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SpinLab: Real-time radical-pair magnetoreception simulation framework driven by geomagnetic activity streams

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SpinLab 🧲🐦

Real-time radical-pair magnetoreception simulation framework driven by geomagnetic activity streams.

Overview

SpinLab is the first integrated platform linking real-time geomagnetic activity data directly to radical-pair quantum spin dynamics simulations. It transforms static field-sweep analyses into dynamic sensing experiments, enabling systematic investigation of magnetoreceptor performance across the full spectrum of geomagnetic conditions.

Key Features

  • Real-time geomagnetic integration: Ingests live Kp index data from NOAA Space Weather Prediction Center
  • Multi-nucleus spin dynamics: Arbitrary nuclear spin configurations with heterogeneous hyperfine tensors
  • Haberkorn recombination: Spin-selective singlet/triplet decay with configurable rate constants
  • Coherence quantification: ℓ₁-norm coherence measure in Zeeman product basis
  • Fisher information sensitivity: Binomial measurement model for magnetic field discriminability
  • Phase classification: Automated regime detection (high-coherence → classical)
  • Validation suite: Reproduces canonical RPM phenomenology (yield curves, anisotropy, RF disruption)

Paper

The SpinLab paper is available in paper/main.pdf:

SpinLab: A Real-Time Radical-Pair Magnetoreception Simulation Framework Driven by Geomagnetic Activity Streams

Alexander Gerard Casavant & Claudia Casavant JackKnife AI Research, February 2026

Figures

Figure Description
Fig 1 Singlet yield vs magnetic field strength
Fig 2 Orientation anisotropy
Fig 3 Coherence dynamics (ℓ₁-norm decay)
Fig 4 Fisher information sensitivity
Fig 5 System architecture
Fig 6 RF disruption effects
Fig 7 Polar anisotropy
Fig 8 Geomagnetic storm comparison

Citation

@article{casavant2026spinlab,
  title={SpinLab: A Real-Time Radical-Pair Magnetoreception Simulation Framework Driven by Geomagnetic Activity Streams},
  author={Casavant, Alexander Gerard and Casavant, Claudia},
  year={2026},
  note={JackKnife AI Research}
}

License

MIT License — see LICENSE.


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