Compressive dual-comb spectroscopy

TL;DR

This paper demonstrates that compressive sensing can significantly reduce data size in dual-comb spectroscopy while maintaining high accuracy, enabling efficient broadband molecular analysis.

Contribution

It introduces a numerical method for compressing dual-comb spectroscopy data with high compression rates and minimal error, advancing spectral data processing techniques.

Findings

Achieved over 100-fold data compression with 3% mole fraction error.

Reconstructed spectra of 10 molecular species with 10.5 compression rate and 0.003 transmittance error.

Validated the approach through numerical simulations in mid-infrared DCS.

Abstract

Broadband, high resolution and rapid measurement of dual-comb spectroscopy (DCS) generates a large amount of data stream. We numerically demonstrate significant data compression of DCS spectra by using a compressive sensing technique. Our numerical simulation shows a compression rate of more than 100 with 3% error in mole fraction estimation of mid-infrared (MIR) DCS of two molecular species in a broadband (~30 THz) and high resolution (~115 MHz) condition. We also numerically demonstrate a massively parallel MIR DCS spectrum of 10 different molecular species can be reconstructed with a compression rate of 10.5 with a transmittance error of 0.003 from the original spectrum.