SpectRal-Crystal Efficiency-Mapping (SCEM): A Powerful Analytical Tool for modElling Quasi-Phase-Matched Interactions

The conventional approach to calculating quasi-phase-matching (QPM) gain stems from three coupled wave equations [1], which fail to account for frequency-dependent nonlinearities or real pump pulses with non-zero linewidth. These deficiencies limit the method's accuracy and applicability, particularly in applications employing broad bandwidth pulses or requiring precise control over frequency conversion processes. Here, we demonstrate a method for more complete analysis of the phase-matching potential resulting from combining one or more input spectra and a nonlinear crystal, with results which can be easily interpreted by means of a spectral-crystal efficiency-map (SCEM). This analytical approach agrees strongly with more computationally demanding full-field numerical simulations [2], and predicts the maximum power one can expect from real frequency conversion processes.

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Published
2025-06-23
DOI
https://doi.org/10.1109/cleo/europe-eqec65582.2025.11111442
Primary Topic
Machine Learning in Materials Science
Type
article
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article

SpectRal-Crystal Efficiency-Mapping (SCEM): A Powerful Analytical Tool for modElling Quasi-Phase-Matched Interactions

Richard A. McCracken, Sebastian C. Robarts
Machine Learning in Materials Science
article

SpectRal-Crystal Efficiency-Mapping (SCEM): A Powerful Analytical Tool for modElling Quasi-Phase-Matched Interactions

Richard A. McCracken, Sebastian C. Robarts
article en

Abstract

The conventional approach to calculating quasi-phase-matching (QPM) gain stems from three coupled wave equations [1], which fail to account for frequency-dependent nonlinearities or real pump pulses with non-zero linewidth. These deficiencies limit the method's accuracy and applicability, particularly in applications employing broad bandwidth pulses or requiring precise control over frequency conversion processes. Here, we demonstrate a method for more complete analysis of the phase-matching potential resulting from combining one or more input spectra and a nonlinear crystal, with results which can be easily interpreted by means of a spectral-crystal efficiency-map (SCEM). This analytical approach agrees strongly with more computationally demanding full-field numerical simulations [2], and predicts the maximum power one can expect from real frequency conversion processes.

Heriot-Watt University (GB)
Affordable and clean energy
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Machine Learning in Materials Science
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SpectRal-Crystal Efficiency-Mapping (SCEM): A Powerful Analytical Tool for modElling Quasi-Phase-Matched Interactions — Richard A. McCracken, Sebastian C. Robarts · (2025) | TGRS Research Map | TGRS