论文标题

电气可编程的多级非易失性光子随机访问记忆

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

论文作者

Meng, Jiawei, Gui, Yaliang, Nouri, Behrouz Movahhed, Comanescu, Gelu, Ma, Xiaoxuan, Zhang, Yifei, Popescu, Cosmin-Constantin, Kang, Myungkoo, Miscuglio, Mario, Peserico, Nicola, Richardson, Kathleen A., Hu, Juejun, Dalir, Hamed, Sorger, Volker J.

论文摘要

光子随机记忆(P-RAM)是通过消除数据链路中的光电转换损耗,是芯片非弹药neumann光子计算的重要组成部分。新兴的相变材料(PCM)已显示出多级内存能力,但是演示仍然会产生相对较高的光学损失,并且需要繁琐的写入式方法来增加功耗和系统包装挑战。在这里,我们演示了一种基于宽带透明相变材料(GE2SB2SE5,GSSE,GSSE)的多状态电气编程的低损失非挥发性光子记忆,并在无定形状态下具有超低吸收。在硅启动平台上展示了​​零静态功率和电气编程的多位P-RAM,该平台的有效振幅调制高达0.2 db/μm,与4位内存的超低插入损失总数为4位记忆,对于4位的记忆,与其他相比的损失率相比,损失比例为100x信号的损失比率是基于损失比例的损失比较距离构图。我们进一步优化了验证绩效折衷的双重酿酒者的定位。在实验上,我们证明了500万个可环性测试,展示了该材料和设备的强大方法。低损坏的光子保留状态为光子功能和可编程电路添加了影响许多应用程序,例如神经网络,LIDAR和传感器。

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/μm 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.

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