Automated generation of photonic circuits for Bell tests with homodyne measurements

TL;DR

This paper introduces an automated framework that uses deep reinforcement learning and quantum optical simulations to design photonic circuits capable of violating Bell inequalities, advancing practical device-independent quantum information processing.

Contribution

The work presents a novel automated method combining reinforcement learning and quantum simulations to design photonic circuits for Bell tests, improving practicality and robustness.

Findings

Achieved a CHSH violation of 2.068 with realistic photonic components.

Designed a loss-tolerant experimental setup using squeezed light and beam splitters.

Demonstrated the potential for practical device-independent quantum applications.

Abstract

Nonlocal quantum realizations, certified by the violation of a Bell inequality, are core resources for device-independent quantum information processing. Although proof-of-principle experiments demonstrating device-independent quantum information processing have already been reported, identifying physical platforms that are realistically closer to practical, viable devices remains a significant challenge. In this work, we present an automated framework for designing photonic implementations of nonlocal realizations using homodyne detections and quantum state heralding. Combining deep reinforcement learning and efficient simulations of quantum optical processes, our method generates photonic circuits that achieve significant violations of the Clauser-Horne-Shimony-Holt inequality. In particular, we find an experimental setup, robust to losses, that yields a CHSH violation of $2.068$ with $3.9$ dB and $0.008$ dB squeezed light sources and two beam splitters.