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March 29, 2026Precision ChemistryOpen Access

Characterization of Parameter Uncertainty in Global Analysis for Ultrafast Spectroscopy Using Markov Chain Monte Carlo Sampling

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Authors

SBSullivan Bailey-DarlandLLLogan S. LancasterTKTaylor D. Krueger

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Overview

Global analysis estimates parameter uncertainty in ultrafast spectroscopy, suggesting improved accuracy for chemical systems.

Key Points

  • This research aims to characterize parameter uncertainty in ultrafast spectroscopy using Markov Chain Monte Carlo sampling methods.
  • Implemented Markov Chain Monte Carlo (MCMC) sampling for uncertainty analysis.
  • Conducted kinetic analysis using global analysis techniques on spectral data.
  • Tested the methodology on generated and experimental femtosecond transient absorption data sets.
  • Estimated parameter uncertainty well within 10% for typical spectral data sets.
  • Demonstrated that global analysis improves accuracy of parameter estimates with simultaneous spectral data collection.

Cite This Study

Bailey-Darland et al. (2026) studied this question.

synapsesocial.com/papers/69c8c2b8de0f0f753b39d304https://doi.org/10.1021/prechem.5c00468
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