The role of modes in nonlinear fiber optical computing

TL;DR

This paper explores how waveguide modes in graded-index multimode fibers can be harnessed for optical computing, revealing that effective computation occurs in a low-dimensional modal subspace influenced by task and regime.

Contribution

It introduces a modal decomposition-based model to evaluate optical computing in multimode fibers and identifies modal statistics as key design metrics.

Findings

Effective computation is confined to a low-dimensional modal subspace.

Modal entropy and energy-based mode counts characterize computational regimes.

Trade-off exists between modal richness and nonlinear beam self-cleaning.

Abstract

We investigate the nonlinear propagation of light in graded-index multimode fiber, utilizing it as an optical computing unit, and quantify how it employs waveguide modes to process information. Using a time-dependent spatiotemporal propagation model with modal decomposition, we evaluate several benchmark regression and classification tasks and study the modal content of the generated speckles, which couples with a simple digital layer to perform optical computing. Analysis of modal entropy and energy-based mode counts reveals that effective computation is confined to a low-dimensional modal subspace, whose identity depends on the task and propagation regime. This also sets a trade-off between modal richness and nonlinear beam self-cleaning. These results establish modal statistics as practical design metrics for fiber-based optical computers.