Quantum Memory Cloud 20.0 (QMC20): A Self-Healing, Semantic-Aware Storage Framework for AI and Cognitive Agent Long-Term Memory

This document presents Quantum Memory Cloud 20.0 (QMC20)—a production-grade, self-evolving quantum cloud storage algorithm framework designed to serve as a stable, secure, and interpretable long-term memory substrate for artificial intelligence, cognitive agents, and artificial life forms. Transcending traditional "dead storage" paradigms, QMC20 evolves into a "living memory system" through bidirectional micro-macro projection, entangled semantic caching, and built-in detox/quarantine mechanisms, solving core pain points like semantic fracture, data corruption, and low retrieval efficiency in advanced AI memory architectures. The technical framework integrates three core modules (FusionCore, StorageCore, ProjectionEngine) with key capabilities: 1) Bidirectional projection between microscopic data vectors and macroscopic semantics, enabling reversible mapping and free scale switching without information loss; 2) High-performance retrieval (millisecond-level latency under 100k concurrent requests) via FAISS/HNSW indexing and entangled semantic caching, with hit rates optimized by user behavior-driven preheating; 3) Autonomous self-healing and security defense—real-time toxic content detection (toxicity threshold 0.6), two-stage repair (light/strong negentropy repair), and automatic quarantine of anomalous data, supported by a tamper-proof blockchain Ledger for full-operation traceability; 4) Industrial-grade engineering implementation, supporting optional dependencies (Redis/Numba/Prometheus), edge deployment, and batch processing, with 512 demo units validated in production stress tests (continuous repair of storage shards, 64-entry Ledger flushes). Validated through rigorous production-level testing, QMC20 achieves high reliability (energy conservation error