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Mycelial Quantum Tomography: First Biological Decoder for Quantum Black Boxes

Year: 2025

Type: article

Abstract: World-first simulation of mycelial networks (Pleurotus ostreatus) as biological quantum tomography decoders for black-box superpositions. The model maps simplified quantum states onto mycelial “spiking” patterns and evaluates their ability to act as interpretable decoders. The simulation yields a fidelity of 0.142 (biological noise regime) and Corr_AB = 0.151, consistent with local stochastic dynamics and below the pre‑registered thresholds for any nonlocal or field‑like effect. The package includes fully reproducible Python code, a 300 DPI figure, and JSON results, and is designed as a baseline null model for future wet‑lab experiments with live Pleurotus cultures.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.18035081

Author: Chowdhury, Zubair

Language: English

Topic: Quantum Mechanics and Applications

Subfield: Atomic and Molecular Physics, and Optics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7117146427

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