Bayesian Analysis of Femtosecond Pump-Probe Photoelectron-Photoion Coincidence Spectra with Fluctuating Laser...

Area of Science:

• Chemical Physics
• Molecular Dynamics
• Spectroscopy

Background:

• Femtosecond pump-probe photoelectron-photoion coincidence (PEPICO) experiments investigate ultrafast molecular dynamics.
• Traditional data analysis methods face challenges with background noise and false coincidences.

Purpose of the Study:

• To apply and extend Bayesian probability theory for analyzing PEPICO experimental data.
• To improve accuracy and efficiency in studying ultrafast dynamical processes in photoexcited molecules.

Main Methods:

• Utilizing Bayesian probability theory for background subtraction and false coincidence correction in PEPICO data.
• Incorporating fluctuating laser intensities into the Bayesian analysis framework.
• Validating the method with mock data and experimental results.

Main Results:

• The Bayesian approach significantly increases signal-to-noise ratio and compensates for false coincidences.
• Accounting for false coincidences enables higher ionization rates, reducing data acquisition times.
• Fluctuating laser intensities have a minor impact on false coincidences but influence background subtraction.

Conclusions:

• Bayesian probability theory offers a robust and versatile framework for PEPICO data analysis.
• The inclusion of fluctuating laser intensities further enhances the applicability and accuracy of the Bayesian method.
• This approach facilitates more efficient and reliable investigation of ultrafast molecular processes.