《硅基集成衍射光学神经网络研究（英文版）》针对硅基集成衍射光学神经网络（DONN）高集成度、高计算容量以及计算单元大规模拓展等关键科学问题展开系统研究。具体包括硅基集成DONN的理论探索、结构设计、仿真计算以及芯片制造、封装、测试和实验系统误差补偿等方面工作。硅基集成DONN芯片具有高集成度、高计算容量、计算单元易于大规模拓展以及稳定性、便携性好等优势，是未来突破算力瓶颈的有效方案之一。《硅基集成衍射光学神经网络研究（英文版）》将对从事硅基集成光子芯片相关研究的科研工作者提供有价值的参考。

符庭钊，国防科技大学前沿交叉学科学院副研究员，研究方向为集成光子芯片、光计算、光学神经网络。博士毕业于清华大学电子工程系，获得2023年度清华大学优秀博士学位论文、清华大学优秀博士毕业生荣誉称号。

Supervisor¡¯s Foreword Artificial intelligence is sweeping across the globe at an unprecedented pace, yet the underlying computational architecture that supports its development faces dual challenges of computing power and power consumption. Optical neural networks represent a highly forward-looking computational architecture, boasting significant advantages such as ultra-high speed, low-power consumption, and large bandwidth. Currently, there has been extensive research in areas such as image processing and speech recognition, positioning it as a strong contender for the next generation of computational architectures. Among these, diffractive optical neural networks (DONNs), characte...