Coupled integrated photonic quantum memristors using a single photon source made of a colour center
Alessio Baldazzi, Roy Philip George Konnoth Ancel, Sebastiano Guaraldo, Xuan Chen, Ziad Abi Akar, Regis Deturche, Stefano Azzini, Christophe Couteau, Lorenzo Pavesi
TL;DR
We demonstrate a scalable network of two coupled photonic quantum memristors implemented on a silicon-nitride PIC, driven by a room-temperature SiV-color-center single-photon source. Each memristor is realized as a Mach-Zehnder interferometer whose phase-dependent reflectivity $R(t)$ is updated through measurement-based feedback, enabling non-Markovian input–output dynamics and enhanced memristive behavior. The experiments reveal non-pinched, large-area hysteresis and self-intersecting loops in inter-memristor relations, with memory depth and input phase ($T$ and $\Phi$) controlling the observed dynamics, and form factors reaching up to $F\approx 0.95$. These results establish coupled PQMs as compact nonlinear building blocks suitable for quantum neuromorphic and reservoir computing architectures on integrated photonic platforms.
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.
