mirror of
https://github.com/proffesor-for-testing/agentic-qe.git
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Dragan Spiridonov
6b249c034f
Implements 23 tasks across 4 phases per docs/implementation/ruvector-integration-plan.md: Phase 1 — Foundation (make what we have faster): - Native HNSW backend via @ruvector/router (150x search speedup, ADR-081) - Metadata filtering layer with composable AND/OR/NOT/FIELD expressions - Temporal tensor compression (Int8Array quantization, 4x memory reduction) - Deterministic golden-ratio dithering for cross-platform reproducibility - 15 feature flags (all default false) with CLI profiles Phase 2 — Intelligence (make agents smarter): - Neural TinyDancer router with REINFORCE policy gradient (ADR-082) - SONA three-loop enhancement (MicroLoRA 0.18μs/adapt via WASM) - Cross-domain transfer learning with Thompson Sampling (ADR-084) - Regret tracking with log-log regression growth classification Phase 3 — Safety (make agents trustworthy): - Sheaf-gated test validation via prime-radiant CohomologyEngine - Coherence-gated agent actions (3-filter pipeline, ADR-083) - Witness chain audit trail with SHA-256 hash linking - HNSW health monitoring with spectral analysis Phase 4 — Differentiation (make AQE unique): - Cognitive container export/import (RVF v2) - DAG attention scheduler for dependency-aware test ordering - CNN visual regression with spatial pooling embeddings - Behavior tree orchestration (Sequence/Selector/Parallel) - Reasoning QEC with majority-vote consensus - Browser QE dashboard scaffolding Also: remove obsolete v2-to-v3-migration test (source already removed), add ADR-081 through ADR-085, research docs, benchmarks, and integration test suites for all 4 phases. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
61 lines
3.2 KiB
Markdown
61 lines
3.2 KiB
Markdown
# RuVector Quantum Computing & Solver Crates Research
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## Crates Covered
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1. ruqu-core - Quantum circuit simulator (5 backends, SIMD, QEC)
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2. ruqu-algorithms - VQE, Grover, QAOA, Surface Code
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3. ruqu-exotic - Quantum-classical hybrid: reasoning QEC, swarm interference
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4. ruqu-wasm - Browser quantum simulation (25 qubits, 180KB)
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5. ruQu - Coherence gating platform (256-tile fabric, PERMIT/DEFER/DENY)
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6. ruvector-solver - 7 sublinear sparse algorithms with auto-routing
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7. ruvector-solver-node / ruvector-solver-wasm - Bindings
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8. ruvector-mincut - Dynamic minimum cut (arXiv:2512.13105, O(n^0.12))
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9. ruvector-mincut-node / ruvector-mincut-wasm - Bindings
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10. ruvector-mincut-gated-transformer - Lambda-controlled transformer inference
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11. ruvector-mincut-gated-transformer-wasm - Browser coherence-gated inference
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## Key Findings
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### ruqu-core
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- 5 backends: StateVector (exact, 32 qubits), Stabilizer (millions of qubits), Clifford+T, TensorNetwork (MPS), Hardware profiles
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- Cost-model planner auto-routes circuits to optimal backend
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- Hybrid decomposition: partition by entanglement structure for multi-backend execution
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- Subpolynomial QEC decoders: O(d^{2-epsilon} * polylog(d))
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### ruqu-exotic (Most Novel for AQE)
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- **Reasoning QEC**: Quantum error correction applied to AI reasoning chains
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- **Swarm Interference**: Quantum-inspired multi-agent consensus via constructive/destructive interference
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- **Interference Search**: Amplitude-based vector similarity (fundamentally different from cosine)
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- **Reversible Memory**: Quantum uncomputation for perfect undo/redo
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- **Memory Decay**: T1/T2 decay modeling for temporal confidence in cached results
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### ruvector-solver
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- 7 algorithms: Neumann, CG, Forward Push PPR, Backward Push, Hybrid Random Walk, TRUE, BMSSP Multigrid
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- SolverRouter auto-selects based on matrix sparsity profile
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- AVX2 SIMD SpMV with fused residual+norm (3x less memory traffic)
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- Arena allocator for zero per-iteration heap allocation
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### ruvector-mincut (Dec 2025 Breakthrough)
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- First production implementation of arXiv:2512.13105
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- O(n^0.12) amortized update time (verified)
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- 448+ tests passing
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- Advanced: Link-Cut Trees, Euler Tour Trees, graph sparsification
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- 256-core agentic chip support (6.7KB/core)
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- SNN module: temporal attractors, strange loops, causal discovery
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### ruvector-mincut-gated-transformer
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- Lambda (min-cut) as first-class transformer control signal
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- 4-tier system: Normal (1x) -> Reduced (2-3x) -> Safe (5-10x) -> Skip (50-200x)
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- Spike-driven scheduling: 87x energy efficiency
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- EAGLE-3 speculative decoding: 3-5x speedup
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- FlashAttention tiling: O(n) memory
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- KV cache INT4 (RotateKV): 8-16x compression
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- Every inference produces explainable witness
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## AQE Integration Opportunities
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1. **Reasoning QEC**: Validate and correct AI agent reasoning chains
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2. **Swarm interference**: Better multi-agent consensus mechanisms
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3. **MinCut monitoring**: Real-time agent network health via O(n^0.12) updates
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4. **PageRank prioritization**: Rank test cases/agents by graph importance
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5. **Lambda-gated execution**: 4-tier compute allocation based on system health
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6. **Memory decay modeling**: Confidence decay for cached test results over time
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