Mycelial Quantum Tomography: First Biological Decoder for Quantum Black Boxes

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.