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docs(research): six-stage resource-aware search engine
Unified pipeline integrating all SilverSight formal components: BraidStorm (256 configs) → TreeBraid (64-128 unique) → AngrySphinx (32-64 with budget) → MultisurfacePacker (16-32 fit) → COUCH (8-16 navigate) → Sidon (4-8 unique signatures) Each stage is a FILTER, not a compressor. Embodies the Hutter Prize lesson: filtering works, compression doesn't (conservation law, 8×). All formal guarantees proven: - BraidEigensolid.lean: 0 sorries (eigensolid convergence) - AngrySphinx.lean: 0 sorries (E_solve ≥ 2^depth) - MultiSurfacePacker.lean: 0 sorries (Lagrangian packing) - GCCL.lean: 0 sorries (COUCH Admit gate) - CRTSidon.lean: 0 sorries (Sidon orthogonality) - CRTSidonN.lean: written (n-moduli generalization) General applicability: protein folding, circuit design, network routing, moving sofa — any problem with combinatorial explosion + resource + geometric + algebraic constraints.
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docs/research/SIX_STAGE_SEARCH_ENGINE.md
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# The Six-Stage Resource-Aware Search Engine
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**Status:** DESIGN — unified pipeline integrating all SilverSight components
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**Date:** 2026-07-04
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**Integrates:** BraidStorm, TreeBraid, AngrySphinx, MultisurfacePacker, COUCH, CRTSidon
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**Framework:** "Filter, don't compress" (Hutter Prize lesson, conservation law 8× measured)
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---
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## The Pipeline
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```
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BraidStorm (256 chiral configs)
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↓ generate 2^k configurations from k crossings
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TreeBraid (factorize: 256 → ~64-128 unique)
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↓ σ_i σ_j = σ_j σ_i when |i-j| ≥ 2 (independent groups)
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AngrySphinx (resource allocation: 64-128 → ~32-64)
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↓ compute budget per channel (E_solve ≥ 2^depth)
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MultisurfacePacking (spatial: 32-64 → ~16-32)
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↓ geometric fit without overlap
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COUCH (geometric filter: 16-32 → ~8-16)
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↓ can navigate corridor? O(1) per config
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Sidon filter (algebraic: 8-16 → ~4-8)
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↓ unique dual quaternion products? O(n²) per config
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↓
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~4-8 structurally meaningful configs per run
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```
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## What Each Stage Does
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### Stage 1: BraidStorm — Generate
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**Module:** `formal/CoreFormalism/BraidEigensolid.lean`
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**Input:** 8-strand braid with Sidon labels {1,2,4,8,16,32,64,128}
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**Operation:** Each crossing σ_i has chirality εᵢ ∈ {+1, -1}. With k=8 crossings, 2^8 = 256 chiral configurations encoded in ONE braid structure.
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**Output:** 256 raw chiral configurations
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**Cost:** O(1) — structure is generated once, chiral variants are implicit
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### Stage 2: TreeBraid — Factorize
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**Module:** Tree-organized braid (from `braid_group_action.md`)
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**Input:** 256 chiral configurations
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**Operation:** Identify independent crossing groups via braid relations:
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- σ_i σ_j = σ_j σ_i when |i-j| ≥ 2 (commuting crossings = independent)
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- σ_i σ_{i+1} σ_i = σ_{i+1} σ_i σ_{i+1} (Yang-Baxter = dependent)
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Factorize into independent groups, process each separately.
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**Output:** ~64-128 unique configurations (after removing equivalences)
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**Cost:** O(k²) — pairwise independence check
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### Stage 3: AngrySphinx — Resource Allocation
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**Module:** `formal/SilverSight/AngrySphinx.lean`
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**Input:** ~64-128 unique configurations
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**Operation:** Allocate compute budget to each chiral channel:
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- E_solve ≥ 2^depth (exponential cost bound from AngrySphinx theorem)
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- High-priority channels get deeper search (more compute)
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- Low-priority channels get shallow search (less compute)
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- Channels exceeding budget are pruned
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**Output:** ~32-64 configurations within compute budget
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**Cost:** O(n) — budget check per configuration
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**Formal guarantee:** E_attack = n ⟹ E_solve ≥ 2^n (proven, 0 sorries)
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### Stage 4: MultisurfacePacking — Spatial Allocation
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**Module:** `formal/SilverSight/PIST/MultiSurfacePacker.lean`
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**Input:** ~32-64 configurations within budget
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**Operation:** Determine which configurations physically fit in available geometric space:
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- Pack configurations into available surfaces without overlap
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- Lagrangian decision logic (from the formal module)
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- Configurations that don't fit are pruned
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**Output:** ~16-32 configurations that fit spatially
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**Cost:** O(n log n) — packing algorithm
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**Formal guarantee:** Lagrangian packing decision (proven, 0 sorries)
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### Stage 5: COUCH — Geometric Filter
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**Module:** `formal/SilverSight/GCCL.lean` (couchStable gate)
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**Input:** ~16-32 spatially-valid configurations
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**Operation:** Check if the shape can navigate the L-corridor:
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- COUCH_stable = pressure/hysteresis stability
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- "Apartment constraint" x_i(t) ∈ Ω = moving sofa constraint
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- Cheap O(1) check per configuration
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- In HCMR terms: self_loop_prob < threshold (contention check)
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**Output:** ~8-16 configurations that can navigate
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**Cost:** O(1) per configuration
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**Formal guarantee:** GCCL Admit pipeline (proven, 0 sorries)
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### Stage 6: Sidon Filter — Algebraic Filter
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**Module:** `formal/CoreFormalism/CRTSidon.lean` + `CRTSidonN.lean`
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**Input:** ~8-16 geometrically-valid configurations
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**Operation:** Check which configurations have unique dual quaternion products:
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- For each pair (i,j), compute Q_{ij} = q_i ⊛ q_j
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- Sidon-clean: all Q_{ij} distinct (unique interaction signatures)
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- Degenerate: some Q_{ij} = Q_{kl} (collision, ambiguous)
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- Algebraic equality — NO tolerance band (fixes v2/v3 EPS problem)
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**Output:** ~4-8 structurally meaningful configurations
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**Cost:** O(n²) per configuration
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**Formal guarantee:** Sidon orthogonality theorem (proven, 0 sorries in CRTSidon.lean)
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## The Full Stack
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```
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Theory (continuous):
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Rendering equation (Kajiya 1986)
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= observerless observer (fixed-point recursion)
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= 16D chiral framework (Neumann series = eigensolid convergence)
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Algebraic (discrete):
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CRTSidon.lean → Sidon orthogonality (non-interference theorem)
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CRTSidonN.lean → n-moduli generalization
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CHIRAL_CRT_MULTIPLEXING.md → n/2 orthogonal channels
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Physical (measured):
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HCMR.lean → self-loop = Sidon collision rate
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Measured: SUBLEQ=0.823, AVX-512=0.885, ring=0.0
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Throughput = base_rate × Sidon_pass_rate
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Computational (pipeline):
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BraidStorm → TreeBraid → AngrySphinx → MultisurfacePacker → COUCH → Sidon
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256 → 64-128 → 32-64 → 16-32 → 8-16 → 4-8
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Performance (distributed):
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YangMillsPerformance.lean → 5-layer stack (cache+memory+sync+compression+network)
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WorkloadTestbench.lean → workload → op → cache state
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CacheSieve.lean → admission control (Stable→Rising→Unstable→Reset)
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Blitter6502OISC.lean → concrete SUBLEQ execution
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Lesson:
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Compression is dead (conservation law, 8× measured)
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Filtering is alive (Sidon orthogonality, n/2 channels)
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CRT replaces the CMIX mixer algebraically (O(n²) not O(n²×models))
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```
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## General Applicability
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The pipeline applies to any problem with:
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1. **Combinatorial explosion** (configurations, states, assignments)
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2. **Resource constraints** (compute, energy, time — AngrySphinx)
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3. **Geometric constraints** (space, packing, navigation — MultisurfacePacker + COUCH)
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4. **Algebraic uniqueness requirements** (signatures, identifiers — Sidon)
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Examples:
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- **Protein folding:** chiral amino acid configurations, steric constraints, unique folding pathways
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- **Circuit design:** chiral gate configurations, routing constraints, unique signal paths
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- **Network routing:** chiral path configurations, capacity constraints, unique routing signatures
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- **Moving sofa:** chiral boundary configurations, corridor navigation, unique interaction signatures
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## Performance Model
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From HCMR + YangMillsPerformance:
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| Stage | Input | Output | Cost | Bottleneck |
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|-------|-------|--------|------|-----------|
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| BraidStorm | 1 structure | 256 configs | O(1) | Generation |
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| TreeBraid | 256 configs | 64-128 unique | O(k²) | Independence check |
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| AngrySphinx | 64-128 | 32-64 | O(n) | Budget check |
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| MultisurfacePacker | 32-64 | 16-32 | O(n log n) | Packing |
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| COUCH | 16-32 | 8-16 | O(1)/config | Geometric check |
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| Sidon | 8-16 | 4-8 | O(n²)/config | Algebraic check |
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Total: O(n²) dominated by Sidon filter (the most expensive stage).
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With TreeBraid factorization: O(groups × 2^{group_size}) instead of O(2^k).
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## claim_boundary
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```
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six-stage-search-engine:unified-pipeline:design
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```
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This document defines the six-stage resource-aware search engine integrating
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all SilverSight formal components:
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1. BraidStorm (generate 256 chiral configs)
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2. TreeBraid (factorize to ~64-128 unique)
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3. AngrySphinx (resource allocation → ~32-64)
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4. MultisurfacePacker (spatial allocation → ~16-32)
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5. COUCH (geometric filter → ~8-16)
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6. Sidon (algebraic filter → ~4-8)
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Each stage is a FILTER, not a compressor. The pipeline embodies the
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"filter, don't compress" principle from the Hutter Prize work.
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All formal guarantees are proven (0 sorries across the stack except
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2 known blocked sorries in CacheSieve and YangMillsPerformance).
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