Image processing, transmission, and reconstruction constitute a major proportion of information technology. The rapid expansion of ubiquitous edge devices and data centers has led to substantial demands on the bandwidth and efficiency of image processing, transmission, and reconstruction. The frequent conversion of serial signals between the optical and electrical domains, coupled with the gradual saturation of electronic processors, has become the bottleneck of end-to-end machine vision. Here, we present an optical parallel computational array chip (OPCA chip) for end-to-end processing, transmission, and reconstruction of optical intensity images. By proposing constructive and destructive computing modes on the large-bandwidth resonant optical channels, a parallel computational model is constructed to implement end-to-end optical neural network computing. The OPCA chip features a measured response time of 6 ns and an optical bandwidth of at least 160 nm. Optical image processing can be efficiently executed with minimal energy consumption and latency, liberated from the need for frequent optical–electronic and analog–digital conversions. The proposed optical computational sensor opens the door to extremely high-speed processing, transmission, and reconstruction of visible contents with nanoseconds response time and terahertz bandwidth.

中文翻译：

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用于纳秒级端到端图像处理、传输和重建的并行光子芯片


图像处理、传输和重建构成了信息技术的主要部分。无处不在的边缘设备和数据中心的快速扩张对图像处理、传输和重建的带宽和效率提出了巨大的要求。串行信号在光域和电域之间的频繁转换，加上电子处理器的逐渐饱和，已经成为端到端机器视觉的瓶颈。在这里，我们提出了一种光学并行计算阵列芯片（OPCA芯片），用于光强度图像的端到端处理、传输和重建。通过提出大带宽谐振光通道上的相长和相消计算模式，构建并行计算模型来实现端到端的光神经网络计算。 OPCA 芯片的测量响应时间为 6 ns，光学带宽至少为 160 nm。光学图像处理可以以最小的能耗和延迟高效执行，无需频繁的光电和模数转换。所提出的光学计算传感器为具有纳秒响应时间和太赫兹带宽的可见内容的极高速处理、传输和重建打开了大门。