Revealing true coupling strengths in two-dimensional spectroscopy with sparsity-based signal recovery

Hadas Frostig; Tim Bayer; Yonina C Eldar; Yaron Silberberg

doi:10.1038/lsa.2017.115

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Revealing true coupling strengths in two-dimensional spectroscopy with sparsity-based signal recovery

Original Articles

- Revealing true coupling strengths in two-dimensional spectroscopy with sparsity-based signal recovery
- Light: Science & Applications Vol. 6, Issue 4, (2017)
- Affiliations：
  
  1.Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel
  2.Institut für Physik, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany
  3.Department of Electrical Engineering, Technion 32000, Haifa, Israel
- Author bio：
  
  Y Silberberg, Email: hadas.frostig@weizmann.ac.il
- Funds：
- DOI：10.1038/lsa.2017.115
  CLC：
- Published：2017-12，
  
  Published Online：07 August 2017，
  
  Received：13 November 2016，
  
  Revised：28 July 2017，
  
  Accepted：04 August 2017
- Accepted：
Scan QR Code
Frostig, H. et al. Revealing true coupling strengths in two-dimensional spectroscopy with sparsity-based signal recovery. Light: Science & Applications, 6, e17115 (2017).
DOI：

Frostig, H. et al. Revealing true coupling strengths in two-dimensional spectroscopy with sparsity-based signal recovery. Light: Science & Applications, 6, e17115 (2017). DOI： 10.1038/lsa.2017.115.

摘要

Abstract

Two-dimensional (2D) spectroscopy is used to study the interactions between energy levels in both the field of optics and nuclear magnetic resonance (NMR). Conventionally

the strength of interaction between two levels is inferred from the value of their common off-diagonal peak in the 2D spectrum

which is termed the cross peak. However

stronger diagonal peaks often have long tails that extend into the locations of the cross peaks and alter their values. Here

we introduce a method for retrieving the true interaction strengths by using sparse signal recovery techniques and apply our method in 2D Raman spectroscopy experiments.

关键词

Keywords

multidimensional spectroscopynonlinear opticssparsity-based algorithms

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