Tailoring Wideband Signals With a Photonic Hardware Accelerator

Abstract

Digital hardware accelerators are increasingly employed to speed up computation and reduce power dissipation, enabling real-time operation. Inspired by this paradigm, we propose the concept of the photonic hardware accelerator-an analog optical processing engine that precedes optical-to-electrical conversion and alleviates the burden on subsequent electronics. We propose one specific class of photonic hardware accelerators designed to assist in acquisition, feature extraction, and storage of wideband waveforms. This fundamental unit reshapes, in real time, the spectrotemporal evolution of a wideband streaming signal based on signal's sparsity. Functioning as an information gearbox, the accelerator transforms the signal according to the nonuniform entropy of its spectrum. Nonlinear group delay dispersion modes are introduced as primitive building blocks for such transformations. Representing spectrotemporal basis functions, these modes and their corresponding time-stretch wavelets have distinct and useful properties that depend on their symmetry. We focus on polynomial basis functions, but also discuss their limitations and alternatives such as spline functions that offer more efficient representation of group delay spectra with localized features. They are used to synthesize complex warped spectrotemporal operations that are reconfigurable and can be implemented in both analog optical and digital (computational) domains. We show how these dispersion-based computational primitives reshape the wideband signal to enable nonuniform sampling, compression, and pattern recognition in real time. Additional applications including coding, signal classification, and enhancement of signal-to-noise ratio during ultrafast analog-to-digital conversion are discussed.