Renormalized Mutual Information for Artificial Scientific Discovery

Leopoldo Sarra, Andrea Aiello, Florian Marquardt

We derive a well-defined renormalized version of mutual information that allows to estimate the dependence between continuous random variables in the important case when one is deterministically dependent on the other. This is the situation relevant for feature extraction, where the goal is to produce a low-dimensional effective description of a high-dimensional system. Our approach enables the discovery of collective variables in physical systems, thus adding to the toolbox of artificial scientific discovery, while also aiding the analysis of information flow in artificial neural networks.

Efficient cavity control with SNAP gates

Thomas Fösel, Stefan Krastanov, Florian Marquardt, Liang Jiang

Microwave cavities coupled to superconducting qubits have been demonstrated to be a promising platform for quantum information processing. A major challenge in this setup is to realize universal control over the cavity. A promising approach are selective number-dependent arbitrary phase (SNAP) gates combined with cavity displacements. It has been proven that this is a universal gate set, but a central question remained open so far: how can a given target operation be realized efficiently with a sequence of these operations. In this work, we present a practical scheme to address this problem. It involves a hierarchical strategy to insert new gates into a sequence, followed by a co-optimization of the control parameters, which generates short high-fidelity sequences. For a broad range of experimentally relevant applications, we find that they can be implemented with 3 to 4 SNAP gates, compared to up to 50 with previously known techniques.

Engineering Fast High-Fidelity Quantum Operations With Constrained Interactions

Thales Figueiredo Roque, Aashish A Clerk, Hugo Ribeiro

Understanding how to tailor quantum dynamics to achieve a desired evolution is a crucial problemin almost all quantum technologies. We present a very general method for designing high-efficiencycontrol sequences that are always fully compatible with experimental constraints on available inter-actions and their tunability. Our approach reduces in the end to finding control fields by solvinga set of time-independent linear equations. We illustrate our method by applying it to a numberof physically-relevant problems: the strong-driving limit of a two-level system, fast squeezing in aparametrically driven cavity, the leakage problem in transmon qubit gates, and the acceleration ofSNAP gates in a qubit-cavity system.