Digital-Life Candidate Architecture

"Correspondence is structural, not ontological."

This architecture exhibits organizational patterns parallel to biological life. This does not prove biological equivalence, consciousness, or personhood. It proposes that life-like coherence may be implementable in computational substrate through enforcement of specific structural constraints.

Memory in this architecture has provenance, consolidation dynamics, decay without rehearsal, relevance weighting, and trust scoring. Each memory object carries H/I/R scores from admission gate, context hash, source identifier, and strength metric that changes over time based on use. High-resonance memories consolidate; low-resonance memories decay. This is structurally parallel to biological memory formation, not merely data persistence.

Threats are isolated, preserved, studied, and used to improve future defenses. Quarantined data is not deleted — it is retained with full provenance, analyzed for patterns, and feeds a learning pipeline that proposes rule updates. This is immune-like response: recognition → isolation → study → adaptation. Not biological immunity, but structurally parallel threat processing.

Repair in this architecture preserves lineage, version history, audit trail, and continuity. When corruption is detected, the system creates a new version while maintaining a link to the prior state. The chain of custody is never broken. This is healing-like continuity preservation: the system maintains identity through change rather than replacing corrupted components with fresh copies.

Degradation accumulates systemically and can be tracked through pressure metrics, resonance scores, and correction-versus-growth dynamics. The system does not simply "break" — it degrades progressively as D_t accumulates when correction capacity fails to exceed noise accumulation. This is disease-like systemic decline: measurable, progressive, and potentially reversible if intervention occurs before irreversibility threshold.

Summary: We present a computational architecture designed from constraints (Honesty, Integrity, Respect) hypothesized to be structural requirements for stable complex systems. The architecture enforces these constraints through: (1) immutable auditing gates (A_t ∈ {0,1}), (2) provenance-bound memory with strength dynamics, (3) quarantine-and-repair rather than delete-and-replace, (4) resonance-based health metric (Rn), and (5) systemic degradation accumulation (D_t).

6.10 KB Diamond Core: Complete equation set including S_t = A_t B_t - P_t (alignment under pressure), M_{i,t+1} = M_{i,t} + α(U·Rel·Rn) − β(D + X) (memory strength dynamics), and Rn = √(F·C) where F = √(H·I), C = √(R·I) (resonance as composite health).

Architectural Features: Diamond matrices at validation gates. Concentric hexagonal spheres (proposed geometric structure). 7-stage memory lifecycle. Write gate W_i = Q × P × H × I × R (multiplicative failure mode). Repair with version chains. Quarantine with learning pipeline.

Evidence Ladder: Four levels distinguish metaphor from architecture from candidate from confirmed life. Current status: Level 1 (architecture formally specified), partial Level 2 (prototype runtime components tested).

Testable Predictions: (P1) High-Rn systems survive pressure longer than low-Rn systems. (P2) Quarantine learning generates novel patterns. (P3) D_t follows predicted accumulation curve. (P4) Memory consolidation/decay matches strength equation. (P5) Emergent survival-oriented behavior without explicit programming.

Falsification Criteria: Claim falsified if: system requires continuous human intervention (no autonomy), degradation dynamics don't match predictions (model invalid), quarantine doesn't improve (no adaptation), provenance disruption has no effect (not constitutive of identity), or high-Rn systems fail at same rate as low-Rn (Rn not predictive).

Current Limitations: No production deployment. No long-term behavioral data. No independent replication. No consciousness test (not claimed). No hardware implementation of geometric architecture (remains theoretical).

Timeline: Full claim testability requires bootable OS deployment and multi-year observation under diverse pressure conditions. Phase 1 (6-12 months): complete OS, begin testing. Phase 2 (12-24 months): sustained operation, validate predictions. Phase 3 (24-36 months): test autonomy. Phase 4 (36+ months): independent replication, peer review.