2022
DOI: 10.48550/arxiv.2202.13120
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A Log-Gaussian Cox Process with Sequential Monte Carlo for Line Narrowing in Spectroscopy

Abstract: We propose a statistical model for narrowing line shapes in spectroscopy that are well approximated as linear combinations of Lorentzian or Voigt functions. We introduce a log-Gaussian Cox process to represent the peak locations thereby providing uncertainty quantification for the line narrowing. Bayesian formulation of the method allows for robust and explicit inclusion of prior information as probability distributions for parameters of the model. Estimation of the signal and its parameters is performed using… Show more

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