Reconstructing photon-number distributions for ultra-low-flux optical fields

Area of Science:

• Biophysics
• Photonics
• Biomolecular Spectroscopy

Background:

• Endogenous photon emission (biophotons) from cellular metabolism is a potential biomarker.
• Low intensity and non-stationary characteristics of biophotons hinder direct biological applications.
• Accurate measurement of photon statistics is crucial for understanding biological processes.

Purpose of the Study:

• To develop a statistical method for reconstructing true photon-number distributions from photocounts.
• To address the challenge of analyzing few-photon signals from biological sources.
• To investigate the statistical properties of weak biophoton emission.

Main Methods:

• A staged, model-based, regularized maximum-likelihood method was developed.
• The method reconstructs photon-number distributions from single-photon detector photocounts.
• The technique was validated using ultra-low laser flux and weak biophoton emission.

Main Results:

• The method accurately recovered expected Poisson statistics for ultra-low laser flux.
• Analysis of weak biophoton emission revealed deviations from Poisson behavior.
• Reconstructed photon-number distributions showed non-stationary dynamics over time.

Conclusions:

• The developed statistical procedure effectively reconstructs photon-number distributions in the few-photon regime.
• Deviations from Poissonian behavior in biophoton emission highlight its complex, non-stationary nature.
• This method enhances the potential of biophoton analysis for physiological biomarker applications.