扭曲光复矢量卷积的实验光学计算

Ling Hong, Haoxu Guo, Xiaodong Qiu, Fei Lin, Wuhong Zhang, Lixiang Chen
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摘要

摘要轨道角动量(OAM)作为光子固有的高维特性,在光通信中提高了信息容量。然而,OAM在光学计算中的潜力几乎尚未被探索。在这里,我们提出了一个高维OAM特征模叠加的复杂矢量卷积的高效光学计算协议。我们使用两个级联空间光调制器制备合适的OAM叠加来编码两个复杂向量。然后,设计了一种深度学习策略来解码复杂的OAM频谱,从而完成光学卷积任务。在我们的实验中,我们成功地展示了7维、9维和11维复向量卷积,其中平均接近度优于95%,平均相对误差< 6%。我们目前的方案可以扩展到包含其他自由度,以便在高维希尔伯特空间中实现更通用的光学计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental optical computing of complex vector convolution with twisted light
Abstract. Orbital angular momentum (OAM), emerging as an inherently high-dimensional property of photons, has boosted information capacity in optical communications. However, the potential of OAM in optical computing remains almost unexplored. Here, we present a highly efficient optical computing protocol for complex vector convolution with the superposition of high-dimensional OAM eigenmodes. We used two cascaded spatial light modulators to prepare suitable OAM superpositions to encode two complex vectors. Then, a deep-learning strategy is devised to decode the complex OAM spectrum, thus accomplishing the optical convolution task. In our experiment, we succeed in demonstrating 7-, 9-, and 11-dimensional complex vector convolutions, in which an average proximity better than 95% and a mean relative error <6  %   are achieved. Our present scheme can be extended to incorporate other degrees of freedom for a more versatile optical computing in the high-dimensional Hilbert space.
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