Quantum-Resonant Netting (QRN) Thermodynamic motivation, formal model of open wave dynamics on the cognitome, and validation program

QRN (Quantum-Resonant Netting) is a hypothesis proposing that the brain can perform energy-efficient pre-selection of competing hypotheses in a wave (quasi-reversible) regime, subsequently fixing the result in a classical spiking circuit. The motivation derives from the Free Energy Principle (FEP): continuous minimization of variational free energy as the hypothesis space grows may require too many metabolically costly communication events (spike bursts and global broadcast propagation). QRN postulates a two-circuit architecture: (i) a wave layer carries amplitude/probability transfer across a graph of hypotheses (the cognitome) in a potential landscape defined by local prediction errors; (ii) irreversible readout and broadcast fixation occur rarely and, under the QRN assumptions, need not scale with N. Formally, QRN is described by the Lindblad equation on a graph with effective Hamiltonian and moderate dephasing , naturally leading to the ENAQT regime (environment-assisted quantum transport), known from quantum networks.