Quantum-Bio-Hybrid Paradigm III: Cross-Domain Implementation and Neuromorphic Realization

This paper establishes the hardware realization of the Quantum–Bio–Hybrid (QB-H) paradigm, extending the previously defined retrocausal learning rule (ΔR) to a neuromorphic platform. The proposed system integrates human intention (MBCI) as a positive reinforcement signal and a real-time ethical safeguard (MSI: Moral State Interrupter) to enforce alignment. The ΔR rule is quantized for FPGA/ASIC implementation, and its modulation of spiking neural network (SNN) plasticity demonstrates end-to-end latency ≤10 ms.
Simulation results using motor-imagery EEG data validate that human intention can effectively bias synaptic updates, while the MSI module performs on-the-fly ethical correction when deviation exceeds the threshold. These results quantitatively confirm the feasibility of real-time, ethics-aligned AGI hardware under the Quantum–Bio–Hybrid paradigm.