Nonconvex optimization for optimum retrieval of the transmission matrix of a multimode fiber

TL;DR

This paper introduces a nonconvex optimization method for efficiently and robustly retrieving the transmission matrix of multimode fibers, enabling high-fidelity light control and imaging with faster computation and better noise resilience.

Contribution

A novel nonconvex optimization approach for transmission matrix retrieval that outperforms existing methods in speed, robustness, and accuracy, validated through numerical and experimental results.

Findings

Achieves 93.6% efficiency compared to holography

Retrieves an 8685×1024 TM in 42.3 seconds with GPU acceleration

Demonstrates high-fidelity image transmission through MMF

Abstract

Transmission matrix (TM) allows light control through complex media such as multimode fibers (MMFs), gaining great attention in areas like biophotonics over the past decade. The measurement of a complex-valued TM is highly desired as it supports full modulation of the light field, yet demanding as the holographic setup is usually entailed. Efforts have been taken to retrieve a TM directly from intensity measurements with several representative phase retrieval algorithms, which still see limitations like slow or suboptimum recovery, especially under noisy environment. Here, a modified non-convex optimization approach is proposed. Through numerical evaluations, it shows that the nonconvex method offers an optimum efficiency of focusing with less running time or sampling rate. The comparative test under different signal-to-noise levels further indicates its improved robustness for TM retrieval. Experimentally, the optimum retrieval of the TM of a MMF is collectively validated by multiple groups of single-spot and multi-spot focusing demonstrations. Focus scanning on the working plane of the MMF is also conducted where our method achieves 93.6% efficiency of the gold standard holography method when the sampling rate is 8. Based on the recovered TM, image transmission through the MMF with high fidelity can be realized via another phase retrieval. Thanks to parallel operation and GPU acceleration, the nonconvex approach can retrieve an 8685$\times$1024 TM (sampling rate=8) with 42.3 s on a regular computer. In brief, the proposed method provides optimum efficiency and fast implementation for TM retrieval, which will facilitate wide applications in deep-tissue optical imaging, manipulation and treatment.