Electrical Programmable Multi-Level Non-volatile Photonic Random-Access Memory

TL;DR

This paper introduces a low-loss, electrically-programmable multi-level non-volatile photonic memory using broadband transparent phase change material, achieving high efficiency, low power, and robust performance suitable for advanced photonic computing applications.

Contribution

It demonstrates a novel broadband transparent phase change material-based photonic memory with ultra-low loss, multi-bit capability, and high cyclability on a silicon platform, advancing photonic memory technology.

Findings

Achieved 0.12 dB total insertion loss for 4-bit memory

Demonstrated 0.2 dB/μm amplitude modulation

Validated robustness with half-a-million cyclability tests

Abstract

Photonic Random-Access Memories (P-RAM) are an essential component for the on-chip non-von Neumann photonic computing by eliminating optoelectronic conversion losses in data links. Emerging Phase Change Materials (PCMs) have been showed multilevel memory capability, but demonstrations still yield relatively high optical loss and require cumbersome WRITE-ERASE approaches increasing power consumption and system package challenges. Here we demonstrate a multi-state electrically-programmed low-loss non-volatile photonic memory based on a broadband transparent phase change material (Ge2Sb2Se5, GSSe) with ultra-low absorption in the amorphous state. A zero-static-power and electrically-programmed multi-bit P-RAM is demonstrated on a silicon-on-insulator platform, featuring efficient amplitude modulation up to 0.2 dB/{\mu}m and an ultra-low insertion loss of total 0.12 dB for a 4-bit memory showing a 100x improved signal to loss ratio compared to other phase-change-materials based photonic memories. We further optimize the positioning of dual micro-heaters validating performance tradeoffs. Experimentally we demonstrate a half-a million cyclability test showcasing the robust approach of this material and device. Low-loss photonic retention-of-state adds a key feature for photonic functional and programmable circuits impacting many applications including neural networks, LiDAR, and sensors for example.