Abstract
We propose a computational method for controlling the output of a multimode fiber using machine learning. Arbitrary images can be projected with amplitude-only calibration (no phase measurement) and fidelities on par with conventional full-measurement methods. We also show the reverse, meaning that multimode fibers can be used as a computational tool that harnesses spatiotemporal nonlinear effects to perform end to end learning tasks with unprecedented speed and low power consumption.
© 2021 The Author(s)
PDF Article | Presentation VideoMore Like This
Babak Rahmani, Damien Loterie, Eirini Kakkava, Navid Borhani, Ugur Tegin, Demetri Psaltis, and Christophe Moser
HTu5B.3 Digital Holography and Three-Dimensional Imaging (DH) 2020
N. Borhani, E. Kakkava, C. Moser, and D. Psaltis
CTH1B.4 Computational Optical Sensing and Imaging (COSI) 2018
Uğur Teğin, Mustafa Yıldırım, İlker Oğuz, Christophe Moser, and Demetri Psaltis
SW3R.3 CLEO: Science and Innovations (CLEO:S&I) 2021