Machine Learning Enabled Lineshape Analysis in Optical Two-Dimensional Coherent Spectroscopy

Michael Titze; Srikanth Namuduri; Shekhar Bhansali; Hebin Li

Machine Learning Enabled Lineshape Analysis in Optical Two-Dimensional Coherent Spectroscopy

Michael Titze
, Srikanth Namuduri
, Shekhar Bhansali
, Hebin Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Although analytical solutions exist, the analysis of two-dimensional spectroscopy (2DCS) data can be tedious. A machine learning approach to analyzing 2DCS spectra is presented. We test the accuracy of the algorithm on simulated and experimental data.

Original language	English
Title of host publication	Conference Proceedings - Lasers and Electro-Optics Society Annual Meeting-LEOS
Volume	2020-May
State	Published - May 1 2020
Externally published	Yes

Cite this

@inproceedings{dbd5e56d340f49ba9d6c05933e01bd04,

title = "Machine Learning Enabled Lineshape Analysis in Optical Two-Dimensional Coherent Spectroscopy",

abstract = "Although analytical solutions exist, the analysis of two-dimensional spectroscopy (2DCS) data can be tedious. A machine learning approach to analyzing 2DCS spectra is presented. We test the accuracy of the algorithm on simulated and experimental data.",

author = "Michael Titze and Srikanth Namuduri and Shekhar Bhansali and Hebin Li",

year = "2020",

month = may,

day = "1",

language = "English",

isbn = "9781943580767",

volume = "2020-May",

booktitle = "Conference Proceedings - Lasers and Electro-Optics Society Annual Meeting-LEOS",

}

TY - GEN

T1 - Machine Learning Enabled Lineshape Analysis in Optical Two-Dimensional Coherent Spectroscopy

AU - Titze, Michael

AU - Namuduri, Srikanth

AU - Bhansali, Shekhar

AU - Li, Hebin

PY - 2020/5/1

Y1 - 2020/5/1

N2 - Although analytical solutions exist, the analysis of two-dimensional spectroscopy (2DCS) data can be tedious. A machine learning approach to analyzing 2DCS spectra is presented. We test the accuracy of the algorithm on simulated and experimental data.

AB - Although analytical solutions exist, the analysis of two-dimensional spectroscopy (2DCS) data can be tedious. A machine learning approach to analyzing 2DCS spectra is presented. We test the accuracy of the algorithm on simulated and experimental data.

UR - https://www.scopus.com/pages/publications/85091642057

M3 - Conference contribution

SN - 9781943580767

VL - 2020-May

BT - Conference Proceedings - Lasers and Electro-Optics Society Annual Meeting-LEOS

ER -

Machine Learning Enabled Lineshape Analysis in Optical Two-Dimensional Coherent Spectroscopy

Abstract

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