The complexity of experimental quantum information processing devices is increasing rapidly, requiring new approaches to control them. In this paper, we address the problems of practically modeling and controlling an integrated optical waveguide array chip—a technology expected to have many applications in telecommunications and optical quantum information processing. This photonic circuit can be electrically reconfigured, but only the output optical signal can be monitored. As a result, the conventional control methods cannot be naively applied. Characterizing such a chip is challenging for three reasons. First, there are uncertainties associated with the Hamiltonian model describing the chip. Second, we expect distortions of the control voltages caused by the chip’s electrical response, which cannot be directly observed. And third, there are imperfections in the measurements caused by losses from coupling the chip externally to optical fibers. We have developed a deep neural n...

中文翻译：

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使用深度学习对可重构光子电路进行建模和控制

实验量子信息处理设备的复杂性正在迅速增加，需要新的方法来控制它们。在本文中，我们解决了对集成光波导阵列芯片进行实际建模和控制的问题，该技术有望在电信和光量子信息处理中得到许多应用。该光子电路可以进行电重新配置，但是仅输出的光信号可以被监视。结果，传统的控制方法不能天真地应用。由于以下三个原因，表征这种芯片具有挑战性。首先，与描述芯片的汉密尔顿模型相关的不确定性。其次，我们期望由芯片的电响应引起的控制电压失真，这是无法直接观察到的。第三，由于将芯片从外部耦合到光纤而造成的损耗会导致测量不完善。我们开发了一种深层神经网络。