Transmission matrix inference via pseudolikelihood decimation. (30th September 2022) - Ancora, Daniele; Leuzzi, Luca
Abstract: Recently, significant efforts in medical imaging are towards the exploitation of disordered media as optics tools. Among several approaches, the transmission matrix description is promising for characterizing complex structures and, currently, has enabled imaging and focusing through disorder. In the present work, we report a statistical mechanics description of the transmission problem. We convert a linear input–output transmission recovery into the statistical inference of an effective interaction matrix. We do this by relying on a pseudolikelihood maximization process based on random intensity observations. Our aim is to bridge results from spin-glass theory to the field of disordered photonics, uncovering insights from the scattering problem and encouraging the development of novel imaging techniques for better medical investigations.