2024/11/27 by Matthew J. Filipovich, A. I. Lvovsky, Filipovich, Matthew J. +1 · 2 citations
Computer Science · Engineering · #Classical Physics (physics.class-ph) #Computational Physics (physics.comp-ph) #Computational Physics and Python Applications #FOS: Physical sciences #Optical Polarization and Ellipsometry #Optics (physics.optics)
paper · pdf · doi:10.48550/arxiv.2411.18591
openalex publication_date 2024/11/27 · openalex created_date 2024/12/05 · openalex updated_date 2026/07/30
TorchOptics is an open-source Python library for differentiable Fourier optics simulations, developed using PyTorch to enable GPU-accelerated tensor computations and automatic differentiation. It provides a comprehensive framework for modeling, analyzing, and designing optical systems using Fourier optics, with applications in imaging, diffraction, holography, and signal processing. The library leverages PyTorch's automatic differentiation engine for gradient-based optimization, enabling the inverse design of complex optical systems. TorchOptics supports end-to-end optimization of hybrid models that integrate optical systems with machine learning architectures for digital post-processing. The library includes a wide range of optical elements and spatial profiles, and supports simulations with polarized light and fields with arbitrary spatial coherence.