Online learning of the transmission matrix of dynamic scattering media - Sorbonne Université
Article Dans Une Revue Optica Année : 2023

Online learning of the transmission matrix of dynamic scattering media

Lorenzo Valzania
Sylvain Gigan

Résumé

Following recent advancements in wavefront shaping, optical methods have proven crucial for imaging and light control in multiply scattering media, such as biological tissues. However, the stability times of living biological specimens often prevent such methods from providing insights into relevant functioning mechanisms in cellular and organ systems. Here, we present a recursive and online optimization routine, borrowed from time series analysis, to optimally track the transmission matrices of dynamic scattering media over arbitrarily long time scales. It operates in a memory-efficient manner while preserving the advantages of both optimization-based routines and transmission-matrix measurements. Because it can be readily implemented in existing wavefront shaping setups featuring amplitude and/or phase modulation and phase-resolved or intensity-only acquisition, it could enable efficient optical investigations of living biological specimens.
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hal-04198883 , version 1 (08-09-2023)

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Lorenzo Valzania, Sylvain Gigan. Online learning of the transmission matrix of dynamic scattering media. Optica, 2023, 10, ⟨10.1364/optica.479962⟩. ⟨hal-04198883⟩
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