Advanced Data Analysis of Spontaneous Biophoton Emission: A Multi-Method Approach
M. Benfatto, L. De Paolis, L. Tonello, P. Grigolini

TL;DR
This paper develops and benchmarks a multi-method analysis pipeline for ultra-weak photon emission data, effectively distinguishing structured biological signals from trivial noise, and establishing a foundation for future biophoton research.
Contribution
It introduces a comprehensive, multi-method framework for analyzing photon-count time series, validated with surrogate data, to reliably identify biological coherence in ultra-weak photon emission.
Findings
Methods recover a hierarchy of dynamical regimes.
Poisson-like behavior confirmed in experimental data.
Multi-resolution approach separates structured signals from noise.
Abstract
Ultra-weak photon emission (UPE) from living systems is widely hypothesized to reflect un-derlying self-organization and long-range coordination in biological dynamics. However, distin-guishing biologically driven correlations from trivial stochastic or instrumental effects requires a robust, multi-method framework. In this work, we establish and benchmark a comprehensive anal-ysis pipeline for photon-count time series, combining Distribution Entropy Analysis, R\'enyi entro-py, Detrended Fluctuation Analysis, its generalization Multifractal Detrended Fluctuation Analysis, and tail-statistics characterization. Surrogate signals constructed from Poisson processes, Fractional Gaussian Noise, and Renewal Processes with power-law waiting times are used to validate sensitivity to memory, intermittency, and multifractality. Across all methods, a coherent hierarchy of dynamical regimes is…
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Taxonomy
TopicsBiofield Effects and Biophysics · Fractal and DNA sequence analysis · Chemical and Physical Studies
