Advanced Data Analysis of Spontaneous Biophoton Emission: A Multi-Method Approach

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, Rényi 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 recovered, demonstrating internal methodological consistency. Application to experimental dark-count data and attenuated coherent-laser emission confirm Poisson-like behavior, establishing an essential statistical baseline for UPE studies. The combined results show that this multi-resolution approach reliably separates trivial photon-counting statistics from struc-tured long-range organization, providing a validated methodological foundation for future biological UPE measurements and their interpretation in the context of non-equilibrium statistical physics, information dynamics, and prospective markers of biological coherence.