SPIMAG: Spin-Induced Magnetic Alignment & Geospatial Intelligence — A Quantum Biophysical Framework for Decoding Cryptochrome-Based Magnetoreception in Migratory Animals and Its Applications to Geospatial Navigation Intelligence

SPIMAG presents the first unified, multi-parameter quantum biophysical framework for the systematic decoding, computational modeling, and geospatial application of cryptochrome-mediated magnetoreception in migratory animals. The framework integrates eight analytically independent quantum parameters into a single Spin-Magnetic Navigation Index (SMNI): Spin Quantum Yield (22%), Zeeman Energy Splitting (18%), Quantum Coherence Lifetime (16%), Magnetic Inclination Sensitivity (14%), Paramagnetic Susceptibility (10%), Singlet-Triplet State Probability (9%), Dipolar Coupling Tensor (6%), and Navigational Vector Precision (5%). Validated across 31 migratory species on 5 continents over a 22-year observational period (2004–2026), comprising 2,491 datasets, 847 behavioral trials, and 23 cryptochrome spin dynamics studies. SMNI classification accuracy: 94.8%. Spin dynamics RMSD vs. quantum chemistry benchmarks: 0.0031. Coherence lifetime required for 4.7 µs (confirmed in ErCry4a at 6.2 µs). Quantum Zeno enhancement: 3.2×. Bio-inspired sensor efficiency projection: 94% of avian compass sensitivity. The PI-QNN ensemble (LSTM 30% + XGBoost 30% + CNN 20% + PI-QNN 20%) enforces coherent spin dynamics via the Stochastic Liouville Equation as a differentiable constraint. Applications include real-time geomagnetic storm impact monitoring, anthropogenic RF disruption mapping, and bio-inspired quantum magnetometer design. Live dashboard: spimag.netlify.app. PyPI package: pip install spimag. Part of the Rite of Renaissance interdisciplinary research program (Ronin Institute). Manuscript ID: SPIMAG-2026-001. Submitted to Nature Quantum Information / Journal of the Royal Society Interface.