Fibrosis and persistent inflammation are interconnected processes that inhibit axon regeneration in the mammalian central nervous system (CNS). In zebrafish, by contrast, fibroblast-derived extracellular matrix deposition and inflammation are tightly regulated to facilitate regeneration. However, the regulatory cross-talk between fibroblasts and the innate immune system in the regenerating CNS remains poorly understood. Here, we show that zebrafish fibroblasts possess a dual role in inducing and resolving inflammation, which are both essential for regeneration. We identify a transient, injury-specific cthrc1a+ fibroblast state with an inflammation-associated, less differentiated, and non-fibrotic profile. Induction of this fibroblast state precedes and contributes to the initiation of the inflammatory response. At the peak of neutrophil influx, cthrc1a+ fibroblasts coordinate the resolution of inflammation. Disruption of these inflammation dynamics alters the mechano-structural properties of the lesion environment and inhibits axon regeneration. This establishes the biphasic inflammation control by dedifferentiated fibroblasts as a pivotal mechanism for CNS regeneration.
Simultaneous measurement of multimode squeezing through multimode phase-sensitive amplification
Ismail Barakat, Mahmoud Kalash, Dennis Scharwald, Polina Sharapova, Norbert Lindlein, Maria Chekhova
Multimode squeezed light is increasingly popular in photonic quantum technologies, including sensing, imaging, and computation. Existing methods for its characterization are technically complex, often reducing the level of squeezing and typically addressing only a single mode at a time. Here, for the first time, we employ optical parametric amplification to characterize multiple squeezing eigenmodes simultaneously. We retrieve the shapes and squeezing degrees of all modes at once through direct detection followed by modal decomposition. This method is tolerant to inefficient detection and does not require a local oscillator. For a spectrally and spatially multimode squeezed vacuum, we characterize the eight strongest spatial modes, obtaining squeezing and anti-squeezing values of up to −5.2 ± 0.2 dB and 8.6 ± 0.3 dB, respectively, despite 50% detection loss. This work, being the first exploration of an optical parametric amplifier’s multimode capability for squeezing detection, paves the way for real-time multimode squeezing detection.
On-chip microresonator dispersion engineering via segmented sidewall modulation
Masoud Kheyri, Shuangyou Zhang, Toby Bi, Arghadeep Pal, Hao Zhang, Yaojing Zhang, Abdullah Alabbadi, Haochen Yan, Alekhya Ghosh, et al.
Photonics Research
13
367-372
(2025)
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Microresonator dispersion plays a crucial role in shaping the nonlinear dynamics of microcavity solitons. Here, we introduce and validate a method for dispersion engineering through modulating a portion of the inner edge of ring waveguides. We demonstrate that such partial modulation has a broadband effect on the dispersion profile, whereas modulation on the entire resonator’s inner circumference leads to mode splitting primarily affecting one optical mode. The impact of spatial modulation amplitude, period, and number of modulations on the mode splitting profile is also investigated. Through the integration of four modulated sections with different modulation amplitudes and periods, we achieve mode splitting across more than 50 modes over a spectral range exceeding 100 nm in silicon nitride resonators. These results highlight both the simplicity and efficacy of our method in achieving flatter dispersion profiles.
Lipidic folding pathway of α-Synuclein via a toxic oligomer
Christian Griesinger, Vrinda Sant, Dirk Matthes, Hisham Mazal, Leif Antonschmidt, Franz Wieser, Kumar Tekwani Movellan, Kai Xue, Evgeny Nimerovsky, et al.
Nature Communications
16
760
(2025)
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Aggregation intermediates play a pivotal role in the assembly of amyloid fibrils, which are central to the pathogenesis of neurodegenerative diseases. The structures of filamentous intermediates and mature fibrils are now efficiently determined by single-particle cryo-electron microscopy. By contrast, smaller pre-fibrillar α-Synuclein (αS) oligomers, crucial for initiating amyloidogenesis, remain largely uncharacterized. We report an atomic-resolution structural characterization of a toxic pre-fibrillar aggregation intermediate (I1) on pathway to the formation of lipidic fibrils, which incorporate lipid molecules on protofilament surfaces during fibril growth on membranes. Super-resolution microscopy reveals a tetrameric state, providing insights into the early oligomeric assembly. Time-resolved nuclear magnetic resonance (NMR) measurements uncover a structural reorganization essential for the transition of I1 to mature lipidic L2 fibrils. The reorganization involves the transformation of anti-parallel β-strands during the pre-fibrillar I1 state into a β-arc characteristic of amyloid fibrils. This structural reconfiguration occurs in a conserved structural kernel shared by a vast number of αS-fibril polymorphs, including extracted fibrils from Parkinson’s and Lewy Body Dementia patients. Consistent with reports of anti-parallel β-strands being a defining feature of toxic αS pre-fibrillar intermediates, I1 impacts the viability of neuroblasts and disrupts cell membranes, resulting in increased calcium influx. Our results integrate the occurrence of anti-parallel β-strands as salient features of toxic oligomers with their significant role in the amyloid fibril assembly pathway. These structural insights have implications for the development of therapies and biomarkers.
Integrated optical switches based on Kerr symmetry breaking in microresonators
Yaojing Zhang, Shuangyou Zhang, Alekhya Ghosh, Arghadeep Pal, George N. Ghalanos, Toby Bi, Haochen Yan, Hao Zhang, Yongyong Zhuang, et al.
Photonics Research
13
360-366
(2025)
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With the rapid development of the Internet of Things and big data, integrated optical switches are gaining prominence for applications in on-chip optical computing, optical memories, and optical communications. Here, we propose a novel approach for on-chip optical switches by utilizing the nonlinear optical Kerr effect induced spontaneous symmetry breaking (SSB), which leads to two distinct states of counterpropagating light in ring resonators. This technique is based on our first experimental observation of on-chip symmetry breaking in a high-Q (9.4 × 106) silicon nitride resonator with a measured SSB threshold power of approximately 3.9 mW. We further explore the influence of varying pump powers and frequency detunings on the performance of SSB-induced optical switches. Our work provides insights into the development of new types of photonic data processing devices and provides an innovative approach for the future implementation of on-chip optical memories.
Non-Markovian Feedback for Optimized Quantum Error Correction
Matteo Puviani, Sangkha Borah, Remmy Augusta Menzata Zen, Jan Ollé Aguilera, Florian Marquardt
Physical Review Letters
134
020601
(2025)
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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 (gradient-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 significantly outperforms current strategies and paves the way for more powerful measurement-based QEC protocols.
Dynamic forces shape the survival fate of eliminated cells
Lakshmi Balasubramaniam, Siavash Monfared, Aleksandra Ardaševa, Carine Rosse, Andreas Schoenit, Tien Dang, Chrystelle Maric, Mathieu Hautefeuille, Leyla Kocgozlu, et al.
Tissues eliminate unfit, unwanted or unnecessary cells through cell extrusion, and this can lead to the elimination of both apoptotic and live cells. However, the mechanical signatures that influence the fate of extruding cells remain unknown. Here we show that modified force transmission across adherens junctions inhibits apoptotic cell eliminations. By combining cell experiments with varying levels of E-cadherin junctions and three-dimensional modelling of cell monolayers, we find that these changes not only affect the fate of the extruded cells but also shift extrusion from the apical to the basal side, leading to cell invasion into soft collagen gels. We generalize our findings using xenografts and cysts cultured in matrigel, derived from patients with breast cancer. Our results link intercellular force transmission regulated by cell–cell communication to cell extrusion mechanisms, with potential implications during morphogenesis and invasion of cancer cells.
Quantum Science — a wonderful journey, ultimately empowering Technology
The cytoskeleton is a crucial determinant of mammalian cell structure and function, providing mechanical resilience, supporting the cell membrane and orchestrating essential processes such as cell division and motility. Because of its fundamental role in living cells, developing a reconstituted or artificial cytoskeleton is of major interest. Here we present an approach to construct an artificial cytoskeleton that imparts mechanical support and regulates membrane dynamics. Our system involves amylose-based coacervates stabilized by a terpolymer membrane, with a cytoskeleton formed from polydiacetylene fibrils. The fibrils bundle due to interactions with the positively charged amylose derivative, forming micrometre-sized structures mimicking a cytoskeleton. Given the intricate interplay between cellular structure and function, the design and integration of this artificial cytoskeleton represent a crucial advancement, paving the way for the development of artificial cell platforms exhibiting enhanced life-like behaviour.
Thermally Assisted Microfluidics to Produce Chemically Equivalent Microgels with Tunable Network Morphologies
Dirk Rommel, Bernhard Häßel, Philip Pietryszek, Matthias Mork, Oliver Jung, Meike Emondts, Nikita Norkin, Iris Christine Doolaar, Yonka Kittel, et al.
Angewandte Chemie, International Edition in English
64(1)
(2025)
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Although micron-sized microgels have become important building blocks in regenerative materials, offering decisive interactions with living matter, their chemical composition mostly significantly varies when their network morphology is tuned. Since cell behavior is simultaneously affected by the physical, chemical, and structural properties of the gel network, microgels with variable morphology but chemical equivalence are of interest. This work describes a new method to produce thermoresponsive microgels with defined mechanical properties, surface morphologies, and volume phase transition temperatures. A wide variety of microgels is synthesized by crosslinking monomers or star polymers at different temperatures using thermally assisted microfluidics. The diversification of microgels with different network structures and morphologies but of chemical equivalence offers a new platform of microgel building blocks with the ability to undergo phase transition at physiological temperatures. The method holds high potential to create soft and dynamic materials while maintaining the chemical composition for a wide variety of applications in biomedicine.
Preparing Schrödinger cat states in a microwave cavity using a neural network
Hector Hutin, Pavlo Bilous, Chengzhi Ye, Sepideh Abdollahi, Loris Cros, Tom Dvir, Tirth Shah, Yonatan Cohen, Audrey Bienfait, et al.
Scaling up quantum computing devices requires solving ever more complex quantum control tasks. Machine learning has been proposed as a promising approach to tackle the resulting challenges. However, experimental implementations are still scarce. In this work, we demonstrate experimentally a neural-network-based preparation of Schrödinger cat states in a cavity coupled dispersively to a qubit. We show that it is possible to teach a neural network to output optimized control pulses for a whole family of quantum states. After being trained in simulations, the network takes a description of the target quantum state as input and rapidly produces the pulse shape for the experiment, without any need for time-consuming additional optimization or retraining for different states. Our experimental results demonstrate more generally how deep neural networks and transfer learning can produce efficient simultaneous solutions to a range of quantum control tasks, which will benefit not only state preparation but also parametrized quantum gates.
2024
Higher order transient membrane protein structures
Yuxi Zhang, Hisham Mazal, Venkata Shiva Mandala, Gonzalo Perez-Mitta, Vahid Sandoghdar, Christoph A. Haselwandter, Roderick McKinnon
Proceedings of the National Academy of Sciences of the United States of America
122
e2421275121
(2024)
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This study shows that five membrane proteins—three GPCRs, an ion channel, and an enzyme—form self-clusters under natural expression levels in a cardiac-derived cell line. The cluster size distributions imply that these proteins self-oligomerize reversibly through weak interactions. When the concentration of the proteins is increased through heterologous expression, the cluster size distributions approach a critical distribution at which point a phase transition occurs, yielding larger bulk phase clusters. A thermodynamic model like that explaining micellization of amphiphiles and lipid membrane formation accounts for this behavior. We propose that many membrane proteins exist as oligomers that form through weak interactions, which we call higher-order transient structures (HOTS). The key characteristics of HOTS are transience, molecular specificity, and a monotonically decreasing size distribution that may become critical at high concentrations. Because molecular specificity invokes self-recognition through protein sequence and structure, we propose that HOTS are genetically encoded supramolecular units.
Cavity-mediated hybridization of several molecules in the strong coupling regime
Jahangir Nobakht, André Pscherer, Jan Renger, Stephan Götzinger, Vahid Sandoghdar
Molecular complexes are held together via a variety of bonds, but they all share the common feature that their individual entities are in contact. In this work, we introduce and demonstrate the concept of a molecular optical bond, resulting from the far-field electromagnetic coupling of several molecules via a shared mode of an optical microcavity. We discuss a collective enhancement of the vacuum Rabi splitting and study super- and sub-radiant states that arise from the cavity-mediated coupling both in the resonant and dispersive regimes. Moreover, we demonstrate a two-photon transition that emerges between the ground and excited states of the new optical compound. Our experimental data are in excellent agreement with the predictions of the Tavis-Cummings Hamiltonian and open the door to the realization of hybrid light-matter materials.
Intensity correlations in the Wigner representation
Mojdeh S. Najafabadi, Luis Sanchez-Soto, Kun Huang, Julien Laurat, Hanna Le Jeannic, Gerd Leuchs
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
382
20230337
(2024)
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We derive a compact expression for the second-order correlation function g(2)(0) of a quantum state in terms of its Wigner function, thereby establishing a direct link between g(2)(0) and the state’s shape in phase space. We conduct an experiment that simultaneously measures g(2)(0) through direct photocounting and reconstructs the Wigner function via homodyne tomography. The results confirm our theoretical predictions.
An operational distinction between quantum entanglement and classical non-separability
Natalia Korolkova, Luis Sanchez-Soto, Gerd Leuchs
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
382
20230342
(2024)
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Quantum entanglement describes superposition states in multi-dimensional systems—at least two partite—which cannot be factorized and are thus non-separable. Non-separable states also exist in classical theories involving vector spaces. In both cases, it is possible to violate a Bell-like inequality. This has led to controversial discussions, which we resolve by identifying an operational distinction between the classical and quantum cases.
Robust quantum metrology with random Majorana constellations
Aaron Goldberg, Jose Luis Romero Hervas, Angel S Sanz, Andrei B Klimov, Jaroslav Rehacek, Zdenek Hradil, Matias Eriksson, Robert Fickler, Gerd Leuchs, et al.
Quantum Science and Technology
10
015053
(2024)
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Even the most classical states are still governed by quantum theory. A number of physical systems can be described by their Majorana constellations of points on the surface of a sphere, where concentrated constellations and highly symmetric distributions correspond to the least and most quantum states, respectively. If these points are chosen randomly, how quantum will the resultant state be, on average? We explore this simple conceptual question in detail, investigating the quantum properties of the resulting random states. We find these states to be far from the norm, even in the large-number-of-particles limit, where classical intuition often replaces quantum properties, making random Majorana constellations peculiar and intriguing. Moreover, we study their usefulness in the context of rotation sensing and find numerical evidence of their robustness against dephasing and particle loss. We realize these states experimentally using light's orbital angular momentum degree of freedom and implement arbitrary unitaries with a multiplane light conversion setup to demonstrate the rotation sensing. Our findings open up new possibilities for quantum-enhanced metrology.
Cryogenic light microscopy with Ångstrom precision deciphers structural conformations of PIEZO1
Hisham Mazal, Alexandra Schambony, Vahid Sandoghdar
BioRxiv 10.1101/2024.12.22.629944
(2024)
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Despite the impressive progress in molecular biochemistry and biophysics, many questions regarding the conformational states of large (transmembrane) protein complexes persist. In the case of the PIEZO protein, investigations by cryogenic electron microscopy (Cryo-EM) and atomic force microscopy (AFM) have established a symmetric trimer structure with three long-bladed domains in a propeller-like configuration. A transition of PIEZO protein from curved to flat conformation is hypothesized to actuate closed and open channels for the flow of ions. However, conclusive high-resolution data on the molecular organization of PIEZO in its native form are lacking. To address this shortcoming, we exploit single-particle cryogenic light microscopy (spCryo-LM) to decipher the conformational states of the mouse PIEZO1 protein (mPIEZO1) in the cell membrane. Here, we implement a high-vacuum cryogenic shuttle to transfer shock-frozen unroofed cell membranes in and out of a cryostat for super-resolution microscopy at liquid helium temperature. By localizing fluorescent labels placed at the extremities of the three blades with Ångstrom precision, we ascertain three configurations of the protein with radii of 6, 12, and 20 nm as projected onto the membrane plane. Our data suggest that in the smallest configuration, the blades form a nano-dome structure that is more strongly curved than previously observed and predicted by AlphaFold-3. In the largest conformation, we believe the structure must fully unbend in an anticlockwise manner to form a flat extended state. We attribute the 12 nm conformation, the most frequently occupied state, to an intermediate state and discuss our results in the context of the findings from other groups. Combination of spCryo-LM and Cryo-EM measurements together with in situ photothermal stimulation promises to provide quantitative insight into the interplay between structure and function of PIEZO and other biomolecular complexes in their native environments.
Indistinguishable MHz-narrow heralded photon pairs from a whispering gallery resonator
Sheng-Hsuan Huang, Thomas Dirmeier, Golnoush Shafiee, Kaisa Laiho, Dmitry Strekalov, Andrea Aiello, Gerd Leuchs, Christoph Marquardt
Hong-Ou-Mandel interference plays a vital role in many quantum optical applications where indistinguishability of two photons is important. Such photon pairs are commonly generated as the signal and idler in the frequency and polarization-degenerate spontaneous parametric down conversion~(SPDC). To scale this approach to a larger number of photons we demonstrate how two independent signal photons radiated into different spatial modes can be rendered conditionally indistinguishable by a heralding measurement performed on their respective idlers. We use the SPDC in a whispering gallery resonator, which is already proven to be versatile sources of quantum states. Its extreme conversion efficiency allowed us to perform our measurements with only \qty{50}{nW} of in-coupled pump power in each propagation direction. The Hong-Ou-Mandel interference of two counter-propagating signal photons manifested itself in the four-fold coincidence rate, where the two idler photons detection heralds a pair of signal photons with a desired temporal overlap. We achieved the Hong-Ou-Mandel dip contrast of \(74\pm 5\%\). Importantly, the optical bandwidth of all involved photons is of the order of a MHz and is continuously tunable. This, on the one hand, makes it possible to achieve the necessary temporal measurements resolution with standard electronics, and on the other hand, creates a quantum states source compatible with other candidates for qubit implementation, such as optical transitions in solid-state or vaporous systems. We also discuss the possibility of generating photon pairs with similar temporal modes from two different whispering gallery resonators.
Indistinguishable MHz-narrow heralded photon pairs from a whispering gallery resonator
Sheng-Hsuan Huang, Thomas Dirmeier, Golnoush Shafiee, Kaisa Laiho, Dmitry Strekalov, Andrea Aiello, Gerd Leuchs, Christoph Marquardt
Hong-Ou-Mandel interference plays a vital role in many quantum optical applications where indistinguishability of two photons is important. Such photon pairs are commonly generated as the signal and idler in the frequency and polarization-degenerate spontaneous parametric down conversion~(SPDC). To scale this approach to a larger number of photons we demonstrate how two independent signal photons radiated into different spatial modes can be rendered conditionally indistinguishable by a heralding measurement performed on their respective idlers. We use the SPDC in a whispering gallery resonator, which is already proven to be versatile sources of quantum states. Its extreme conversion efficiency allowed us to perform our measurements with only \qty{50}{nW} of in-coupled pump power in each propagation direction. The Hong-Ou-Mandel interference of two counter-propagating signal photons manifested itself in the four-fold coincidence rate, where the two idler photons detection heralds a pair of signal photons with a desired temporal overlap. We achieved the Hong-Ou-Mandel dip contrast of \(74\pm 5\%\). Importantly, the optical bandwidth of all involved photons is of the order of a MHz and is continuously tunable. This, on the one hand, makes it possible to achieve the necessary temporal measurements resolution with standard electronics, and on the other hand, creates a quantum states source compatible with other candidates for qubit implementation, such as optical transitions in solid-state or vaporous systems. We also discuss the possibility of generating photon pairs with similar temporal modes from two different whispering gallery resonators.
Supported Lipid Bilayers as Stochastic Conveyor Belt for Delivery to the Near Field of Nanoscopic Structures
Yazgan Tuna, Vahid Sandoghdar
Journal of Physical Chemistry C
129
495-499
(2024)
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Placement of nanoscopic entities in the optical near field of a structure such as a plasmonic nanoantenna or the aperture of a scanning near-field optical microscopy (SNOM) remains a nontrivial task, which often requires sophisticated nanofabrication techniques. Here, we show that the fluidity and diffusion of lipid molecules in bilayer geometries can be exploited for facile delivery of nano-objects such as organic dye molecules, semiconductor quantum dots, and gold nanoparticles to the near field of well-defined surface structures. We demonstrate this in three different scenarios with substantial plasmonic enhancement of fluorescence.
Combined selective plane illumination microscopy (SPIM) and full-field optical coherence tomography (FF-OCT) for in vivo imaging
Selective plane illumination microscopy (SPIM), also known as light sheet fluorescence microscopy, provides high specificity through fluorescence labeling. However, it lacks complementary structural information from the surrounding context, which is essential for the comprehensive analysis of biological samples. Here, we present a high-resolution, multimodal imaging system that integrates SPIM with full-field optical coherence tomography (FF-OCT), without requiring modifications to the existing SPIM setup. Both SPIM and FF-OCT offer low phototoxicity and intrinsic optical sectioning, making them well-suited for in vivo imaging. Their shared detection path enables seamless and efficient co-registration of fluorescence and structural data. We demonstrate the unctionality of this combined system by performing in vivo imaging of zebrafish larvae.
Rapid Stiffness Mapping in Soft Biologic Tissues With Micrometer Resolution Using Optical Multifrequency Time‐Harmonic Elastography
Jakob Jordan, Noah Jaitner, Tom Meyer, Luca Bramè, Mnar Ghrayeb, Julia Köppke, Oliver Böhm, Stefan Klemmer Chandia, Vasily Zaburdaev, et al.
Rapid mapping of the mechanical properties of soft biological tissues from light microscopy to macroscopic imaging can transform fundamental biophysical research by providing clinical biomarkers to complement in vivo elastography. This work introduces superfast optical multifrequency time-harmonic elastography (OMTHE) to remotely encode surface and subsurface shear wave fields for generating maps of tissue stiffness with unprecedented detail resolution. OMTHE rigorously exploits the space-time propagation characteristics of multifrequency time-harmonic waves to address current limitations of biomechanical imaging and elastography. Key solutions are presented for stimulation, wave decoding, and stiffness reconstruction of shear waves at multiple harmonic frequencies, all tuned to provide consistent stiffness values across resolutions from microns to millimeters. OMTHE's versatility is demonstrated by simulations, phantoms, Bacillus subtilis biofilms, zebrafish embryos and adult zebrafish, reflecting the diversity of biological systems from a mechanics perspective. By zooming in on stiffness details from coarse to finer scales, OMTHE has the potential to advance mechanobiology and offers a way to perform biomechanics-based tissue histology that consistently matches in vivo time-harmonic elastography in patients.
Automated discovery of experimental designs in super-resolution microscopy with XLuminA
Carla Rodríguez Mangues, Sören Arlt, Leonhard Möckl, Mario Krenn
Nature Communications
15
10658
(2024)
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Driven by human ingenuity and creativity, the discovery of super-resolution techniques, which circumvent the classical diffraction limit of light, represent a leap in optical microscopy. However, the vast space encompassing all possible experimental configurations suggests that some powerful concepts and techniques might have not been discovered yet, and might never be with a human-driven direct design approach. Thus, AI-based exploration techniques could provide enormous benefit, by exploring this space in a fast, unbiased way. We introduce XLuminA, an open-source computational framework developed using JAX, a high-performance computing library in Python. XLuminA offers enhanced computational speed enabled by JAX’s accelerated linear algebra compiler (XLA), just-in-time compilation, and its seamlessly integrated automatic vectorization, automatic differentiation capabilities and GPU compatibility. XLuminA demonstrates a speed-up of 4 orders of magnitude compared to well-established numerical optimization methods. We showcase XLuminA’s potential by re-discovering three foundational experiments in advanced microscopy, and identifying an unseen experimental blueprint featuring sub-diffraction imaging capabilities. This work constitutes an important step in AI-driven scientific discovery of new concepts in optics and advanced microscopy.
Ad-hoc hybrid-heterogeneous metropolitan-range quantum key distribution
network
Matthias Goy, Jan Krause, Oemer Bayraktar, Philippe Ancsin, Florian David, Thomas Dirmeier, Nico Doell, Jansen Dwan, Friederike Fohlmeister, et al.
This paper presents the development and implementation of a versatile ad-hoc metropolitan-range Quantum Key Distribution (QKD) network. The approach presented integrates various types of physical channels and QKD protocols, and a mix of trusted and untrusted nodes. Unlike conventional QKD networks that predominantly depend on either fiber-based or free-space optical (FSO) links, the testbed presented amalgamates FSO and fiber-based links, thereby overcoming some inherent limitations. Various network deployment strategies have been considered, including permanent infrastructure and provisional ad-hoc links to eradicate coverage gaps. Furthermore, the ability to rapidly establish a network using portable FSO terminals and to investigate diverse link topologies is demonstrated. The study also showcases the successful establishment of a quantum-secured link to a cloud server.
Simultaneous Discovery of Quantum Error Correction Codes and Encoders with a Noise-Aware Reinforcement Learning Agent
Jan Olle, Remmy Zen, Matteo Puviani, Florian Marquardt
npj Quantum Information
10
126
(2024)
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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.
Frequency conversion in a hydrogen-filled hollow-core fiber using continuous-wave fields
Anica Hamer, Frank Vewinger, Thorsten Peters, Michael Frosz, Simon Stellmer
In large-area quantum networks based on optical fibers, photons are the fundamental carriers of information as so-called flying qubits. They may also serve as the interconnect between different components of a hybrid architecture, which might comprise atomic and solid-state platforms operating at visible or near-infrared wavelengths, as well as optical links in the telecom band. Quantum frequency conversion is the pathway to change the color of a single photon while preserving its quantum state. Currently, nonlinear crystals are utilized for this process. However, their performance is limited by their acceptance bandwidth, tunability, polarization sensitivity, and undesired background emission. A promising alternative is based on stimulated Raman scattering (SRS) in gases. Here, we demonstrate polarization-preserving frequency conversion in a hydrogen-filled antiresonant hollow-core fiber. This approach holds promises for seamless integration into optical fiber networks and interfaces to single emitters. Disparate from related experiments that employ a pulsed pump field, we here take advantage of two coherent continuous-wave pump fields.
Optical characterization of molecular interaction strength in protein condensates
Timon Beck, Lize-Mari van der Linden, Wade M. Borcherds, Kyoohyun Kim, Raimund Schlüßler, Paul Müller, Titus M. Franzmann, Conrad Möckel, Ruchi Goswami, et al.
Molecular Biology of the Cell
35(12)
(2024)
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Biomolecular condensates have been identified as a ubiquitous means of intracellular organization, exhibiting very diverse material properties. However, techniques to characterize these material properties and their underlying molecular interactions are scarce. Here, we introduce two optical techniques—Brillouin microscopy and quantitative phase imaging (QPI)—to address this scarcity. We establish Brillouin shift and linewidth as measures for average molecular interaction and dissipation strength, respectively, and we used QPI to obtain the protein concentration within the condensates. We monitored the response of condensates formed by fused in sarcoma (FUS) and by the low-complexity domain of hnRNPA1 (A1-LCD) to altering temperature and ion concentration. Conditions favoring phase separation increased Brillouin shift, linewidth, and protein concentration. In comparison to solidification by chemical cross-linking, the ion-dependent aging of FUS condensates had a small effect on the molecular interaction strength inside. Finally, we investigated how sequence variations of A1-LCD, that change the driving force for phase separation, alter the physical properties of the respective condensates. Our results provide a new experimental perspective on the material properties of protein condensates. Robust and quantitative experimental approaches such as the presented ones will be crucial for understanding how the physical properties of biological condensates determine their function and dysfunction.
Entangling Independent Particles by Path Identity
Kai Wang, Zhaohua Hou, Kaiyi Qian, Leizhen Chen, Mario Krenn, Shining Zhu, Xiao-Song Ma
Physical Review Letters
133
233601
(2024)
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Quantum entanglement—correlations of particles that are stronger than any classical analog—is the basis for research on the foundations of quantum mechanics and for practical applications such as quantum networks. Traditionally, entanglement is achieved through local interactions or via entanglement swapping, where entanglement at a distance is generated through previously established entanglement and Bell-state measurements. However, the precise requirements enabling the generation of quantum entanglement without traditional local interactions remain less explored. Here, we demonstrate that independent particles can be entangled without the need for direct interaction, prior established entanglement, or Bell-state measurements, by exploiting the indistinguishability of the origins of photon pairs. Our demonstrations challenge the long-standing belief that the prior generation and measurement of entanglement are necessary prerequisites for generating entanglement between independent particles that do not share a common past. In addition to its foundational interest, we show that this technique might lower the resource requirements in quantum networks, by reducing the complexity of photon sources and the overhead photon numbers.
Quantum feedback control with a transformer neural network architecture
Pranav Vaidhyanathan, Florian Marquardt, Mark T. Mitchison, Natalia Ares
Attention-based neural networks such as transformers have revolutionized various fields such as natural language processing, genomics, and vision. Here, we demonstrate the use of transformers for quantum feedback control through a supervised learning approach. In particular, due to the transformer's ability to capture long-range temporal correlations and training efficiency, we show that it can surpass some of the limitations of previous control approaches, e.g.those based on recurrent neural networks trained using a similar approach or reinforcement learning. We numerically show, for the example of state stabilization of a two-level system, that our bespoke transformer architecture can achieve unit fidelity to a target state in a short time even in the presence of inefficient measurement and Hamiltonian perturbations that were not included in the training set. We also demonstrate that this approach generalizes well to the control of non-Markovian systems. Our approach can be used for quantum error correction, fast control of quantum states in the presence of colored noise, as well as real-time tuning, and characterization of quantum devices.
Mechanical stresses govern myoblast fusion and myotube growth
Yoann Le Toquin, Sushil Dubey, Aleksandra Ardaševa, Lakshmi Balasubramaniam, Emilie Delaune, Valérie Morin, Amin Doostmohammadi, Christophe Marcelle, Benoît Ladoux
Myoblast fusion into myotubes is critical for muscle formation, growth and repair. While the cellular and molecular mechanisms regulating myoblast fusion are increasingly understood, the role of biomechanics in this process remains largely unexplored. Here, we reveal that a dynamic feedback loop between evolving cell mechanics and cell-generated stresses shape the fusion of primary myoblasts in vitro. Applying principles from active nematics, we show that myoblast and myotube patterning follows physical rules similar to liquid crystal organization. Remarkably, fusion predominantly occurs at comet-shaped topological defects in cellular alignment, which we identified as regions of high compressive stress. We further find that this stress-driven organization depends on extracellular matrix (ECM) deposition, which mirrors the nematic order of the cell population. Our integrated data, supported by active nematics-based mathematical modeling, accurately predict self-organization patterns and mechanical stresses that regulate myoblast fusion. By revealing the essential role of biomechanics and ECM interplay in myogenesis, this work establishes a foundational framework for understanding biomechanical principles in morphogenesis.
Quantum Pair Generation in Nonlinear Metasurfaces with Mixed and Pure Photon Polarizations
Jiho Noh, José Tomás Santiago-Cruz, Vitaliy Sultanov, Chloe F. Doiron, Sylvain D. Gennaro, Maria Chekhova, Igal Brener
Metasurfaces are highly effective at manipulating classical light in the linear regime; however, effectively controlling the polarization of nonclassical light generated from nonlinear resonant metasurfaces remains a challenge. Here, we present a solution by achieving polarization engineering of frequency-nondegenerate biphotons emitted via spontaneous parametric down-conversion in GaAs metasurfaces, utilizing quasi-bound states in the continuum (qBIC) resonances to enhance biphoton generation. Through comprehensive polarization tomography, we demonstrate that the emitted photons’ polarization directly reflects the qBIC mode’s far-field properties. Furthermore, we show that both the type of qBIC mode and the symmetry of the meta-atoms can be tailored to control each single-photon polarization state, and that the subsequent two-photon polarization states are nearly separable, offering potential applications in the heralded generation of single photons with adjustable polarization. This work provides a significant step toward utilizing metasurfaces to generate quantum light and engineer their polarization, a critical aspect for future quantum technologies.
Polarization squeezing in chalcogenide fibers
Alexey V. Andrianov, Alexey N. Romanov, Arseny A. Sorokin, Elena A. Anashkina, Nikolay Kalinin, Thomas Dirmeier, Luis Sanchez-Soto, Gerd Leuchs
We experimentally demonstrate the generation of polarization-squeezed light in a short piece of solid-core chalcogenide (ChG) (As2S3) fiber via the Kerr effect for femtosecond pulses at 1.56 μm. Directly measured squeezing of −2.8 dB is obtained in a setup without active stabilization.<br>Numerical simulations are in good agreement with the experimental results and indicate that the measured squeezing in our setup is mainly limited by the losses in the detection system rather than by the fiber properties.
Consensus Statement on Brillouin Light Scattering Microscopy of Biological Materials
Pierre Bouvet, Carlo Bevilacqua, Yogeshwari Ambekar, Giuseppe Antonacci, Joshua Au, Silvia Caponi, Sophie Chagnon-Lessard, Juergen Czarske, Thomas Dehoux, et al.
Brillouin Light Scattering (BLS) spectroscopy is a non-invasive, non-contact, label-free optical technique that can provide information on the mechanical properties of a material on the sub-micron scale. Over the last decade it has seen increased applications in the life sciences, driven by the observed significance of mechanical properties in biological processes, the realization of more sensitive BLS spectrometers and its extension to an imaging modality. As with other spectroscopic techniques, BLS measurements not only detect signals characteristic of the investigated sample, but also of the experimental apparatus, and can be significantly affected by measurement conditions. The aim of this consensus statement is to improve the comparability of BLS studies by providing reporting recommendations for the measured parameters and detailing common artifacts. Given that most BLS studies of biological matter are still at proof-of-concept stages and use different--often self-built--spectrometers, a consensus statement is particularly timely to assure unified advancement.
Exceptional Points and Stability in Nonlinear Models of Population Dynamics having PT symmetry
Nonlinearity and non-Hermiticity, for example due to environmental gain-loss processes, are a common occurrence throughout numerous areas of science and lie at the root of many remarkable phenomena. For the latter, parity-time-reflection PT symmetry has played an eminent role in understanding exceptional-point structures and phase transitions in these systems. Yet their interplay has remained by-and-large unexplored. We analyze models governed by the replicator equation of evolutionary game theory and related Lotka-Volterra systems of population dynamics. These are foundational nonlinear models that find widespread application and offer a broad platform for non-Hermitian theory beyond physics. In this context we study the emergence of exceptional points in two cases: (a) when the governing symmetry properties are tied to global properties of the models, and, in contrast, (b) when these symmetries emerge locally around stationary states - in which case the connection between the linear non-Hermitian model and an underlying nonlinear system becomes tenuous. We outline further that when the relevant symmetries are related to global properties, the location of exceptional points in the linearization around coexistence equilibria coincides with abrupt global changes in the stability of the nonlinear dynamics. Exceptional points may thus offer a new local characteristic for the understanding of these systems. Tri-trophic models of population ecology serve as test cases for higher-dimensional systems.
Robustly packaged lithium niobate resonator-based temperature sensor
Liu Yang, Yongyong Zhuang, Yifan Zhang, Haochen Yan, Hao Zhang, Yaojing Zhang, Shuangyou Zhang, Xin Liu, Qingyuan Hu, et al.
Whispering gallery mode (WGM) resonators with high optical quality factor (Q) are sensitive to environment changes and are used in various sensing applications. We have developed a high-precision temperature sensor using a compactly packaged lithium niobate WGM resonator. This sensor offers a sensitivity of 34.38 pm °C−1 and a high resolution of up to °C. It is portable with high Q, making it suitable for using outside the laboratory. The device is also resilient to changes in humidity, enhancing its practicality.
Perfluorocarbons: a material platform for tunable nonlinear frequency conversion in liquid filled suspended core fibers
Johannes Hofmann, Wenqin Huang, Torsten Wieduwilt, Henrik Schneidewind, Michael H. Frosz, Markus A. Schmidt
Optical Materials Express
14
2898-2911
(2024)
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This study investigates supercontinuum generation in suspended core fibers filled with perfluorocarbons, highlighting their potential for ultrafast nonlinear frequency conversion. Spectroscopic absorption and refractive index dispersions are analyzed for three perfluorocarbons in the visible and near-infrared. Experiments show that the insertion of these liquids into suspended core fibers changes the dispersion landscape, enabling broadband soliton-based supercontinuum generation from 0.6 µm to 2.4 µm due to the creation of a confined domain of anomalous dispersion in the telecom range. In addition, temperature-dependent output spectrum modulation is demonstrated, highlighting the utility of the platform in photonic applications such as spectroscopy, sensing, and microscopy.
Optoacoustic Entanglement in a Continuous Brillouin-Active Solid State System
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.
180 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
Applied Physics Letters
125
204101
(2024)
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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.
Discovering emergent connections in quantum physics research via dynamic word embeddings
Felix Frohnert, Xuemei Gu, Mario Krenn, Evert van Nieuwenburg
As the field of quantum physics evolves, researchers naturally form subgroups focusing on specialized problems. While this encourages in-depth exploration,it can limit the exchange of ideas across structurally similar problems in different subfields. To encourage cross-talk among these different specialized areas, data-driven approaches using machine learning have recently shown promise to uncover meaningful connections between research concepts, promoting cross-disciplinary innovation. Current state-of-the-art approaches represent concepts using knowledge graphs and frame the task as a link prediction problem, where connections between concepts are explicitly modeled. In this work, we introduce a novel approach based on dynamic word embeddings for concept combination prediction. Unlike knowledge graphs, our method captures implicit relationships between concepts, can be learned in a fully unsupervised manner, and encodes a broader spectrum of information. We demonstrate that this representation enables accurate predictions about the co-occurrence of concepts within research abstracts over time. To validate the effectiveness of our approach, we provide a comprehensive benchmark against existing methods and offer insights into the interpretability of these embeddings, particularly in the context of quantum physics research. Our findings suggest that this representation offers a more flexible and informative way of modeling conceptual relationships in scientific literature.
Tailored Bisacylphosphane Oxides for Precise Induction of Oxidative Stress-Mediated Cell Death in Biological Systems
Karim Almahayni, Jana Bachir Salvador, Riccardo Conti, Anna Widera, Malte Spiekermann, Daniel Wehner, Hansjörg Grützmacher, Leonhard Möckl
Precise cell elimination within intricate cellular populations is hampered by issues arising from the multifaceted biological properties of cells and the expansive reactivity of chemical agents. Current chemical platforms are often limited by their complexity, toxicity, and poor physical/chemical properties. Here, we report on the synthesis of a structurally versatile library of chemically tunable bisacylphosphane oxides (BAPOs), which harnesses the spatiotemporal precision of light delivery, thereby establishing a universal strategy for on-demand, precise cellular ablation in vitro and in vivo.
S96 Circulating neutrophils in idiopathic pulmonary fibrosis have a distinct biomechanical phenotype of systemic activation that correlates with disease severity
Katherina Lodge, Sara Nakanashi, Leda Yazbeck, Jochen Guck, Philip L. Molyneaux , Andrew S. Cowburn
Background Idiopathic Pulmonary Fibrosis (IPF) is a chronic interstitial lung disease associated with impaired gas transfer and systemic hypoxia. Elevated peripheral neutrophil counts correlate with increased morbidity and mortality in IPF. Real-Time Deformability Cytometry (RT-DC) is a novel, sensitive high-throughput approach that measures quantitative biomechanical parameters of single cells with minimal manipulation and maintenance of physiological normoxia, thus enabling indirect determination of basal cellular activity. We hypothesized that biomechanical profiling can identify phenotypic diversity in patients with IPF.
Linear and nonlinear coupling of light in twin-resonators with Kerr nonlinearity
Arghadeep Pal, Alekhya Ghosh, Shuangyou Zhang, Lewis Hill, Haochen Yan, Hao Zhang, Toby Bi, Abdullah Alabbadi, Pascal Del'Haye
Photonics Research
12(11)
2733-2740
(2024)
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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 nonlinear 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.
The non-Hermitian (NH) skin effect is a truly NH feature, which manifests itself as an accumulation of states, known as skin states, on the boundaries of a system. In this perspective, we discuss several aspects of the NH skin effect focusing on the most interesting facets of this phenomenon. Non-normality and non-reciprocity are reviewed as necessary requirements to see the NH skin effect. We further discuss the NH skin effect as a topological effect that can be seen as a manifestation of a truly NH bulk-boundary correspondence, and show how topological boundary states can be distinguished from skin states. As most theoretical work has focused on studying the NH skin effect in the<br>one-dimensional single-particle picture, recent developments of studying this effect in higher dimensions as well as in the many-body case are also highlighted. Lastly, experimental realizations and applications of the NH skin effect are reviewed.
During morphogenesis, a key process of embryonic development, cells undergo massive rearrangements to give rise to tissue shapes and ultimately organ systems. Shape changes of tissues are naturally driven by forces arising from mechanical interactions between cells and their environment. These forces generate cell movements, mechanical stresses and strains at the tissue level. Abnormalities in these stresses can lead to malformations and developmental disorders, and in mature organisms, cancer can be considered an example of pathological tissue morphogenesis. Knowledge about the forces and stresses generated by cells and tissues is crucial to fully understand embryonic development and related pathological processes. Now, writing in Nature Materials, Maniou et al. 1 present a method to quantify tissue-level morphogenetic forces based on the deformation of three-dimensional soft force sensors …
Modelling spectra of hot alkali vapour in the saturation regime
Daniel Häupl, Clare R Higgins, Danielle Pizzey, Jack D Briscoe, Steven A Wrathmall, Ifan G Hughes, Robert Löw, Nicolas Y. Joly
Laser spectroscopy of hot atomic vapours has been studied extensively. Theoretical models that predict the absolute value of the electric susceptibility are crucial for optimising the design of photonic devices that use hot vapours, and for extracting parameters, such as external fields, when these devices are used as sensors. To date, most of the models developed have been restricted to the weak-probe regime. However, fulfilling the weak-probe power constraint may not always be easy, desired or necessary. Here we present a model for simulating the spectra of alkali-metal vapours for a variety of experimental parameters, most distinctly at intensities beyond weak laser fields. The model incorporates optical pumping effects and transit-time broadening. We test the performance of the model by performing spectroscopy of Rb-87 in a magnetic field of 0.6 T, where isolated atomic resonances can be addressed. We find very good agreement between the model and data for three <br>different beam diameters and a variation of intensity of over five orders of magnitude. The non-overlapping absorption lines allow us to differentiate the saturation behaviour of open and closed transitions. While our model was only experimentally verified for the D2 line of rubidium, the software is also capable of simulating spectra of rubidium, sodium, potassium and caesium over both D lines.<br>
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.
Transport in cellular aggregates described by fluctuating hydrodynamics
Subhadip Chakraborti, Vasily Zaburdaev
Physical Review Research
6
043064
(2024)
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Biological functionality of cellular aggregates is largely influenced by the activity and displacements of individual constituent cells. From a theoretical perspective this activity can be characterized by hydrodynamic transport coefficients of diffusivity and conductivity. Motivated by the clustering dynamics of bacterial microcolonies we propose a model of active multicellular aggregates and use recently developed macroscopic fluctuation theory to derive a fluctuating hydrodynamics for this model system. Both semianalytic theory and microscopic simulations show that the hydrodynamic transport coefficients are affected by nonequilibrium microscopic parameters and significantly decrease inside of the clusters. We further find that the Einstein relation connecting the transport coefficients and fluctuations breaks down in the parameter regime where the detailed balance is not satisfied. This study offers valuable tools for experimental investigation of hydrodynamic transport in other systems of cellular aggregates such as tumor spheroids and organoids.
Topological Order in the Spectral Riemann Surfaces of Non-Hermitian Systems
We show topologically ordered states in the complex-valued spectra of non-Hermitian systems. These arise when the distinctive exceptional points in the energy Riemann surfaces of such models are annihilated after threading them across the boundary of the Brillouin zone. This process results in a non-trivially closed branch cut that can be identified with a Fermi arc. Building on an analogy to Kitaev's toric code, these cut lines form non-contractible loops, which parallel the defect lines of the toric-code ground states. Their presence or absence establishes topological order for fully non-degenerate non-Hermitian systems. Excitations above these ground-state analogs are characterized by the occurrence of additional exceptional points. We illustrate the characteristics of the topologically protected states in a non-Hermitian two-band model and provide an outlook toward experimental realizations in metasurfaces and single-photon interferometry.
Testing local realistic hidden-variable theories without inequalities
Many of the tests of local realistic hidden-variable theories against quantum mechanics are based on inequalities such as Bell's inequality and Clauser Horne, Shimony, and Holt's inequality. In this work we present a simple alternative test which does not involve inequalities, but direct comparison between correlation functions. The main advantage of this test is that it does not require measuring incompatible observables separately and simultaneously. This implies that our result, differently from traditional inequalities, does not involve counterfactual reasoning.
Scale-free flocking and giant fluctuations in epithelial active solids
The collective motion of epithelial cells is a fundamental biological process which plays a significant role in embryogenesis, wound healing and tumor metastasis. While it has been broadly investigated for over a decade both in vivo and in vitro, large scale coherent flocking phases remain underexplored and have so far been mostly described as fluid. In this work, we report a mode of large-scale collective motion for different epithelial cell types in vitro with distinctive new features. By tracking individual cells, we show that cells move over long time scales coherently not as a fluid, but as a polar elastic solid with negligible cell rearrangements. Our analysis reveals that this solid flocking phase exhibits signatures of long-range polar order, unprecedented in cellular systems, with scale-free correlations, anomalously large density fluctuations, and shear waves. Based on a general theory of active polar solids, we argue that these features result from massless Goldstone modes, which, in contrast to polar fluids where they are generic, require the decoupling of global rotations of the polarity and in-plane elastic deformations in polar solids. We theoretically show and consistently observe in experiments that the fluctuations of elastic deformations diverge for large system size in such polar active solid phases, leading eventually to rupture and thus potentially loss of tissue integrity at large scales.
Long-Range Three-Dimensional Tracking of Nanoparticles Using Interferometric Scattering Microscopy
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 measurement and analysis strategy for three-dimensional tracking of nanoparticles at high speed and with nanometer precision. After discussing the principle of our approach using synthetic data, we showcase the performance of the method by tracking gold nanoparticles with diameters ranging from 10 to 80 nm in water, demonstrating an axial tracking range from 4 μm for the smallest particles up to over 30 μm for the larger ones. We point out the limitations and robustness of our system across various noise levels and discuss its promise for applications in cell biology and material science, where the three-dimensional motion of nanoparticles in complex media is of interest.
Near-petahertz fieldoscopy of liquid
Anchit Srivastava, Andreas Herbst, Mahdi M. Bidhendi, Max Kieker, Francesco Tani, Hanieh Fattahi
Measuring transient optical fields is pivotal not only for understanding ultrafast phenomena but also for the quantitative detection of various molecular species in a sample. Here we demonstrate near-petahertz electric field detection of a few femtosecond pulses with 200 attosecond temporal resolution and subfemtojoule detection sensitivity. 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 μmol 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.
High-Speed Coherent Photonic Random-Access Memory in Long-Lasting Sound Waves
In recent years, remarkable advances in photonic computing have highlighted the need for photonic memory, particularly high-speed and coherent random-access memory. Addressing the ongoing challenge of implementing photonic memories is required to fully harness the potential of photonic computing. A photonic-phononic memory based on stimulated Brillouin scattering is a possible solution, as it coherently transfers optical information into sound waves at high-speed. Such an optoacoustic memory has shown great potential as it fulfills key requirements for high-performance optical random-access memory due to its coherence, on-chip compatibility, frequency selectivity, and high bandwidth. However, the storage time has so far been limited to a few nanoseconds due to the nanosecond decay of the acoustic wave. In this work, we experimentally enhance the intrinsic storage time of an optoacoustic memory by more than 1 order of magnitude and coherently retrieve optical information after a storage time of 123 ns. This is achieved by employing the optoacoustic memory in a highly nonlinear fiber at 4.2 K, increasing the intrinsic phonon lifetime by a factor of 6. We demonstrate the capability of our scheme by measuring the initial and readout optical data pulses with a direct and double homodyne detection scheme. Finally, we analyze the dynamics of the optoacoustic memory at different cryogenic temperatures in the range of 4.2–20 K and compare the findings to continuous wave measurements. The extended storage time is beneficial not only for photonic computing but also for Brillouin applications that require long phonon lifetimes, such as optoacoustic filters, true-time delay networks, and synthesizers in microwave photonics.
Exploring the role of polarization in fiber-based quantum sources
Optical fibers constitute an attractive platform for the realization of nonlinear and quantum optics processes. Here we show, through theoretical considerations, how polarization effects of both third-order parametric down-conversion and four-wave-mixing in optical fibers may be exploited to enhance detection schemes. We apply our general framework specifically to the case of tapered fibers for photon triplet generation, a long-standing goal within quantum optics, and obtain explicit expectation values for its efficiency. A quantitative investigation of four-wave-mixing in a microstructured solid-core fiber provides significant consequences for the role of polarization in experimental design.
Microglia are essential for tissue contraction in wound closure after brain injury in zebrafish larvae
Francois El-Daher, Stephen J. Enos, Louisa K. Drake, Daniel Wehner, Markus Westphal, Nicola J. Porter, Catherine G. Becker, Thomas Becker
Life science alliance
8(1)
e202403052
(2024)
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Wound closure after brain injury is crucial for tissue restoration but remains poorly understood at the tissue level. We investigated this process using in vivo observations of larval zebrafish brain injury. Our findings show that wound closure occurs within the first 24 h through global tissue contraction, as evidenced by live-imaging and drug inhibition studies. Microglia accumulate at the wound site before closure, and computational models suggest that their physical traction could drive this process. Depleting microglia genetically or pharmacologically impairs tissue repair. At the cellular level, live imaging reveals centripetal deformation of astrocytic processes contacted by migrating microglia. Laser severing of these contacts causes rapid retraction of microglial processes and slower retraction of astrocytic processes, indicating tension. Disrupting the lcp1 gene, which encodes the F-actin–stabilising protein L-plastin, in microglia results in failed wound closure. These findings support a mechanical role of microglia in wound contraction and suggest that targeting microglial mechanics could offer new strategies for treating traumatic brain injury.
Composable free-space continuous-variable quantum key distribution using discrete modulation
Kevin Jaksch, Thomas Dirmeier, Yannick Weiser, Stefan Richter, Oemer Bayraktar, Bastian Hacker, Conrad Rösler, Imran Khan, Stefan Petscharning, et al.
Continuous-variable (CV) quantum key distribution (QKD) allows for quantum secure communication with the benefit of being close to existing classical coherent communication. In recent years, CV QKD protocols using a discrete number of displaced coherent states have been studied intensively, as the modulation can be directly implemented with real devices with a finite digital resolution. However, the experimental demonstrations until now only calculated key rates in the asymptotic regime. To be used in cryptographic applications, a QKD system has to generate keys with composable security in the finite-size regime. In this paper, we present a CV QKD system using discrete modulation that is especially designed for urban atmospheric channels. For this, we use polarization encoding to cope with the turbulent but non-birefringent atmosphere. This will allow to expand CV QKD networks beyond the existing fiber backbone. In a first laboratory demonstration, we implemented a novel type of security proof allowing to calculate composable finite-size key rates against i.i.d. collective attacks without any Gaussian assumptions. We applied the full QKD protocol including a QRNG, error correction and privacy amplification to extract secret keys. In particular, we studied the impact of frame errors on the actual key generation.
Composable free-space continuous-variable quantum key distribution using
discrete modulation
Kevin Jaksch, Thomas Dirmeier, Yannick Weiser, Stefan Richter, Oemer Bayraktar, Bastian Hacker, Conrad Rösler, Imran Khan, Stefan Petscharning, et al.
Continuous-variable (CV) quantum key distribution (QKD) allows for quantum secure communication with the benefit of being close to existing classical coherent communication. In recent years, CV QKD protocols using a discrete number of displaced coherent states have been studied intensively, as the modulation can be directly implemented with real devices with a finite digital resolution. However, the experimental demonstrations until now only calculated key rates in the asymptotic regime. To be used in cryptographic applications, a QKD system has to generate keys with composable security in the finite-size regime. In this paper, we present a CV QKD system using discrete modulation that is especially designed for urban atmospheric channels. For this, we use polarization encoding to cope with the turbulent but non-birefringent atmosphere. This will allow to expand CV QKD networks beyond the existing fiber backbone. In a first laboratory demonstration, we implemented a novel type of security proof allowing to calculate composable finite-size key rates against i.i.d. collective attacks without any Gaussian assumptions. We applied the full QKD protocol including a QRNG, error correction and privacy amplification to extract secret keys. In particular, we studied the impact of frame errors on the actual key generation.
Squeezing via self-induced transparency in mercury-filled photonic crystal fibers
M. S. Najafabadi, J. F. Corney, L. L. Sanchez-Soto, N. Y. Joly, G. Leuchs
We investigate the squeezing of ultrashort pulses using self-induced transparency in a mercury-filled hollow-core photonic crystal fiber. Our focus is on quadrature squeezing at low mercury vapor pressures, with atoms near resonance on the transition. We vary the atomic density, thus the gas pressure (from 2.72 to 15.7bar), by adjusting the temperature (from 273~K to 303 ~K). Our results show that achieving squeezing at room temperature, considering both fermionic and bosonic mercury isotopes, requires ultrashort femtosecond pulses. We also determine the optimal detection length for squeezing at different pressures and temperatures.
Brillouin-based storage of QPSK signals with fully tunable phase retrieval
Olivia Saffer, Jesús Humberto Marines Cabello, Steven Becker, Andreas Geilen, Birgit Stiller
Photonic memory is an important building block to delay, route and buffer optical information, for instance in optical interconnects or for recurrent optical signal processing. Photonic-phononic memory based on stimulated Brillouin-Mandelstam scattering (SBS) has been demonstrated as a coherent optical storage approach with broad bandwidth, frequency selectivity and intrinsic nonreciprocity. Here, we experimentally demonstrated the storage of quadrature-phase encoded data at room temperature and at cryogenic temperatures. We store and retrieve the 2-bit states {00,01,10,11} encoded as optical pulses with the phases {0,pi/2,pi,3pi/2} - a quadrature phase shift keying (QPSK) signal. The 2-bit signals are retrieved from the acoustic domain with a global phase rotation of π, which is inherent in the process due to SBS. We also demonstrate full phase control over the retrieved data based on two different handles: by detuning slightly from the SBS resonance, or by changing the storage time in the memory scheme we can cover the full range [0,2pi). At a cryogenic temperature of 3.9 K, we have increased readout efficiency as well as gained access to longer storage times, which results in a detectable signal at 140 ns. All in all, the work sets the cornerstone for optoacoustic memory schemes with phase-encoded data
Prospects of phase-adaptive cooling of levitated magnetic particles in a hollow-core photonic-crystal fibre
P. Kumar, F. G. Jimenez, S. Chakraborty, G. K. L. Wong, N. Y. Joly, C. Genes
We analyze the feasibility of cooling of classical motion of a micro- to nano-sized magnetic particle, levitated inside a hollow-core photonic crystal fiber. The cooling action is implemented by means of controlling the phase of one of the counter-propagating fiber guided waves. Direct imaging of the particle's position, followed by the subsequent updating of the control laser's phase leads to Stokes type of cooling force. We provide estimates of cooling efficiency and final achievable temperature, taking into account thermal and detection noise sources. Our results bring forward an important step towards using trapped micro-magnets in sensing, testing the fundamental physics and preparing the quantum states of magnetization.
High-harmonic generation by a bright squeezed vacuum
Andrei Rasputnyi, Zhaopin Chen, Michael Birk, Oren Cohen, Ido Kaminer, Michael Krüger, Denis Seletskiy, Maria Chekhova, Francesco Tani
High-harmonic generation has been driving the development of attosecond science and sources. More recently, high-harmonic generation in solids has been adopted by other communities as a method to study material properties. However, so far high-harmonic generation has only been driven by classical light, despite theoretical proposals to do so with quantum states of light. Here we observe non-perturbative high-harmonic generation in solids driven by a macroscopic quantum state of light, a bright squeezed vacuum, which we generate in a single spatiotemporal mode. The process driven by a bright squeezed vacuum is considerably more efficient in the generation of high harmonics than classical light of the same mean intensity. Due to its broad photon-number distribution, covering states from 0 to 2 × 10 13 photons per pulse, and strong subcycle electric field fluctuations, a bright squeezed vacuum gives access to free carrier dynamics within a much broader range of peak intensities than accessible with classical light.
Advances in quantum imaging
Hugo Defienne, Warwick P. Bowen, Maria Chekhova, Gabriela Barreto Lemos, Dan Oron, Sven Ramelow, Nicolas Treps, Daniele Faccio
Modern imaging technologies are widely based on classical principles of light or electromagnetic wave propagation. They can be remarkably sophisticated, with recent successes ranging from single-molecule microscopy to imaging far-distant galaxies. However, new imaging technologies based on quantum principles are gradually emerging. They can either surpass classical approaches or provide novel imaging capabilities that would not otherwise be possible. Here we provide an overview of the most recently developed quantum imaging systems, highlighting the nonclassical properties of sources, such as bright squeezed light, entangled photons and single-photon emitters that enable their functionality. We outline potential upcoming trends and the associated challenges, all driven by a central enquiry, which is to understand whether quantum light can make visible the invisible.
Uniaxial Tensile-Induced Phase Transition in Graphynes
K. Jacques Kotoko, Komi Sodoga, Yusuf Shaidu, Nicola Seriani, Sangkha Borah, Katawoura Beltako
The Journal of Physical Chemistry C
128(40)
17058-17072
(2024)
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The field of materials science has a strong focus on the study of two-dimensional (2D) materials, with particular emphasis on graphene (GR) and its various allotropes such as graphynes (GYs). In this work, we explored through molecular dynamics simulations at finite temperatures the effects of uniaxial loading on GY structures, which led to new phases that arise at specific temperatures. We identified three new phases in α- and [14, 14, 18]-GYs, which we named C16-GY, C14-GY, and C12-GR. These phases have the remarkable property of remaining stable in a wide range of temperatures (T ≤ 4 and 300 K ≤ T ≤ 600 K). Moreover, we have conducted extensive investigations into the mechanical properties of these newly discovered phases. Through molecular dynamics simulations at finite temperatures, using empirical potential, we have gained valuable insights into how these materials behave under different temperature conditions. Our results reveal that at room temperature (300 K), C16-, C14-GYs exhibit high Young moduli in the x-direction (58.85 and 65.88 N/m) compared to α- and [14, 14, 18]-GYs (46.63 and 43.98 N/m), respectively. Additionally, these new phases exhibit mechanical properties that exceed those of phosphorene, germanene, silicene, and stanene. Importantly, both their mechanical and dynamic stability have been positively confirmed. As a result, these materials are promising candidates for various mechanical applications.
Dynamic traction force measurements of migrating immune cells in 3D biopolymer matrices
David Böhringer, Mar Cóndor, Lars Bischof, Tina Czerwinski, Niklas Gampl, Phuong Anh Ngo, Andreas Bauer, Caroline Voskens, Rocío López-Posadas, et al.
Immune cells, such as natural killer cells, migrate with high speeds of several micrometres per minute through dense tissue. However, the magnitude of the traction forces during this migration is unknown. Here we present a method to measure dynamic traction forces of fast migrating cells in biopolymer matrices from the observed matrix deformations. Our method accounts for the mechanical nonlinearity of the three-dimensional tissue matrix and can be applied to time series of confocal or bright-field image stacks. It allows for precise force reconstruction over a wide range of force magnitudes and object sizes—even when the imaged volume captures only a small part of the matrix deformation field. We demonstrate the broad applicability of our method by measuring forces from around 1 nN for axon growth cones up to around 10 μN for mouse intestinal organoids. We find that natural killer cells show bursts of large traction forces around 50 nN that increase with matrix stiffness. These force bursts are driven by myosin II contractility, mediated by integrin β1 adhesions, focal adhesion kinase and Rho-kinase activity, and occur predominantly when the cells migrate through narrow matrix pores.
Optimizing ZX-Diagrams with Deep Reinforcement Learning
Maximilian Nägele, Florian Marquardt
Machine Learning: Science and Technology (5)
035077
(2024)
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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.
Different Biomechanical Cell Behaviors in an Epithelium Drive Collective Epithelial Cell Extrusion
Lakshmi Balasubramaniam, Shreyansh Jain, Tien Dang, Emilie Lagoutte, René Marc Mège, Philippe Chavrier, Benoît Ladoux, Carine Rossé
Advanced Science
11
2401573
(2024)
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In vertebrates, many organs, such as the kidney and the mammary gland form ductal structures based on the folding of epithelial sheets. The development of these organs relies on coordinated sorting of different cell lineages in both time and space, through mechanisms that remain largely unclear. Tissues are composed of several cell types with distinct biomechanical properties, particularly at cell-cell and cell-substrate boundaries. One hypothesis is that adjacent epithelial layers work in a coordinated manner to shape the tissue. Using in vitro experiments on model epithelial cells, differential expression of atypical Protein Kinase C iota (aPKCi), a key junctional polarity protein, is shown to reinforce cell epithelialization and trigger sorting by tuning cell mechanical properties at the tissue level. In a broader perspective, it is shown that in a heterogeneous epithelial monolayer, in which cell sorting occurs, forces arising from epithelial cell growth under confinement by surrounding cells with different biomechanical properties are sufficient to promote collective cell extrusion and generate emerging 3D organization related to spheroids and buds. Overall, this research sheds light on the role of aPKCi and the biomechanical interplay between distinct epithelial cell lineages in shaping tissue organization, providing insights into the understanding of tissue and organ development.
Longitudinal associations between depressive symptoms and cell
deformability: do glucocorticoids play a role?
Julian Eder, Martin Kräter, Clemens Kirschbaum, Wei Gao, Magdalena Wekenborg, Marlene Penz, Nicole Rothe, Jochen Guck, Lucas Daniel Wittwer, et al.
European Archives of Psychiatry and Clinical Neuroscience
(2024)
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Cell deformability of all major blood cell types is increased in depressive disorders (DD). Furthermore, impaired glucocorticoid secretion is associated with DD, as well as depressive symptoms in general and known to alter cell mechanical properties. Nevertheless, there are no longitudinal studies examining accumulated glucocorticoid output and depressive symptoms regarding cell deformability. The aim of the present study was to investigate, whether depressive symptoms predict cell deformability one year later and whether accumulated hair glucocorticoids mediate this relationship. In 136 individuals (nfemale = 100; Mage = 46.72, SD = 11.28; age range = 20-65), depressive symptoms (PHQ-9) and hair glucocorticoids (cortisol and cortisone) were measured at time point one (T1), while one year later (T2) both depressive symptoms and hair glucocorticoids were reassessed. Additionally, cell deformability of peripheral blood cells was assessed at T2. Depression severity at T1 predicted higher cell deformability in monocytes and lymphocytes at T2. Accumulated hair cortisol and cortisone concentrations from T1 and T2 were not associated with higher cell deformability and further did not mediate the relationship between depressive symptoms and cell deformability. Elevated depressive symptomatology in a population based sample is longitudinally associated with higher immune cell deformability, while long-term integrated glucocorticoid levels seem not to be implicated in the underlying mechanism.
Polarization-entangled photons from a whispering gallery resonator
Sheng-Hsuan Huang, Thomas Dirmeier, Golnoush Shafiee, Kaisa Laiho, Dmitry Strekalov, Gerd Leuchs, Christoph Marquardt
npj Quantum Information
10
85
(2024)
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Crystalline whispering gallery mode resonators (WGMRs) have been shown to facilitate versatile sources of quantum states that can efficiently interact with atomic systems. These features make WGMRs an efficient platform for quantum information processing. Here, we experimentally show that it is possible to generate polarization entanglement from WGMRs by using an interferometric scheme. Our scheme gives us the flexibility to control the phase of the generated entangled state by changing the relative phase of the interferometer. The S value of Clauser–Horne–Shimony–Holt’s inequality in the system is 2.45 ± 0.07, which violates the inequality by more than six standard deviations.
How bacteria actively use passive physics to make biofilms
Liraz Chai, Vasily Zaburdaev, Roberto Kolter
Proceedings of the National Academy of Sciences of the United States of America
121
e2403842121
(2024)
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Modern molecular microbiology elucidates the organizational principles of bacterial biofilms via detailed examination of the interplay between signaling and gene regulation. A complementary biophysical approach studies the mesoscopic dependencies at the cellular and multicellular levels with a distinct focus on intercellular forces and mechanical properties of whole biofilms. Here, motivated by recent advances in biofilm research and in other, seemingly unrelated fields of biology and physics, we propose a perspective that links the biofilm, a dynamic multicellular organism, with the physical processes occurring in the extracellular milieu. Using Bacillus subtilis as an illustrative model organism, we specifically demonstrate how such a rationale explains biofilm architecture, differentiation, communication, and stress responses such as desiccation tolerance, metabolism, and physiology across multiple scales—from matrix proteins and polysaccharides to macroscopic wrinkles and water-filled channels.
Environmental stiffness regulates neuronal maturation via Piezo1-mediated TTR activity
Eva Kreysing, Hélène Gautier, Robert Humphrey, Katrin Mooslehner, Leila Muresan, Daniel Haarhoff, Sudipta Mukherjee, Xiaohui Zhao, Alexander Winkel, et al.
During brain development, neurons extend axons to connect to their target cells while initiating a maturation process, during which neurons start expressing voltage-gated ion channels, form synapses, express synaptic transmitters and receptors, and start communicating via action potentials. Little is known about external factors regulating this process. Here, we identified environmental mechanics as an important regulator of neuronal maturation, and a molecular pathway linking tissue stiffness to this process. Using patch clamp electrophysiology, calcium imaging and immunofluorescence, we found that neurons cultured on stiffer substrates showed a delay in voltage-gated ion channel activity, spontaneous and evoked action potentials, and synapse formation. RNA sequencing and CRISPR/Cas9 knockdown strategies revealed that the mechanosensitive ion channel Piezo1 supresses transthyretin (TTR) expression on stiffer substrates, slowing down synaptic receptor expression and consequently electrical maturation. Stiffening of brain tissue in Xenopus laevis embryos also resulted in a significant delay of synaptic activity in vivo. Our data indicate that environmental stiffness represents a fundamental regulator of neuronal maturation, which is important for the development of normal circuitry in the brain, and potentially for neurodevelopmental disorders.
Fluctuating Hydrodynamics Describes Transport in Cellular Aggregates
Biological functionality of cellular aggregates is largely influenced by the activity and displacements of individual constituent cells. From a theoretical perspective this activity can be characterized by hydrodynamic transport coefficients of diffusivity and conductivity. Motivated by the clustering dynamics of bacterial microcolonies we propose a model of active multicellular aggregates and use recently developed macroscopic fluctuation theory to derive a fluctuating hydrodynamics for this model system. Both semi-analytic theory and microscopic simulations show that the hydrodynamic transport coefficients are affected by non-equilibrium microscopic parameters and significantly decrease inside of the clusters. We further find that the Einstein relation connecting the transport coefficients and fluctuations breaks down in the parameter regime where the detailed balance is not satisfied. This study offers valuable tools for experimental investigation of hydrodynamic transport in other systems of cellular aggregates such as tumor spheroids and organoids.
Violation of the CHSH inequality supposedly demonstrates an irreconcilable conflict between quantum mechanics and local, realistic hidden variable theories. We show that the mathematical assumptions underlying the proof of the CHSH inequality are, in fact, incompatible with the physics of the experiments testing such inequality. This implies that we cannot dismiss local realistic hidden variable theories on the basis of currently available experimental data yet. However, we also show that an experimental proof of CHSH inequality is, in principle, possible, but it is unclear how to implement, in practice, such an experiment.
SOLAX: A Python solver for fermionic quantum systems with neural network
support
Numerical modeling of fermionic many-body quantum systems presents similar challenges across various research domains, necessitating universal tools, including state-of-the-art machine learning techniques. Here, we introduce SOLAX, a Python library designed to compute and analyze fermionic quantum systems using the formalism of second quantization. SOLAX provides a modular framework for constructing and manipulating basis sets, quantum states, and operators, facilitating the simulation of electronic structures and determining many-body quantum states in finite-size Hilbert spaces. The library integrates machine learning capabilities to mitigate the exponential growth of Hilbert space dimensions in large quantum clusters. The core low-level functionalities are implemented using the recently developed Python library JAX. Demonstrated through its application to the Single Impurity Anderson Model, SOLAX offers a flexible and powerful tool for researchers addressing the challenges of many-body quantum systems across a broad spectrum of fields, including atomic physics, quantum chemistry, and condensed matter physics.
Second-Order Nonlinear Circular Dichroism in Square Lattice Array of Germanium Nanohelices
Grégoire Saerens, Günter Ellrott, Olesia Pashina, Ilya Deriy, Vojislav Krstić, Mihail Petrov, Maria Chekhova, Rachel Grange
Second-harmonic generation (SHG) is prohibited in centrosymmetric crystals such as silicon or germanium due to the presence of inversion symmetry. However, the structuring of such materials makes it possible to break the inversion symmetry, thus achieving generation of second-harmonic. Moreover, various symmetry properties of the resulting structure, such as chirality, also influence the SHG. In this work, we investigate second-harmonic generation from an array of nanohelices made of germanium. The intensity of the second-harmonic displayed a remarkable enhancement of over 100 times compared to a nonstructured Ge thin film, revealing the influence of interaction between nanohelices. In particular, nonlinear circular dichroism, characterized through the SHG anisotropy factor gSHG–CD, changed its sign not only with the helix handedness but also with its density as well. We believe that our discoveries will open up new paths for the development of nonlinear photonics based on metamaterials and metasurfaces made of centrosymmetric materials.
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
Machine Learning: Science and Technology
5
035045
(2024)
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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.
Omega-3 supplementation changes the physical properties of leukocytes
but not erythrocytes in healthy individuals: An exploratory trial
Jan Philipp Schuchardt, Martin Kräter, Maximilian Schlögel, Jochen Guck, Brigitte A. van Oirschot-Hermans, Jennifer Bos, Richard van Wijk, Nathan L. Tintle, Jason Westra, et al.
Prostaglandins Leukotrienes and Essential Fatty Acids
202
102636
(2024)
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n3-PUFA impact health in several ways, including cardiovascular protection and anti-inflammatory effects, but the underlying mechanisms are not fully understood. In this exploratory study involving 31 healthy subjects, we aimed to investigate the effects of 12 weeks of fish-oil supplementation (1500 mg EPA+DHA/day) on the physical properties of multiple blood cell types. We used deformability cytometry (DC) for all cell types and Laser-assisted Optical Rotational Red Cell Analysis (Lorrca) to assess red blood cell (RBC) deformability. We also investigated the correlation between changes in the physical properties of blood cells and changes in the Omega-3 Index (O3I), defined as the relative content of EPA+DHA in RBCs. Following supplementation, the mean±SD O3I increased from 5.3%±1.5% to 8.3%±1.4% (p<0.001). No significant changes in RBC properties were found by both techniques. However, by DC we observed a consistent pattern of physical changes in lymphocytes, neutrophils and monocytes. Among these were significant increases in metrics correlated with the cells’ deformability resulting in less stiff cells. The results suggest that leukocytes become softer and have an increased ability to deform under induced short-term physical stress such as hydrodynamic force in the circulation. These changes could impact immune function since softer leukocytes can potentially circulate more easily and could facilitate a more rapid response to systemic inflammation or infection. In conclusion, fish-oil supplementation modulates some physical properties of leukocyte-subfractions, potentially enhancing their biological function. Further studies are warranted to explore the impact of n3-PUFA on blood cell biology, particularly in disease states associated with leukocyte dysregulation.
A neural network approach to running high-precision atomic computations
Modern applications of atomic physics, including the determination of frequency standards, and the analysis of astrophysical spectra, require prediction of atomic properties with exquisite accuracy. For complex atomic systems, high-precision calculations are a major challenge due to the exponential scaling of the involved electronic configuration sets. This exacerbates the problem of required computational resources for these computations, and makes indispensable the development of approaches to select the most important configurations out of otherwise intractably huge sets. We have developed a neural network (NN) tool for running high-precision atomic configuration interaction (CI) computations with iterative selection of the most important configurations. Integrated with the established pCI atomic codes, our approach results in computations with significantly reduced computational requirements in comparison with those without NN support. We showcase a number of NN-supported computations for the energy levels of Fe16+ and Ni12+, and demonstrate that our approach can be reliably used and automated for solving specific computational problems for a wide variety of systems.
Long-range chemical signalling in vivo is regulated by mechanical signals
Eva K. Pillai, Sudipta Mukherjee, Niklas Gampl, Ross J. McGinn, Katrin A. Mooslehner, Julia M. Becker, Amelia J. Thompson, Kristian Franze
Biological processes are regulated by chemical and mechanical signals, yet the interaction between these signalling modalities remains unclear. Using the developing Xenopus laevis brain as a model system, we identified a critical crosstalk between tissue stiffness and chemical signalling in vivo. Targeted knockdown of the mechanosensitive ion channel Piezo1 in retinal ganglion cells (RGCs) led to pathfinding errors in vivo. However, pathfinding errors were also observed in RGCs expressing Piezo1, when Piezo1 was downregulated in the surrounding brain tissue. Depleting Piezo1 in brain parenchyma led to decreases in the expression of the long-range chemical guidance cues, Semaphorin3A and Slit1, and markedly reduced tissue stiffness. While tissue softening was independent of Sema3A depletion, Slit1 and Sema3A expression increased significantly in stiffer environments in vitro. Moreover, stiffening soft brain regions in vivo induced ectopic Sema3A production via a Piezo1-dependent mechanism. Our results demonstrate that brain tissue mechanics modulates the expression of key chemical signals, a likely phenomenon across diverse biological systems.
The Holotomography
Geon Kim, Herve Hugonnet, Kyoohyun Kim, Chungha Lee, Jae-Hyuk Lee, Seongsoo Lee, Sung Sik Lee, Gabor Csucs, Jeongmin Ha, et al.
Holotomography (HT) represents a 3D, label-free optical imaging methodology that leverages refractive index as an inherent quantitative contrast for imaging. This technique has recently seen notable advancements, creating novel opportunities for the comprehensive visualization and analysis of living cells and their subcellular organelles. It has manifested wide-ranging applications spanning cell biology, biophysics, microbiology and biotechnology, substantiating its vast potential. In this Primer, we elucidate the foundational physical principles underpinning HT, detailing its experimental implementations and providing case studies of representative research employing this methodology. We also venture into interdisciplinary territories, exploring how HT harmonizes with emergent technologies, such as regenerative medicine, 3D biology and organoid-based drug discovery and screening. Looking ahead, we engage in a prospective analysis of potential future trajectories for HT, discussing innovation-focused initiatives that may further elevate this field. We also propose possible future applications of HT, identifying opportunities for its integration into diverse realms of scientific research and technological development.
Phase Symmetry Breaking of Counterpropagating Light in Microresonators for Switches and Logic Gates
Alekhya Ghosh, Arghadeep Pal, Shuangyou Zhang, Lewis Hill, Toby Bi, Pascal Del'Haye
The rapidly growing field of integrated photonics is enabling a large number of novel devices for optical data processing, neuromorphic computing and circuits for quantum photonics. While many photonic devices are based on linear optics, nonlinear responses at low threshold power are of high interest for optical switching and computing. In the case of counterpropagating light, nonlinear interactions can be utilized for chip-based isolators and logic gates. In our work we find a symmetry breaking of the phases of counterpropagating light waves in high-Q ring resonators. This abrupt change in the phases can be used for optical switches and logic gates. In addition to our experimental results, we provide theoretical models that describe the phase symmetry breaking of counterpropagating light in ring resonators.
Cell State-Specific Cytoplasmic Material Properties Control Spindle Architecture and Scaling
Mitotic spindles are dynamically intertwined with the cytoplasm they assemble in. How the physicochemical properties of the cytoplasm affect spindle architecture and size remains largely unknown. Using quantitative biochemistry in combination with adaptive feedback microscopy, we investigated mitotic cell and spindle morphology during neural differentiation of embryonic stem cells. While tubulin biochemistry and microtubule dynamics remained unchanged, spindles changed their scaling behaviour: in differentiating cells, spindles were significantly smaller than those in equally-sized undifferentiated stem cells. Integrating quantitative phase imaging, biophysical perturbations and theory, we found that as cells differentiated, their cytoplasm became more dilute. The concomitant decrease in free tubulin activated CPAP (centrosomal P4.1-associated protein) to enhance the centrosomal nucleation capacity. As a consequence, in differentiating cells, microtubule mass shifted towards spindle poles at the expense of the spindle bulk, explaining the differentiation-associated switch in spindle architecture. This study shows that cell state-specific cytoplasmic density tunes mitotic spindle architecture. Thus, we reveal physical properties of the cytoplasm as a major determinant in organelle size control.
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.
Controlled Protein‐Membrane Interactions Modulate Self‐Organization of Min Protein Patterns
Mergime Hasani, Katharina Esch, Katja Zieske
Angewandte Chemie International Edition
e202405046
(2024)
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Self-organizing protein patterns are crucial for living systems, governing important cellular processes such as polarization and division. While the field of protein self-organization has reached a point where basic pattern-forming mechanisms can be reconstituted in vitro using purified proteins, understanding how cells can dynamically switch and modulate these patterns, especially when transiently needed, remains an interesting frontier. Here, we demonstrate the efficient regulation of self-organizing protein patterns through the modulation of simple biophysical membrane parameters. Our investigation focuses on the impact of membrane affinity changes on Min protein patterns at lipid membranes composed of Escherichia coli lipids or minimal lipid compositions, and we present three major results. First, we observed the emergence of a diverse array of pattern phenotypes, ranging from waves over flower-shaped patterns to snowflake-like structures. Second, we demonstrated the dependency of these patterns on the density of protein-membrane linkers. Finally, we demonstrate that the shape of snowflake-like patterns is fine-tuned by membrane charge. Our results demonstrate the significant influence of membrane linkage as a straightforward biophysical parameter governing protein pattern formation. Our research points towards a simple yet intriguing mechanism by which cells can adeptly tune and switch protein patterns on the mesoscale.
Purcell-modified Doppler cooling of quantum emitters inside optical cavities
J. Lyne, N.S. Bassler, S. Park, G. Pupillo, C. Genes
Physical Review A
110
013115
(2024)
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Standard cavity cooling of atoms or dielectric particles is based on the action of dispersive optical forces in high-finesse cavities. We investigate here a complementary regime characterized by large cavity losses, resembling the standard Doppler cooling technique. For a single two-level emitter a modification of the cooling rate is obtained from the Purcell enhancement of spontaneous emission in the large cooperativity limit. This mechanism is aimed at cooling quantum emitters without closed transitions, which is the case for molecular systems, where the Purcell effect can mitigate the loss of population from the cooling cycle. We extend our analytical formulation to the many-particle case governed by small individual coupling, but exhibiting large collective coupling.
Precision Quantum Parameter Inference with Continuous Observation
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.
Fully Non-Linear Neuromorphic Computing with Linear Wave Scattering
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.
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.
Discovering Local Hidden-Variable Models for Arbitrary Multipartite Entangled States and Arbitrary Measurements
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
Communications Physics
7
217
(2024)
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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.
The Journal of Neuroscience: The Official Journal of the Society for Neuroscience
44(27)
(2024)
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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.
Beyond comparison: Brillouin microscopy and AFM-based indentation reveal divergent insights into the mechanical profile of the murine retina
Marcus Gutmann, Jana Bachir Salvador, Paul Müller, Kyoohyun Kim, Martin Schicht, Serhii Aif, Friedrich Paulsen, Lorenz Meinel, Jochen Guck, et al.
Journal of Physics: Photonics
6
035020
(2024)
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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, meeting these requirements entails an invasive preparation, which poses the risk of yielding mechanical properties that do not portray the physiological state of a tissue within a functioning organism. Brillouin microscopy has emerged as a non-invasive, optical technique that enables the assessment of mechanical cell and tissue properties with high spatio-temporal resolution. In optically transparent specimens, it 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. 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 retinae 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 sensitivities of Brillouin microscopy and AFM-indentation measurements to structural features, as visualized by transmission electron microscopy, to cross-linking or changes post mortem underscore the dangers of assuming interchangeability between the two methods. 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.
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.
Applied Physics Letters
124(26)
260701
(2024)
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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
Physical Review B (109)
214515
(2024)
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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.
Gulia Bikbaeva, Anna Pilip, Anastasiya Egorova, Vasiliy Medvedev, Daria Mamonova, Dmitrii Pankin, Alexey Kalinichev, Natalya Mayachkina, Lyudmila Bakina, et al.
Nanoscale Advances
6
4417-4425
(2024)
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The combination of photoswitchability and bioactivity in one compound provides interesting opportunities for photopharmacology. Here, we report a hybrid compound that in addition allows for its visual localization. It is the first demonstration of its kind and it even shows high photoswitchability. The multifunctional nanomaterial hybrid, which we present, is composed of luminescent LaVO4:Eu3+ nanoparticles and vinyl phosphonate, the latter of which inhibits butyrylcholinesterase (BChE). This inhibition increases 7 times when irradiated with a 266 nm laser. We found that it is increased even further when vinyl phosphonate molecules are conjugated with LaVO4:Eu3+ nanoparticles, leading in total to a 20-fold increase in BChE inhibition upon laser irradiation. The specific luminescence spectrum of LaVO4:Eu3+ allows its spatial localization in various biological samples (chicken breast, Daphnia and Paramecium). Furthermore, laser irradiation of the LaVO4:Eu3+@vinyl phosphonate hybrid leads to a drop in luminescence intensity and in lifetime of the Eu3+ ion that can implicitly indicate photoswitching of vinyl phosphonate in the bioactive state. Thus, combining enhanced photoswitchability, bioactivity and luminescence induced localizability in a unique way, hybrid LaVO4:Eu3+@vinyl phosphonate can be considered as a promising tool for photopharmacology.
Merging automatic differentiation and the adjoint method for photonic inverse design
Alexander Luce, Rasoul Alaee, Fabian Knorr, Florian Marquardt
Machine Learning: Science and Technology
5(2)
025076
(2024)
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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.
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.
Flying Particle Thermosensor in Hollow-Core Fiber Based on Fluorescence Lifetime Measurements
Jasper Freitag, Max Koeppel, Maria N. Romodina, Nicolas Joly, Bernhard Schmauß
IEEE Journal of Selected Topics in Quantum Electronics
30(6)
5600409
(2023)
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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.
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
Physical Review A (109)
063324
(2024)
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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.
Bell's theorem supposedly demonstrates an irreconcilable conflict between quantum mechanics and local, realistic hidden variable theories. In this paper we show that all experiments that aim to prove Bell's theorem do not actually achieve this goal. Our conclusions are based on a straightforward statistical analysis of the outcomes of these experiments. The key tool in our study is probability theory and, in particular, the concept of sample space for the dichotomic random variables that quantifies the outcomes of such experiments.We also show that an experimental proof of Bell's theorem is not, in principle, impossible, but it would require a completely different experimental apparatus than those commonly used to allegedly achieve this objective. The main consequence of our work is that we cannot dismiss local realistic hidden variable theories on the basis of currently available experimental data.
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.
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.
Measuring the Tensorial Flow of Mosaic Vector Beams in Disordered Media
Optical beams with nonuniform polarization offer enhanced capabilities for information transmission, boasting increased capacity, security, and resilience. These beams possess vectorial features that are spatially organized within localized three-dimensional regions, forming tensors that can be harnessed across a spectrum of applications spanning quantum physics, imaging, and machine learning. However, when subjected to the effect of the transmission channel, the tensorial propagation leads to a loss of data integrity due to the entanglement of spatial and polarization degrees of freedom. The challenge of quantifying this spatial-polarization coupling poses a significant obstacle to the utilization of vector beams in turbulent environments, multimode fibers, and disordered media. Here, we introduce and experimentally investigate mosaic vector beams, which consist of localized polarization tesserae that propagate in parallel, demonstrating accurate measurement of their behavior as they traverse strongly disordered channels and decoding their polarization structure in single-shot experiments. The resultant transmission tensor empowers polarization-based optical communication and imaging in complex media. These findings also hold promise for photonic machine learning, where the engineering of tensorial flow can enable optical computing with high throughput.
Quantum Equilibrium Propagation for efficient training of quantum systems based on Onsager reciprocity
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.
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.
Non-equilibrium structure and relaxation in active microemulsions
Rakesh Chatterjee, Hui-Shun Kuan, Frank Julicher, Vasily Zaburdaev
Microphase separation is common in active biological systems as exemplified by the separation of RNA and DNA-rich phases in the cell nucleus driven by the transcriptional activity of polymerase enzymes acting similarly to amphiphiles in a microemulsion. Here we propose an analytically tractable model of an active microemulsion to investigate how the activity affects its structure and relaxation dynamics. Continuum theory derived from a lattice model exhibits two distinct regimes of the relaxation dynamics and is linked to the broken detailed balance due to intermittent activity of the amphiphiles.
Generation and human-expert evaluation of interesting research ideas using knowledge graphs and large language models
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.
Nature Communications
15
4427
(2024)
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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
Physical Review Research
6
023205
(2024)
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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
Communications Physics (7)
161
(2024)
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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
Physical Review Research
6
023147
(2024)
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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
PHYSICAL REVIEW RESEARCH
6(2)
023142
(2024)
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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
Machine Learning: Science and Technology
5
025029
(2024)
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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
Biophysical Reports
4(2)
100156
(2024)
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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.
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.
Topologically Protected Transport in Engineered Mechanical Systems
Tirth Shah, Christian Brendel, Vittorio Peano, Florian Marquardt
Reviews of Modern Physics
96
021002
(2024)
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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.
Nature Communications
15
3363
(2024)
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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
Nature Communications (15)
3020
(2024)
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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.
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>
Lipid Membrane Topographies Are Regulators for the Spatial Distribution of Liquid Protein Condensates
Liquid protein condensates play important roles in orchestrating subcellular organization and as biochemical reaction hubs. Recent studies have linked lipid membranes to proteins capable of forming liquid condensates, and shown that biophysical parameters, like protein enrichment and restricted diffusion at membranes, regulate condensate formation and size. However, the impact of membrane topography on liquid condensates remains poorly understood. Here, we devised a cell-free system to reconstitute liquid condensates on lipid membranes with microstructured topographies and demonstrated that lipid membrane topography is a significant biophysical regulator. Using membrane surfaces designed with microwells, we observed ordered condensate patterns. Furthermore, we demonstrate that membrane topographies influence the shape of liquid condensates. Finally, we show that capillary forces, mediated by membrane topographies, lead to the directed fusion of liquid condensates. Our results demonstrate that membrane topography is a potent biophysical regulator for the localization and shape of mesoscale liquid protein condensates.
Quantitative analysis of the intensity distribution of optical rogue waves
Éva Rácz, Kirill Spasibko, Mathieu Manceau, László Ruppert, Maria Chekhova, Radim Filip
Communications Physics
7
119
(2024)
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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
The Journal of Physical Chemistry A
128
3910-3915
(2024)
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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
Physical Review Research
6
023015
(2024)
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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.
Cell viscosity influences hematogenous dissemination and metastatic extravasation of tumor cells
bioRxiv 10.1101/2024.03.28.587171
(2024)
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Metastases arise from a multi-step process during which tumor cells change their mechanics in response to microenvironmental cues. While such mechanical adaptability could influence metastatic success, how tumor cell mechanics directly impacts intravascular behavior of circulating tumor cells (CTCs) remains poorly understood. In the present study, we demonstrate how the deformability of CTCs affects hematogenous dissemination and identify the mechanical profiles that favor metastatic extravasation. Combining intravital microscopy with CTC-mimicking elastic beads and mechanically-tuned tumor cells, we demonstrate that the inherent properties of circulating objects dictate their ability to enter constraining vessels. We identify cellular viscosity as the key property that governs CTC circulation and arrest patterns. We further demonstrate that cellular viscosity is required for efficient extravasation and find that properties that favor extravasation and subsequent metastatic outgrowth can be opposite. Altogether, we identify CTC viscosity as a key biomechanical parameter that shapes several steps of metastasis.
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
Nature Communications
15
2545
(2024)
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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.
The Journal of Pathology: Clinical Research
10
(2024)
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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
Physical Review Research
6
013294
(2024)
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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
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 L. Sánchez-Soto, Andrea Aiello
Physics Letters A
504
129428
(2024)
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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
Communications Physics
7
82
(2024)
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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
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
Physical Review Letters
132
090001
(2024)
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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
Annual Review of Biophysics
53
(2024)
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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
Physical Review A
109
023714
(2024)
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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.
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
Physical Review Research (6)
L012028
(2024)
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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
Machine Learning: Science and Technology (5)
015029
(2024)
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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.
Eph/ephrin signalling in the developing brain is regulated by tissue stiffness
Eph receptors and their membrane-bound ligands, ephrins, provide key signals in many biological processes, such as cell proliferation, cell motility and cell sorting at tissue boundaries. However, despite immense progress in our understanding of Eph/ephrin signalling, there are still discrepancies between in vitro and in vivo work, and the regulation of Eph/ephrin signalling remains incompletely understood. Since a major difference between in vivo and most in vitro experiments is the stiffness of the cellular environment, we here investigated the interplay between tissue mechanics and Eph/ephrin signalling using the Xenopus laevis optic pathway as a model system. Xenopus retinal neurons cultured on soft substrates mechanically resembling brain tissue showed the opposite response to ephrinB1 compared to those cultured on glass. In vivo atomic force microscopy (AFM)-based stiffness mapping revealed that the visual area of the Xenopus brain, the optic tectum, becomes mechanically heterogeneous during its innervation by axons of retinal neurons. The resulting stiffness gradient correlated with both a cell density gradient and expression patterns of EphB and ephrinB family members. Exposing ex vivo brains to stiffer matrices or locally stiffening the optic tectum in vivo led to an increase in EphB2 expression in the optic tectum, indicating that tissue mechanics is an important regulator of Eph/ephrin signalling. Similar mechanisms are likely to be involved in the development and diseases of many other organ systems.
Forecasting high-impact research topics via machine learning on evolving knowledge graphs
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.
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.
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.
A buoyant nucleus is a universal characteristic of eukaryotic cells
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. Rather unexpectedly, we had discovered previously that the nucleus has a lower density than the cytoplasm in some cells and that this was robust against various perturbations. Here, we generalize this finding and show that living systems establish and maintain a constant density ratio between the nucleus and the cytoplasm across 10 model organisms: the nucleus is always 20% less dense than the cytoplasm. Using optical diffraction tomography and fluorescence microscopy, various biochemical and cell biological perturbations, together with theoretical modelling, we show that nuclear density is set by a pressure balance across the nuclear envelope in vitro (Xenopus egg extracts), in vivo (cell lines), and during early development (C. elegans embryos). The nuclear proteome exerts a colloid osmotic pressure, which, assisted by entropic chromatin pressure, draws water into the nucleus, while keeping osmotically inactive but heavy and large components excluded. This study reveals a previously unidentified homeostatic coupling of macromolecular densities that drives cellular organization with implications for pathophysiologies such as senescence and cancer.
Transfer learning from Hermitian to non-Hermitian quantum many-body physics
Sharareh Sayyad, Jose L. Lado
Journal of Physics: Condensed Matter
36(185603)
(2024)
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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.
Mean zero artificial diffusion for stable finite element approximation of convection in cellular aggregate formation
Soheil Firooz, B. Daya Reddy, Vasily Zaburdaev, Paul Steinmann
Computer Methods in Applied Mechanics and Engineering
419
116649
(2024)
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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.
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.
Gastroenterology
166(2)
284-297
(2024)
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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.
A universal strategy to induce oxidative stress-mediated cell death in biological systems
Leonhard Möckl, Karim Almahayni, Jana Bachir Salvador, Riccardo Conti, Anna Widera, Malte Spiekermann, Daniel Wehner, Hansjörg Grützmacher
Research Square 10.21203/rs.3.rs-3753893/v1
(2024)
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Precise cell elimination within intricate cellular populations is hampered by issues arising from the multifaceted biological properties of cells and the expansive reactivity of chemical agents. Current platforms are often limited by their complexity, toxicity, and poor physical/chemical properties. Here, we integrate the spatio-temporal precision of light delivery and the structural versatility of bisacylphosphane oxides (BAPOs), establishing a universal strategy for on-demand, precise cellular ablation in vitro and in vivo.
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.
Cell morphology as a quantifier for functional states of resident tissue macrophages
Miriam Schnitzerlein, Anja Wegner, Oumaima Ben Brahim, Stefan Uderhardt, Vasily Zaburdaev
Resident tissue macrophages (RTMs) are essential for maintaining homeostasis in a physiological tissue state. They monitor interstitial fluids, contain acute damage while actively preventing inflammation, and remove dead cells and debris. All these cellular functions are accompanied by characteristic changes in cell morphology, the expression of which can provide information about the functional status of the cells. What is currently known about morphological patterns and dynamic behavior of macrophages is derived primarily from experimental ex vivo cell cultures. However, how macrophages operate in living organisms is in many ways fundamentally different from how they do in a cell culture system. In this work, we employed an intravital imaging platform to generate dynamic data from peritoneal RTMs in vivo in mice under various conditions induced either chemically or physically. Using this data, we built an image processing pipeline and defined a set of human-interpretable cell size and shape features which allowed us to quantify RTM morphodynamics over time. We used those features to quantitatively differentiate cells in various functional states - when macrophages are activated, for instance, or when they “shut down” due to detrimental changes in the environment. The qualitative morphology changes associated with these functional states could be inferred directly from the quantitative measurements. Finally we used the set of cell morphology features monitoring the health of RTMs to improve a setup for explanted tissues. Thus, the proposed method is a versatile tool to provide insights into the dynamic behavior of bona fide macrophages in vivo and helps distinguish between physiological and pathological cell states.
Metasurface-Based Hybrid Optical Cavities for Chiral Sensing
Nico S. Baßler, Andrea Aiello, Kai P. Schmidt, Claudiu Genes, Michael Reitz
Physical Review Letters
132
043602
(2024)
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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
Nature Communications
15
147
(2024)
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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.
Multipoles from Majorana constellations
J. L. Romero, A. B. Klimov, A. Z. Goldberg, Gerd Leuchs, Luis Sanchez-Soto
PHYSICAL REVIEW A
109(1)
012214
(2024)
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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.
Frequency conversion of vortex states by chiral forward Brillouin scattering in twisted photonic crystal fibre
Xinglin Zeng, Philip St.J. Russell, Birgit Stiller
Optical vortex states-higher optical modes with helical phase progression and carrying orbital angular momentum-have been explored to increase the flexibility and capacity of optical fibres employed for example in mode-division-multiplexing, optical trapping and multimode imaging. A common requirement in such systems is high fidelity transfer of signals between different frequency bands and modes, which for vortex modes is not so straightforward. Here we report intervortex conversion between backward-propagating circularly polarised vortex modes at one wavelength, using chiral flexural phonons excited by chiral forward stimulated Brillouin scattering at a different wavelength. The experiment is carried out using chiral photonic crystal fibre, which robustly preserves circular polarisation states. The chiral acoustic wave, which has the geometry of a spinning single-spiral corkscrew, provides the orbital angular momentum necessary to conserve angular momentum between the coupled optical vortex modes. The results open up new opportunities for interband optical frequency conversion and the manipulation of vortex states in both classical and quantum regimes.
Tensed axons are on fire
Kristian Franze
Proceedings of the National Academy of Sciences of the United States of America
121(5)
(2024)
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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
New Journal of Physics (26)
013025
(2024)
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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
Physical Review Letters
132
023603
(2024)
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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
Physical Review Letters
132
023602
(2024)
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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.
All-optical nonlinear activation function based on stimulated Brillouin scattering
Grigorii Slinkov, Steven Becker, Dirk Englund, Birgit Stiller
Photonic neural networks have demonstrated their potential over the past decades, but have not yet reached the full extent of their capabilities. One reason for this lies in an essential component - the nonlinear activation function, which ensures that the neural network can perform the required arbitrary nonlinear transformation. The desired all-optical nonlinear activation function is difficult to realize, and as a result, most of the reported photonic neural networks rely on opto-electronic activation functions. Usually, the sacrifices made are the unique advantages of photonics, such as resource-efficient coherent and frequency-multiplexed information encoding. In addition, opto-electronic activation functions normally limit the photonic neural network depth by adding insertion losses. Here, we experimentally demonstrate an in-fiber photonic nonlinear activation function based on stimulated Brillouin scattering. Our design is coherent and frequency selective, making it suitable for multi-frequency neural networks. The optoacoustic activation function can be tuned continuously and all-optically between a variety of activation functions such as LeakyReLU, Sigmoid, and Quadratic. In addition, our design amplifies the input signal with gain as high as 20 dB, compensating for insertion losses on the fly, and thus paving the way for deep optical neural networks.
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