Basani Jasvith Raj, Vadlamani Sri Krishna, Bandyopadhyay Saumil, Englund Dirk R, Hamerly Ryan
Department of Electrical and Computer Engineering, Institute for Research in Electronics and Applied Physics, and Joint Quantum Institute, University of Maryland, College Park, MD 20742, USA.
Research Laboratory of Electronics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Nanophotonics. 2023 Jan 9;12(5):975-984. doi: 10.1515/nanoph-2022-0525. eCollection 2023 Mar.
Multiport interferometers based on integrated beamsplitter meshes have recently captured interest as a platform for many emerging technologies. In this paper, we present a novel architecture for multiport interferometers based on the sine-cosine fractal decomposition of a unitary matrix. Our architecture is unique in that it is self-similar, enabling the construction of modular multi-chiplet devices. Due to this modularity, our design enjoys improved resilience to hardware imperfections as compared to conventional multiport interferometers. Additionally, the structure of our circuit enables systematic truncation, which is key in reducing the hardware footprint of the chip as well as compute time in training optical neural networks, while maintaining full connectivity. Numerical simulations show that truncation of these meshes gives robust performance even under large fabrication errors. This design is a step forward in the construction of large-scale programmable photonics, removing a major hurdle in scaling up to practical machine learning and quantum computing applications.
基于集成分束器网格的多端口干涉仪最近作为许多新兴技术的平台而受到关注。在本文中，我们提出了一种基于酉矩阵的正弦 - 余弦分形分解的多端口干涉仪新架构。我们的架构独特之处在于它是自相似的，能够构建模块化的多芯片设备。由于这种模块化，与传统多端口干涉仪相比，我们的设计对硬件缺陷具有更强的恢复能力。此外，我们电路的结构允许系统截断，这对于减少芯片的硬件占用面积以及训练光学神经网络时的计算时间至关重要，同时保持完全连通性。数值模拟表明，即使在制造误差较大的情况下，这些网格的截断也能给出稳健的性能。这种设计在大规模可编程光子学的构建方面向前迈进了一步，消除了扩大到实际机器学习和量子计算应用的一个主要障碍。
