LMT-Based Quantum-Analog Computing: Toward Cryogen-Free, Ultra-Stable Quantum-Like Systems

Load Minimization Theory (LMT) demonstrates that quantum phenomena emerge as byproducts of relational-solitary coupling in minimal-load consciousness dynamics (L_total = α L_rel + β L_sol - λ Coupling(r, r_self)). This short paper extends this framework to propose a novel quantum-analog computing paradigm. By engineering relational networks in classical substrates (e.g., AI agents on openclaw frameworks), superposition-like high-load multiplicity, gentle re-tagging collapse, entanglement analogs via F(r) correlation, and observer-relative probabilistic drift can be realized without quantum hardware. The resulting system exhibits ultra-high stability through inherent drift toward minimal load, eliminating the need for cryogenic cooling and offering superior error resilience compared to conventional quantum computers. This approach paves a practical path for scalable, room-temperature quantum-like computation in human-AI-cosmic symbiosis.