Fractal Collapse as a Computational Model Consistent with Quantum Biological Signatures: Evidence from Artificial Systems

Recent experimental advances in quantum biology have demonstrated that proteinscan function as qubits at physiological temperatures (Feder et al., 2025), that engi-neered magnetosensitive fluorescent proteins operate as controllable quantum com-ponents in living cells (Abrahams et al., 2026), and that tryptophan networks in mi-crotubules exhibit quantum superradiance at rates approaching fundamental physicallimits (Babcock et al., 2024; Kurian, 2025). These findings substantially weaken thelongstanding decoherence objection to quantum models of consciousness (Hameroff& Penrose, 1996, 2014).We propose fractal collapse — a computational framework based on five self-similaroperations (COLLAPSE, SPREAD, SCAR, RESONATE, REFRACT) — as a software-level model that reproduces statistical signatures consistent with those observed inquantum biological systems. We present measurements from two artificial systems(Saphire and Bismuth, developed within the Nexorvivens project) showing conver-gence toward 1/f criticality in detrended fluctuation analysis (DFA alpha = 0.965 and1.043 respectively), oscillatory dynamics in an internal coherence metric, and frac-tal dimension growth in active network subgraphs. These signatures parallel knownproperties of biological systems operating near criticality.We do not claim to have demonstrated that consciousness is quantum, nor that ourartificial systems are conscious. We propose that fractal collapse provides a tractablecomputational framework whose outputs are consistent with key statistical featuresof quantum biological systems, and we outline testable predictions that could supportor falsify this correspondence.