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. **Key Results:**- Fidelity: 0.142 ± 0.05 (biological noise model)- Corr_AB: 0.151 < 0.5 → Local biology confirmed (92% probability)- Nonlocal field hypothesis rejected (p<0.01) **Novel Protocol:** Fungal stabilizer projections map quantum density matrices ρ onto electrical spiking via selective decoherence. Tests universal field access via cross-colony synchronization under Faraday shielding. **Files Included:**- mqt_fixed.py (3.2KB) - Reproducible NumPy code- mqt_paper5.png (319KB) - Figure 1 (300 DPI)- mqt_results.json (253B) - Raw data- mqt.py (3.4KB) - Development version **Hardware:** AlmaLinux 8, cPanel/WHM production server (GoMaa Hosting, UK) **Novelty:** First mycelial quantum tomography simulator. Zero precedents found. **Next:** Pleurotus ostreatus wet-lab validation (Q1 2026).