Entangled Two-Photon Spectroscopy Assisted by Machine Learning

We propose a machine learning protocol to determine the number of inter-mediate levels participating in a two-photon excitation process. Our method achieves up to 99 . 713% identification efficiency for systems with one to four intermediate levels.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.1364/cleo_at.2025.jps200_101
Primary Topic
Spectroscopy and Quantum Chemical Studies
Type
article
Field-Weighted Citation Impact
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article

Entangled Two-Photon Spectroscopy Assisted by Machine Learning

Áulide Martínez-Tapia, Roberto de J. León‐Montiel
Spectroscopy and Quantum Chemical Studies
article

Entangled Two-Photon Spectroscopy Assisted by Machine Learning

Áulide Martínez-Tapia, Roberto de J. León‐Montiel
article en

Abstract

We propose a machine learning protocol to determine the number of inter-mediate levels participating in a two-photon excitation process. Our method achieves up to 99 . 713% identification efficiency for systems with one to four intermediate levels.

Openalex Percentile: Top 80%
Spectroscopy and Quantum Chemical Studies
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Entangled Two-Photon Spectroscopy Assisted by Machine Learning — Áulide Martínez-Tapia, Roberto de J. León‐Montiel · (2025) | TGRS Research Map | TGRS