Coupled integrated photonic quantum memristors using a single photon source made of a colour center

TL;DR

This paper demonstrates a network of two coupled photonic quantum memristors on a silicon chip, showing complex non-Markovian dynamics and enhanced memory effects, advancing quantum neuromorphic computing.

Contribution

First experimental realization of coupled integrated photonic quantum memristors with feedback, revealing complex memory dynamics and potential for scalable quantum computing architectures.

Findings

Observed larger hysteresis form factors in coupled memristors.

Demonstrated self-intersecting hysteresis loops indicating non-trivial memory dynamics.

Numerical simulations explained the emergence of these features from phase interactions.

Abstract

Photonic quantum memristors provide a measurement-induced route to nonlinear and history-dependent quantum dynamics. Experimental demonstrations have so far focused on isolated devices or simple cascaded devices configurations. Here, we experimentally realize and characterize a network of two coupled photonic quantum memristors with crossed feedback, implemented on a silicon nitride photonic integrated circuit and fed by a room-temperature single-photon source based on a silicon-vacancy color center SiV$^-$ in a nanodiamond. Each memristor consists of an integrated Mach-Zehnder interferometer whose transfer function is adaptively updated by photon detection events on another memristor, thus generating novel non-Markovian input-output dynamics with an enhanced memristive behaviour compared to single devices. In particular, we report inter-memristor input-output hysteresis curves exhibiting larger form factors and displaying self-intersecting loops, respectively revealing marked bistability and topologically non-trivial memory dynamics. Furthermore, numerical simulations show how these features emerge from the interplay between memory depth and relative input phase, for both intra- and inter-memristor input-output relations. Our results establish coupled integrated photonic quantum memristors as scalable nonlinear building blocks and highlight their potential for implementing compact quantum neuromorphic and reservoir computing architectures.