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

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    Researchers developed a statistical method to reconstruct photon-number distributions from low-intensity biological light emissions. This technique reveals non-Poissonian dynamics in biophotons, offering new biomarker potential.

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    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.