Hardware error correction for programmable photonics
Hardware error correction for programmable photonics
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DOI：
10.1364/optica.424052
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发表时间：
2021-10-20
期刊：
影响因子：
10.4
通讯作者：
Englund, Dirk
中科院分区：
文献类型：
--
作者：
Bandyopadhyay, Saumil;Hamerly, Ryan;Englund, Dirk
可重构干涉仪的可编程光子电路可用于实现对光学模式的任意操作，为量子模拟、信号处理和人工智能等领域的加速任务提供了一个灵活的平台。扩展这些系统的主要障碍是静态制造误差，其中每个设备中的小组件误差累积在电路计算中产生重大误差。减轻这种误差通常需要依赖于电路实时反馈的数值优化，这极大地限制了硬件的可扩展性。在这里，我们提出了一种确定性的方法，通过局部校正单个光门内的硬件误差来校正电路误差。我们将我们的方法应用于可编程光子学中实现的大规模光学神经网络和无限脉冲响应滤波器的模拟，发现它们对组件误差的弹性远远超出了现代工艺公差。我们的研究结果强调了在当前的制造工艺下将可编程光子学扩展到数百种模式的潜在方法。(C) 2021年美国光学学会根据OSA开放获取出版协议的条款
Programmable photonic circuits of reconfigurable interferometers can be used to implement arbitrary operations on optical modes, providing a flexible platform for accelerating tasks in quantum simulation, signal processing, and artificial intelligence. A major obstacle to scaling up these systems is static fabrication error, where small component errors within each device accrue to produce significant errors within the circuit computation. Mitigating this error usually requires numerical optimization dependent on real-time feedback from the circuit, which can greatly limit the scalability of the hardware. Here we present a deterministic approach to correcting circuit errors by locally correcting hardware errors within individual optical gates. We apply our approach to simulations of large scale optical neural networks and infinite impulse response filters implemented in programmable photonics, finding that they remain resilient to component error well beyond modern day process tolerances. Our results highlight a potential way to scale up programmable photonics to hundreds of modes with current fabrication processes. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement