论文标题
通过生成函数的自动分化来模拟多模高斯状态的光子统计
Simulating the Photon Statistics of Multimode Gaussian States by Automatic Differentiation of Generating Functions
论文作者
论文摘要
光子学的进步需要光子数清除的量子光学实验的模拟。我们展示了一种简单且通用的方法，用于模拟一般多模高斯状态的光子统计数据。得出的生成函数可以模拟高斯州光子统计以及多模光子添加和光子减少高斯州的光子统计的光子概率，力矩和阶乘力矩。数值结果是通过使用软件框架Pytorch来自动差异来自动差异化。我们的方法特别适合于在具有较低光子数量的现实情况下对量子光学实验的光子光子统计的实际模拟，其中必须考虑各种不完美来源。例如，我们计算了最近的多部分时间键编码量子键分布设置的检测概率，并将它们与相应的实验值进行比较。
Advances in photonics require photon-number resolved simulations of quantum optical experiments with Gaussian states. We demonstrate a simple and versatile method to simulate the photon statistics of general multimode Gaussian states. The derived generating functions enable simulations of the photon number distribution, cumulative probabilities, moments, and factorial moments of the photon statistics of Gaussian states as well as of multimode photon-added and photon-subtracted Gaussian states. Numerical results are obtained by automatic differentiation of these generating functions by employing the software framework PyTorch. Our approach is particularly well suited for practical simulations of the photon statistics of quantum optical experiments in realistic scenarios with low photon numbers, in which various sources of imperfections have to be taken into account. As an example, we calculate the detection probabilities for a recent multipartite time-bin coding quantum key distribution setup and compare them with the corresponding experimental values.
