苏安潘:可扩展的光子线性向量机器
Ziyue Yang1, Chen Li1, Yuqia Ran2
1Department of Electronic Engineering, Tsinghua University, 100084, Beijing, China.
Light, science & applications
|December 31, 2025
概括
一个新的光子SUANPAN架构使得可扩展的矢量乘法为人工智能 (AI). 这个光子线性向量机器使用发射器-探测器对进行高维计算,实现超过98%的保真度.
科学领域:
- 光子学和人工智能 (AI) 的发展
- 光学计算是指光学计算的应用.
- 线性代数 线性代数
背景情况:
- 光子学为人工智能矢量乘法提供了优势,由于并行性和速度.
- 当前的光子线性运算面临着维度和复杂性的局限性.
- 数字-模拟转换是现有的光子计算架构的一个瓶.
研究的目的:
- 提出一个可编程和可重新配置的光子线性向量机器,具有极大的可扩展性.
- 为了克服当前光子线性运算的维度限制.
- 开发一种光子计算架构,其灵感来源于中国的算盘 (Suanpan).
主要方法:
- 使用独立的发射器探测器对作为基本计算单元.
- 采用比特编码和模拟检测用于向量元素准备,避免大型转换器阵列.
- 实现了 8x8 垂直腔表面发射激光 (VCSEL) 阵列和 8x8 MoTe2 光探测器阵列的架构.
主要成果:
- 在矢量内乘积上实现了超过98%的计算保真度.
- 通过乘以独立的发射器探测器对而没有内部光束相互作用来证明可扩展性.
- 成功地应用了光子SUANPAN来解决一个1024维的优化问题.
- 在手写数字数据集上获得了88%的分类准确度.
结论:
- 光子SUANPAN架构为高维向量运算提供了极端的可扩展性.
- 这种方法绕过了复杂的数字-模拟转换阵列的需求.
- 光子SUANPAN显示了作为各种AI应用的基本线性向量机的潜力.
相关概念视频
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