Quantum Neural Field Mapping
QNFM is the umbrella framework connecting a fixed geometric probe (the A-Gate), a hierarchy of measurable geometric invariants, and application domains where covariance structure carries signal. The encoding pipeline below is how it works for EEG.
Explore the pipeline ↓The framework as described below is the April 2026 version: EEG → covariance → manifold → circuit. Since September the object is the trace-normalised covariance treated as a density matrix, with the total power carried as a classical scalar alongside it. The derivation and the worked examples are in the Notebook. The pipeline below is kept because the first three steps are unchanged.
Every 20-second EEG window passes through five stages: phase extraction, connectivity estimation, angle encoding, quantum measurement, and polarity classification. Each stage is mathematically grounded and hardware-executable on current quantum processors.
Watch the full QNFM pipeline in real time. The simulation cycles between interictal and ictal states — observe how PLV connectivity surges during seizure, driving the SPD trajectory across the manifold. Toggle polarity to see the A-Gate's asymmetric response.
QNFM predicts a hierarchy of geometric invariants — each measurable by the same A-Gate circuit. The architecture for higher-order invariants is still under active investigation.