optical atomic clocks produce highly stable frequency standards and frequency combs bridge clock frequencies with hundreds of terahertz difference. In this paper, we propose a hybrid clock scheme, where a light source pumps an active optical clock through a microresonator-based nonlinear third harmonic process, serves as a passive optical clock via indirectly locking its frequency to an atomic transition, and drives a chip-scale microcomb whose mode spacing is stabilized using the active optical clock. The operation of the whole hybrid system is investigated through simulation analysis. The numerical results show: (i) The short-term frequency stability of the passive optical clock follows an Allan deviation of σy(τ) = 9.3 × 10−14τ−1/2 with the averaging time τ, limited by the population fluctuations of interrogated atoms. (ii) The frequency stability of the active optical clock reaches σy(τ) = 6.2 × 10−15τ−1/2, which is close to the quantum noise limit. (iii) The mode spacing of the stabilized microcomb has a shot-noise-limited Allan deviation of σy(τ) = 1.9 × 10−11τ−1/2. Our hybrid scheme may be realized using recently developed technologies in (micro)photonics and atomic physics, paving the way towards on-chip optical frequency comparison, synthesis, and synchronization.

Shear rheology of methyl cellulose based solutions for cell mechanical measurements at high shear rates

Beyza Büyükurganci, Santanu Kumar Basu, Markus Neuner, Jochen Guck, Andreas Wierschem, Felix Reichel

Methyl cellulose (MC) is a widely used material in various microfluidic applications in biology. Due to its biocompatibility, it has become a popular crowding agent for microfluidic cell deformability measurements, which usually operate at high shear rates (>10 000 s−1). However, a full rheological characterization of methyl cellulose solutions under these conditions has not yet been reported. With this study, we provide a full shear-rheological description for solutions of up to 1% MC dissolved in phosphate-buffered saline (PBS) that are commonly used in real-time deformability cytometry (RT-DC). We characterized three different MC-PBS solutions used for cell mechanical measurements in RT-DC with three different shear rheometer setups to cover a range of shear rates from 0.1–150 000 s−1. We report viscosities and normal stress differences in this regime. Viscosity functions can be well described using a Carreau–Yasuda model. Furthermore, we present the temperature dependency of shear viscosity and first normal stress difference of these solutions. Our results show that methyl cellulose solutions behave like power-law liquids in viscosity and exhibit first normal stress difference at shear rates between 5000–150 000 s−1. We construct a general viscosity equation for each MC solution at a certain shear rate and temperature. Furthermore, we investigated how MC concentration influences the rheology of the solutions and found the entanglement concentration at around 0.64 w/w%. Our results help to better understand the viscoelastic behavior of MC solutions, which can now be considered when modelling stresses in microfluidic channels.

Optical Vortex Brillouin Laser

Xinglin Zeng, Philip Russell, Yang Chen, Zheqi Wang, Gordon Wong, Paul Roth, Michael Frosz, Birgit Stiller

Optical vortices, which have been extensively studied over the last decades, offer an additional degree of freedom useful in many applications, such as optical tweezers and quantum control. Stimulated Brillouin scattering (SBS), providing a narrow linewidth and a strong nonlinear response, has been used to realize quasi-continuous wave lasers. Here, stable oscillation of optical vortices and acoustic modes in a Brillouin laser based on chiral photonic crystal fiber (PCF) is reported, which robustly supports helical Bloch modes (HBMs) that carry circularly polarized optical vortex and display circular birefringence. A narrow-linewidth Brillouin fiber laser that stably emits 1st- and 2nd-order vortex-carrying HBMs is implemented. Angular momentum conservation selection rules dictate that pump and backward Brillouin signals have opposite topological charge and spin. Additionally, it is shown that when the chiral PCF is placed within a laser ring cavity, the linewidth-narrowing associated with lasing permits the peak of the Brillouin gain that corresponds to acoustic mode to be measured with resolution of 10 kHz and accuracy of 520 kHz. The results pave the way to a new generation of vortex-carrying SBS systems with applications in optical tweezers, quantum information processing, and vortex-carrying nonreciprocal systems.

Complex decoherence-free interactions between giant atoms

Lei Du, Lingzhen Guo, Yong Li

Giant atoms provide a promising platform for engineering decoherence-free interactions, which is a major task in modern quantum technologies. Here we study systematically how to implement complex decoherence-free interactions among giant atoms resorting to periodic coupling modulations and suitable arrangements of coupling points. We demonstrate that the phase of the modulation, which is tunable in experiments, can be encoded into the decoherence-free interactions and thus enables phase-dependent dynamics when the giant atoms constitute an effective closed loop. Moreover, we consider the influence of non-Markovian retardation effect arising from large separations of the coupling points and study its dependence on the modulation parameters.

From Dyson Models to Many-Body Quantum Chaos

Alexei Andreanov, Matteo Carrega, Jeff Murugan, Jan Olle, Dario Rosa, Ruth Shir

Understanding the mechanisms underlying many-body quantum chaos is one of the big challenges in theoretical physics. We tackle this problem by considering a set of perturbed quadratic Sachdev-Ye-Kitaev (SYK) Hamiltonians defined on graphs. This allows to disambiguate between operator growth and \emph{delocalization}, showing that the latter is the dominant process in the single-particle to many-body chaotic transition. Our results are verified numerically with state-of-the-art numerical techniques, capable of extracting eigenvalues in a desired energy window of very large Hamiltonians, in this case up to dimension 2¹⁹×2¹⁹. Our approach essentially provides a new way of viewing many-body chaos from a single-particle perspective.

Embracing the diversity of model systems to deconstruct the basis of regeneration and tissue repair

Aldine Amiel, Stephanie Tsai, Daniel Wehner

The eighth EMBO conference in the series ‘The Molecular and Cellular Basis of Regeneration and Tissue Repair’ took place in Barcelona (Spain) in September 2022. A total of 173 researchers from across the globe shared their latest advances in deciphering the molecular and cellular basis of wound healing, tissue repair and regeneration, as well as their implications for future clinical applications. The conference showcased an ever-expanding diversity of model organisms used to identify mechanisms that promote regeneration. Over 25 species were discussed, ranging from invertebrates to humans. Here, we provide an overview of the exciting topics presented at the conference, highlighting novel discoveries in regeneration and perspectives for regenerative medicine.

Observation of Robust Polarization Squeezing via the Kerr Nonlinearity in an Optical Fiber

Nikolay Kalinin, Thomas Dirmeier, Arseny A. Sorokin, Elena A. Anashkina, Luis Sanchez-Soto, Joel F. Corney, Gerd Leuchs, Alexey V. Andrianov

Squeezed light is one of the resources of photonic quantum technology. Among the various nonlinear interactions capable of generating squeezing, the optical Kerr effect is particularly easy-to-use. A popular venue is to generate polarization squeezing, which is a special self-referencing variant of two-mode squeezing. To date, polarization squeezing generation setups have been very sensitive to fluctuations of external factors and have required careful tuning. In this work, a development of a new all-fiber setup for polarization squeezing generation is reported. The setup consists of passive elements only and is simple, robust, and stable. More than 5 dB of directly measured squeezing is obtained over long periods of time without any need for adjustments. Thus, the new scheme provides a robust and easy-to-set-up way of obtaining squeezed light applicable to different applications. The impact of pulse duration and pulse power on the degree of squeezing is investigated.

Measurement of Minute Liquid Volumes of Chiral Molecules Using In-Fiber Polarimetry

Florian Schorn, Arabella Essert, Yu Zhong, Sahib Abdullayev, Kathrin Castiglione, Marco Haumann, Nicolas Y. Joly

We report an optofluidic method that enables to efficiently measure the enantiomeric excess of chiral molecules at low concentrations. The approach is to monitor the optical activity induced by a Kagome-lattice hollow core photonic crystal fiber filled with a sub-mu L volume of chiral compounds. The technique also allows monitoring the enzymatic racemization of Rmandelic acid.

On-chip quantum interference between the origins of a multi-photon state

Lan-Tian Feng, Ming Zhang, Di Liu, Yu-Jie Cheng, Guo-Ping Guo, Dao-Xin Dai, Guang-Can Guo, M. Krenn, Xi-Feng Ren

Quantum mechanically, multiple particles can jointly be in a coherent superposition of two or more different states at the same time. This property is called quantum entanglement, and gives rise to characteristic nonlocal interference and stays at the heart of quantum information process. Here, rather than interference of different intrinsic properties of particles, we experimentally demonstrated coherent superposition of two different birthplaces of a four-photon state. The quantum state is created in four probabilistic photon-pair sources, two combinations of which can create photon quadruplets. Coherent elimination and revival of distributed 4-photons can be fully controlled by tuning a phase. The stringent coherence requirements are met by using a silicon-based integrated photonic chip that contains four spiral waveguides for producing photon pairs via spontaneous four-wave mixing. The experiment gives rise to peculiar nonlocal phenomena without any obvious involvement of entanglement. Besides several potential applications that exploit the new on-chip technology, it opens up the possibility for fundamental studies on nonlocality with spatially separated locations.

Direct Optical Probe of Magnon Topology in Two-Dimensional Quantum Magnets

Emil Viñas Boström, Tahereh Sadat Parvini, James W. McIver, Angel Rubio, Silvia Viola-Kusminskiy, Michael A. Sentef

Controlling edge states of topological magnon insulators is a promising route to stable spintronics devices. However, to experimentally ascertain the topology of magnon bands is a challenging task. Here we derive a fundamental relation between the light-matter coupling and the quantum geometry of magnon states. This allows us to establish the two-magnon Raman circular dichroism as an optical probe of magnon topology in honeycomb magnets, in particular of the Chern number and the topological gap. Our results pave the way for interfacing light and topological magnons in functional quantum devices.

Quantum coherent control in pulsed waveguide optomechanics

Junyin Zhang, Changlong Zhu, Christian Wolff, Birgit Stiller

Coherent control of traveling acoustic excitations in a waveguide system is an interesting way to manipulate and transduce classical and quantum information. So far, these interactions, often based on optomechanical resonators or Brillouin scattering, have been studied in the steady-state regime using continuous waves. However, waveguide experiments are often based on optical pump pulses, which require treatment in a dynamic framework. In this paper, we present an effective Hamiltonian formalism in the dynamic regime using optical pulses that links waveguide optomechanics and cavity optomechanics, which can be used in the classical and quantum regime including quantum noise. Based on our formalism, a closed solution for coupled-mode equation under the undepleted assumption is provided and we found that the strong coupling regime is already accessible in current Brillouin waveguides by using pulses. We further investigate several possible experiments within waveguide optomechanics, including Brillouin-based coherent transfer, Brillouin cooling, and optoacoustic entanglement.

Image-based cell sorting using focused travelling surface acoustic waves

Ahmad Ahsan Nawaz, Despina Soteriou, Catherine Xu, Ruchi Goswami, Maik Herbig, Jochen Guck, Salvatore Girardo

Sorting cells is an essential primary step in many biological and clinical applications such as high-throughput drug screening, cancer research and cell transplantation. Cell sorting based on their mechanical properties has long been considered as a promising label-free biomarker that could revolutionize the isolation of cells from heterogeneous populations. Recent advances in microfluidic image-based cell analysis combined with subsequent label-free sorting by on-chip actuators demonstrated the possibility of sorting cells based on their physical properties. However, the high purity of sorting is achieved at the expense of a sorting rate that lags behind the analysis throughput. Furthermore, stable and reliable system operation is an important feature in enabling the sorting of small cell fractions from a concentrated heterogeneous population. Here, we present a label-free cell sorting method, based on the use of focused travelling surface acoustic wave (FTSAW) in combination with real-time deformability cytometry (RT-DC). We demonstrate the flexibility and applicability of the method by sorting distinct blood cell types, cell lines and particles based on different physical parameters. Finally, we present a new strategy to sort cells based on their mechanical properties. Our system enables the sorting of up to 400 particles per s. Sorting is therefore possible at high cell concentrations (up to 36 million per ml) while retaining high purity (>92%) for cells with diverse sizes and mechanical properties moving in a highly viscous buffer. Sorting of small cell fraction from a heterogeneous population prepared by processing of small sample volume (10 μl) is also possible and here demonstrated by the 667-fold enrichment of white blood cells (WBCs) from raw diluted whole blood in a continuous 10-hour sorting experiment. The real-time analysis of multiple parameters together with the high sensitivity and high-throughput of our method thus enables new biological and therapeutic applications in the future.

Epithelial RAC1-dependent cytoskeleton dynamics controls cell mechanics, cell shedding and barrier integrity in intestinal inflammation

Luz del Carmen Martínez-Sánchez, Phuong Anh Ngo, Rashmita Pradhan, Lukas-Sebastian Becker, David Boehringer, Despina Soteriou, Markéta Kubánková, Christine Schweitzer, Tatyana Koch, et al.

OBJECTIVE: Increased apoptotic shedding has been linked to intestinal barrier dysfunction and development of inflammatory bowel diseases (IBD). In contrast, physiological cell shedding allows the renewal of the epithelial monolayer without compromising the barrier function. Here, we investigated the role of live cell extrusion in epithelial barrier alterations in IBD. DESIGN: Taking advantage of conditional GGTase and RAC1 knockout mice in intestinal epithelial cells (Pggt1biΔIEC and Rac1iΔIEC mice), intravital microscopy, immunostaining, mechanobiology, organoid techniques and RNA sequencing, we analysed cell shedding alterations within the intestinal epithelium. Moreover, we examined human gut tissue and intestinal organoids from patients with IBD for cell shedding alterations and RAC1 function. RESULTS: Epithelial Pggt1b deletion led to cytoskeleton rearrangement and tight junction redistribution, causing cell overcrowding due to arresting of cell shedding that finally resulted in epithelial leakage and spontaneous mucosal inflammation in the small and to a lesser extent in the large intestine. Both in vivo and in vitro studies (knockout mice, organoids) identified RAC1 as a GGTase target critically involved in prenylation-dependent cytoskeleton dynamics, cell mechanics and epithelial cell shedding. Moreover, inflamed areas of gut tissue from patients with IBD exhibited funnel-like structures, signs of arrested cell shedding and impaired RAC1 function. RAC1 inhibition in human intestinal organoids caused actin alterations compatible with arresting of cell shedding. CONCLUSION: Impaired epithelial RAC1 function causes cell overcrowding and epithelial leakage thus inducing chronic intestinal inflammation. Epithelial RAC1 emerges as key regulator of cytoskeletal dynamics, cell mechanics and intestinal cell shedding. Modulation of RAC1 might be exploited for restoration of epithelial integrity in the gut of patients with IBD.

Photon pairs bi-directionally emitted from a resonant metasurface

Changjin Son, Vitaliy Sultanov, Tomas Santiago-Cruz, Aravind P. Anthur, Haizhong Zhang, Ramon Paniagua-Dominguez, Leonid Krivitsky, Arseniy I. Kuznetsov, Maria V. Chekhova

Metasurfaces are artificially structured surfaces able to control the properties of light at subwavelength scales. While, initially, they have been proposed as means to control classical optical fields, they are now emerging as nanoscale sources of quantum light, in particular of entangled photons with versatile properties. Geometric resonances in metasurfaces have been recently used to engineer the frequency spectrum of entangled photons, but the emission directivity was so far less studied. Here, we generate photon pairs via spontaneous parametric down conversion from a metasurface supporting a quasi-bound state in the continuum (BIC) leading to remarkable emission directivities. The pair generation rate is enhanced 67 times compared to the case of an unpatterned film of the same thickness and material. At the wavelength of the quasi-BIC resonance, photons are mostly emitted backwards, while their partners, spectrally detuned by only 8 nm, are emitted forwards. This behavior demonstrates fine spectral splitting of entangled photons and their bi-directional emission, never before observed in nanoscale sources. We expect this work to be a starting point for the efficient demultiplexing of photons in nanoscale quantum optics.

Artificial Intelligence and Machine Learning for Quantum Technologies

Mario Krenn, Jonas Landgraf, Thomas Fösel, Florian Marquardt

In recent years the dramatic progress in machine learning has begun to impact many areas of science and technology significantly. In the present perspective article, we explore how quantum technologies are benefiting from this revolution. We showcase in illustrative examples how scientists in the past few years have started to use machine learning and more broadly methods of artificial intelligence to analyze quantum measurements, estimate the parameters of quantum devices, discover new quantum experimental setups, protocols, and feed- back strategies, and generally improve aspects of quantum computing, quantum communication, and quantum simulation. We highlight open challenges and future possibilities and conclude with some speculative visions for the next decade.