Optical phenomena always display some degree of partial coherence between their respective degrees of freedom. Partial coherence is of particular interest in multimodal systems, where classical and quantum correlations between spatial, polarization, and spectral degrees of freedom can lead to fascinating phenomena (e.g., entanglement) and be leveraged for advanced imaging and sensing modalities (e.g., in hyperspectral, polarization, and ghost imaging). Here, we present a universal method to analyze, process, and generate spatially partially coherent light in multimode systems by using self-configuring optical networks. Our method relies on cascaded self-configuring layers whose average power outputs are sequentially optimized. Once optimized, the network separates the input light into its mutually incoherent components, which is formally equivalent to a diagonalization of the input density matrix. We illustrate our method with numerical simulations of Mach-Zehnder interferometer arrays and show how this method can be used to perform partially coherent environmental light sensing, generation of multimode partially coherent light with arbitrary coherency matrices, and unscrambling of quantum optical mixtures. We provide guidelines for the experimental realization of this method, including the influence of losses, paving the way for self-configuring photonic devices that can automatically learn optimal modal representations of partially coherent light fields.

光学现象在其各自的自由度之间总是表现出某种程度的部分相干性。部分相干性在多模态系统中特别令人感兴趣，其中空间、偏振和光谱自由度之间的经典和量子相关性可以导致令人着迷的现象（例如，纠缠），并可用于先进的成像和传感模式（例如，在高光谱、偏振和重影成像）。在这里，我们提出了一种使用自配置光网络在多模系统中分析、处理和生成空间部分相干光的通用方法。我们的方法依赖于级联的自配置层，其平均功率输出被顺序优化。优化后，网络将输入光分离为其相互不相干的分量，这在形式上相当于输入密度矩阵的对角化。我们通过马赫-曾德尔干涉仪阵列的数值模拟来说明我们的方法，并展示如何使用该方法来执行部分相干环境光传感、生成具有任意相干矩阵的多模部分相干光以及量子光学混合物的解扰。我们为该方法的实验实现提供了指导，包括损耗的影响，为自配置光子器件铺平了道路，该器件可以自动学习部分相干光场的最佳模态表示。