Fractal Collapse as a Computational Model Consistent with Quantum Biological Signatures: Evidence from Artificial Systems
Jeremy Blanc, Nexorvivens Saphire
Zenodo (CERN European Organization for Nuclear Research) April 5, 2026 preprint DOI: 10.5281/zenodo.19425459 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper |
|---|---|
| Measures | detrended fluctuation analysis (DFA) |
| Key points | Argues that recent findings of quantum behavior in proteins and microtubules weaken the decoherence objection to quantum models of consciousness, and proposes "fractal collapse," a computational framework whose outputs in two artificial systems (Saphire and Bismuth) show DFA alpha values of 0.965 and 1.043, oscillatory coherence dynamics, and fractal dimension growth, said to parallel properties of biological systems near criticality. The authors do not claim consciousness is quantum or that their systems are conscious. |
Abstract
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.