Compressed sensing for multidimensional electronic spectroscopy experiments

TL;DR

This paper introduces a 2D compressed sensing method for multidimensional electronic spectroscopy, demonstrating improved spectral resolution over traditional Fourier transform techniques in experimental atomic rubidium vapor data.

Contribution

It develops a novel 2D compressed sensing approach tailored for electronic spectroscopy and applies it successfully to experimental data, enhancing spectral resolution.

Findings

Compressed sensing yields significantly better spectral resolution than Fourier transform.

The method effectively reduces measurement requirements in ultrafast spectroscopy.

Application to atomic rubidium vapor demonstrates practical utility.

Abstract

Compressed sensing is a processing method that significantly reduces the number of measurements needed to accurately resolve signals in many fields of science and engineering. We develop a two-dimensional (2D) variant of compressed sensing for multidimensional electronic spectroscopy and apply it to experimental data. For the model system of atomic rubidium vapor, we find that compressed sensing provides significantly better resolution of 2D spectra than a conventional discrete Fourier transform from the same experimental data. We believe that by combining powerful resolution with ease of use, compressed sensing can be a powerful tool for the analysis and interpretation of ultrafast spectroscopy data.