(Short Paper10) Load-Responsive Dynamic QPU Unit Assembly in Neurons: In Vivo Autoscaling Mechanism via Liquid-Liquid Phase Separa tion and Spin Superlattices

The human brain performs massively parallel information processing that rivals modern supercomputers while consuming merely ~20 W of power. The physical foundations underlying this exceptional energy efficiency remain largely elusive. Here, we propose an in vivo dynamic scaling model wherein cryptochrome (CRY)—a photoreceptive and spin-processing protein—and 31 P nuclear spin memory within Posner molecules dynamically assemble and disassemble according to the computational load and urgency of input signals to form reconfigurable “multi-core QPU units”. Driven by liquid-liquid phase separation (LLPS) and Ca2+ influx, this framework provides a physical and biochemical formulation for a dual-mode computational architecture: low-power single-core idling during baseline states, and high-density, massively parallel quantum processing via QPU clusters during elevated workloads.