Compressive Fourier Transform Spectroscopy

TL;DR

This paper introduces a compressive-sampling method for Fourier-transform spectroscopy that significantly reduces data acquisition time without modifying existing setups, demonstrated on vibrational spectra with less than 25% of traditional samples.

Contribution

The paper presents a novel compressive-sampling approach enabling faster Fourier-transform spectroscopy without hardware changes, applicable to multidimensional measurements.

Findings

Achieved spectral resolution with less than 25% of Nyquist samples.

No modifications needed for existing Fourier-transform spectroscopy setups.

Effective for sparse vibrational spectra in CARS experiments.

Abstract

We describe an approach based on compressive-sampling which allows for a considerable reduction in the acquisition time in Fourier-transform spectroscopy. In this approach, an N-point Fourier spectrum is resolved from much less than N time-domain measurements using a compressive-sensing reconstruction algorithm. We demonstrate the technique by resolving sparse vibrational spectra using <25% of the Nyquist rate samples in single-pulse CARS experiments. The method requires no modifications to the experimental setup and can be directly applied to any Fourier-transform spectroscopy measurement, in particular multidimensional spectroscopy.