Universal convolution from wave dynamics: photonic processing and encryption in synthetic dimension

TL;DR

This paper demonstrates that wave dynamics in symmetric lattices inherently perform convolution, enabling high-speed photonic processing and encryption, and establishing a unified physics-based framework for scalable optical computing.

Contribution

It reveals that wave dynamics naturally implement convolution, leading to a universal, physics-based approach for designing high-speed, multifunctional photonic processors and encryption methods.

Findings

Achieved 13.5 TOPS image processing rate.

Developed a universal convolutional architecture based on wave dynamics.

Demonstrated optical encryption leveraging phase information and reversibility.

Abstract

Convolution, a cornerstone of signal processing and optical neural networks, has traditionally been implemented by mapping mathematical operations onto complex hardware. Here, we overcome this challenge by revealing that wave dynamics in translation-symmetric lattices intrinsically performs convolution, with the dispersion relation uniquely defining the complex-valued kernel. Leveraging this universal principle, we develop a convolutional architecture of minimal complexity through wave evolution in programmable photonic synthetic lattices, delivering high-throughput, multifunctional capabilities at a rate of 13.5 tera-operations per second (TOPS) for image processing. Beyond convolution acceleration, the kernel's complex nature facilitates the photonic simulation of both irreversible diffusion and reversible unitary quantum dynamics under classical incoherent excitation. Capitalizing on the physics-based reversibility and undetectable phase information, we demonstrate a novel convolution-driven optical encryption strategy. This work establishes a unified framework for photonic computing by grounding convolution in wave dynamics, opening avenues toward scalable, multifunctional photonic processors with high integration potential.