Bridging gaps between random approaches to quantum simulation

Ignacio García-Mata, Raúl O Vallejos, Diego A. Wisniacki

The fidelity amplitude (FA) is a quantity of paramount importance in echo-type experiments.We use semiclassical theory to study the average FA for quantum chaotic systems under external perturbation.We explain analytically two extreme cases: the random dynamics limit-attained approximately by strongly chaotic systems-and the random perturbation limit, which shows a Lyapunov decay.Numerical simulations help us to bridge the gap between both the extreme cases.

Dominic William Berry

García-Mata, I., Vallejos, R.O., Wisniacki, D.A.

The fidelity amplitude (FA) is a quantity of paramount importance in echo-type experiments. We use semiclassical theory to study the average FA for quantum chaotic systems under external perturbation. We explain analytically two extreme cases: the random dynamics limit-attained approximately by strongly chaotic systems-and the random perturbation limit, which shows a Lyapunov decay. Numerical simulations help us to bridge the gap between both the extreme cases. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.

Qi Zhou

Simone Bordoni, Andrea Papaluca, Piergiorgio Buttarini +3 more

Abstract In the current era of quantum computing, robust and efficient tools are essential to bridge the gap between simulations and quantum hardware execution. In this work, we introduce a machine learning approach to characterize the noise impacting a quantum chip and emulate it during simulations. Our algorithm leverages reinforcement learning (RL), offering increased flexibility in reproducing various noise models compared to conventional techniques such as randomized benchmarking or heuristic noise models. The effectiveness of the RL agent has been validated through simulations and testing on real superconducting qubits. Additionally, we provide practical use-case examples for the study of renowned quantum algorithms.

E. Solano