Nonlinear optical encoding enabled by recurrent linear scattering

TL;DR

This paper introduces a passive optical nonlinear mapping using a multiple-scattering cavity, enabling efficient data processing and compression for tasks like classification and detection with low power and high performance.

Contribution

The authors present a novel optical design leveraging multiple scattering to induce nonlinear mappings passively, facilitating data compression and processing in optical computing.

Findings

Effective nonlinear mapping achieved with low-power continuous-wave laser

High performance in real-time pedestrian detection at extreme compression ratios

Demonstrated versatility across classification, image reconstruction, and detection tasks

Abstract

Optical information processing and computing can potentially offer enhanced performance, scalability and energy efficiency. However, achieving nonlinearity-a critical component of computation-remains challenging in the optical domain. Here we introduce a design that leverages a multiple-scattering cavity to passively induce optical nonlinear random mapping with a continuous-wave laser at a low power. Each scattering event effectively mixes information from different areas of a spatial light modulator, resulting in a highly nonlinear mapping between the input data and output pattern. We demonstrate that our design retains vital information even when the readout dimensionality is reduced, thereby enabling optical data compression. This capability allows our optical platforms to offer efficient optical information processing solutions across applications. We demonstrate our design's efficacy across tasks, including classification, image reconstruction, keypoint detection and object detection, all of which are achieved through optical data compression combined with a digital decoder. In particular, high performance at extreme compression ratios is observed in real-time pedestrian detection. Our findings open pathways for novel algorithms and unconventional architectural designs for optical computing.