Sparse Optimization of Two-Dimensional Terahertz Spectroscopy
Abstract
Two-dimensional terahertz spectroscopy (2DTS) is a low-frequency analogue of two-dimensional optical spectroscopy that is rapidly maturing as a probe of a wide variety of condensed matter systems. However, a persistent problem of 2DTS is the long experimental acquisition times, preventing its broader adoption. A potential solution, requiring no increase in experimental complexity, is signal reconstruction via compressive sensing. In this work, we apply the sparse exponential mode analysis (SEMA) technique to 2DTS of a cuprate superconductor. We benchmark the performance of the algorithm in reconstructing the terahertz nonlinearities and find that SEMA reproduces the asymmetric photon echo lineshapes with as low as a 10% sampling rate and reaches the reconstruction noise floor with beyond 20-30% sampling rate. The success of SEMA in reproducing such subtle, asymmetric lineshapes confirms compressive sensing as a general method to accelerate 2DTS and multidimensional spectroscopies more broadly.
Cite
@article{arxiv.2409.13101,
title = {Sparse Optimization of Two-Dimensional Terahertz Spectroscopy},
author = {Zhengjun Wang and Hongju Da and Ankit S. Disa and Tonu Pullerits and Albert Liu and Frank Schlawin},
journal= {arXiv preprint arXiv:2409.13101},
year = {2025}
}