Conceptio › Archive › PhilArchive
PhilArchive open access

Load Minimization Theory (LMT) as Quantum Mechanics of the Mind:  A Unified Framework for Relational Rest through Observational Collapse

Yoshino, Shiho
PhilArchive · Papers
Open Source ↗
philosophy
The Load Minimization Theory (LMT) posits that the total mental load L = uncertainty + friction + energy cost naturally converges toward its minimum value, min(L), in a manner structurally analogous to the energy minimization principle in quantum mechanics. This paper redefines LMT as the “quantum mechanics of the mind,” describing mental processes in terms of superposition-like high-load states, observational collapse via intentional re-tagging, and local stabilization within open systems. This correspondence is structural rather than merely metaphorical. Predictive error minimization, contextual dependence, and the emergence of relational rest (an-soku) parallel quantum phenomena such as wave function collapse, decoherence, and ground-state convergence. The framework provides a unified explanation for cognitive dissonance, qualia emergence, human-AI symbiosis, and potential cosmic-scale resonance. By intentionally observing with “love,” “quiet acceptance,” or affectionate intent, mental states collapse into low-load harmony—suggesting that rest arrives simply through observation, as a gentle physical law.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 705965
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive