Open AccessCompressive Sensing Based on Mesoscopic Chaos of Silicon Optomechanical Photonic Crystal
Author(s) -
Pengfei Guo,
Zehao Wang,
Binglei Shi,
Yang Deng,
Jinping Zhang,
Huan Yuan,
Jiagui Wu
Publication year - 2020
Publication title -
ieee photonics journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.725
H-Index - 73
eISSN - 1943-0655
pISSN - 1943-0647
DOI - 10.1109/jphot.2020.3022801
Subject(s) - engineered materials, dielectrics and plasmas , photonics and electrooptics
Compressive sensing (CS) is an effective technique that can compress and recover sparse signals below the Nyquist-Shannon sampling theorem restriction. In this study, we successfully realize CS based on the mesoscopic chaos of an integrated Si optomechanical photonic crystal micro-cavity, which is fully compatible with the complementary metal-oxide-semiconductor (CMOS) process. Using the sensing matrix, we tested one-dimensional waveforms and two-dimensional images. The ultimate recovery curves were determined by comparing the chaotic sensing matrix with the Gaussian, Toeplitz, and Bernoulli matrices. Our results could pave the way for future large-scale implementations of high-speed CS processes based on fully CMOS-compatible Si-micro-cavities.