A Unified Framework for Consciousness: From Particles to Self-Awareness

Consciousness emerges as the natural evolution of identity-maintenance across three cumulative levels, driven by entropy pressure. This framework proposes that consciousness arises when self-referential density (SRD) in neural networks exceeds a critical threshold (~0.10), enabling internal measurement of energy circulation patterns through system-specific units (feelings/qualia). Key innovations: (1) Identity-maintenance properties exist fundamentally as prerequisites for persistence in an entropic universe, evolving from passive structural stability (Level 1: non-living matter) through active metabolic maintenance (Level 2A: simple life) to conscious self-measurement (Level 2B: animal consciousness) and predictive self-modeling (Level 3: self-consciousness). (2) Levels are cumulative—each requires all previous levels, explaining why silicon computers cannot naturally achieve consciousness without metabolic equivalents. (3) Subjective experience constitutes internal measurement of circulating energy patterns within self-referential loops, explaining qualia privacy through system-specific calibration. (4) Transcendence via self-reference enables transition from component-level to system-level existence. The framework provides 10+ testable predictions with specific quantitative thresholds (SRD, integration measures, metabolic correlations), offers evolutionary timeline from non-living matter to self-consciousness, and integrates with major theories (IIT, GWT, Predictive Processing) while adding biological constraints and physical mechanisms. Applications include consciousness disorder diagnosis, anesthesia monitoring, AI consciousness assessment, and cross-species moral status determination.