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E. L. Ginzton Laboratory, Stanford University, 348 Via Pueblo, Stanford, CA 94305, USA
Charles Roques-Carmes (chrc@stanford.edu)
Received:25 March 2024,
Revised:30 August 2024,
Accepted:2024-09-03,
Published Online:20 September 2024,
Published:30 November 2024
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Roques-Carmes, C., Fan, S. H. & Miller, D. A. B. Measuring, processing, and generating partially coherent light with self-configuring optics. Light: Science & Applications, 13, 2726-2733 (2024).
Roques-Carmes, C., Fan, S. H. & Miller, D. A. B. Measuring, processing, and generating partially coherent light with self-configuring optics. Light: Science & Applications, 13, 2726-2733 (2024). DOI: 10.1038/s41377-024-01622-y.
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.
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