Add research index synthesizing all 12 documents (14,322 lines)
Master index for RF Topological Sensing research compendium covering: graph theory foundations, CSI edge weights, attention mechanisms, transformers, sublinear algorithms, ESP32 hardware, contrastive learning, temporal graphs, resolution analysis, system architecture, quantum sensors, and quantum biomedical sensing. Includes key findings, proposed ADRs (044, 045), and 5-phase implementation roadmap. https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
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# RF Topological Sensing — Research Index
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## SOTA Research Compendium
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**Generated**: 2026-03-08
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**Total Documents**: 12
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**Total Lines**: 14,322
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**Branch**: `claude/rf-mincut-sensing-uHnQX`
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---
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## Core Concept
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RF Topological Sensing treats a room as a dynamic signal graph where ESP32 nodes
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are vertices and TX-RX links are edges weighted by CSI coherence. Instead of
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estimating position, minimum cut detects where the RF field topology changes —
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revealing physical boundaries corresponding to objects, people, and environmental
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shifts. This creates a "radio nervous system" that is structurally aware of space.
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---
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## Document Index
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### Foundations (Documents 1-2)
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| # | Document | Lines | Key Topics |
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|---|----------|-------|------------|
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| 01 | [RF Graph Theory & Mincut Foundations](01-rf-graph-theory-foundations.md) | 1,112 | Max-flow/min-cut theorem, Stoer-Wagner/Karger algorithms, Fiedler vector, Cheeger inequality, spectral graph theory, comparison to classical RF sensing |
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| 02 | [CSI Edge Weight Computation](02-csi-edge-weight-computation.md) | 1,059 | CSI feature extraction, coherence metrics, MUSIC/ESPRIT multipath decomposition, Kalman filtering of edges, noise robustness, normalization |
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### Machine Learning (Documents 3-4)
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| # | Document | Lines | Key Topics |
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|---|----------|-------|------------|
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| 03 | [Attention Mechanisms for RF Sensing](03-attention-mechanisms-rf-sensing.md) | 1,110 | GAT for RF graphs, self-attention for CSI, cross-attention fusion, differentiable mincut, antenna-level attention, efficient attention variants |
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| 04 | [Transformer Architectures for Graph Sensing](04-transformer-architectures-graph-sensing.md) | 896 | Graphormer/SAN/GPS, temporal graph transformers, ViT for spectrograms, transformer-based mincut prediction, foundation models for RF, edge deployment |
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### Algorithms (Document 5)
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| # | Document | Lines | Key Topics |
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|---|----------|-------|------------|
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| 05 | [Sublinear Mincut Algorithms](05-sublinear-mincut-algorithms.md) | 1,170 | Sublinear approximation, dynamic mincut, streaming algorithms, Benczúr-Karger sparsification, local partitioning, Rust implementation |
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### Hardware & Systems (Documents 6, 10)
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| # | Document | Lines | Key Topics |
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|---|----------|-------|------------|
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| 06 | [ESP32 Mesh Hardware Constraints](06-esp32-mesh-hardware-constraints.md) | 1,122 | ESP32 CSI capabilities, 16-node topology, TDM synchronization, computational budget, channel hopping, power analysis, firmware architecture |
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| 10 | [System Architecture & Prototype Design](10-system-architecture-prototype.md) | 1,625 | End-to-end pipeline, crate integration, DDD module design, 100ms latency budget, 3-phase prototype, benchmark design, ADR-044, Rust traits |
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### Learning & Temporal (Documents 7-8)
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| # | Document | Lines | Key Topics |
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|---|----------|-------|------------|
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| 07 | [Contrastive Learning for RF Coherence](07-contrastive-learning-rf-coherence.md) | 1,226 | SimCLR/MoCo for CSI, AETHER-Topo extension, delta-driven updates, self-supervised pre-training, triplet edge classification, MERIDIAN transfer |
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| 08 | [Temporal Graph Evolution & RuVector](08-temporal-graph-evolution-ruvector.md) | 1,528 | TGN/TGAT/DyRep, RuVector graph memory, cut trajectory tracking, event detection, compressed storage, cross-room transitions, drift detection |
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### Analysis (Document 9)
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| # | Document | Lines | Key Topics |
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|---|----------|-------|------------|
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| 09 | [Resolution & Spatial Granularity](09-resolution-spatial-granularity.md) | 1,383 | Fresnel zone analysis, node density vs resolution, Cramér-Rao bounds, graph cut resolution theory, multi-frequency enhancement, scaling laws |
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### Quantum Sensing (Documents 11-12)
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| # | Document | Lines | Key Topics |
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|---|----------|-------|------------|
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| 11 | [Quantum-Level Sensors](11-quantum-level-sensors.md) | 934 | NV centers, Rydberg atoms, SQUIDs, quantum illumination, quantum graph algorithms, hybrid architecture, quantum ML, NISQ applications |
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| 12 | [Quantum Biomedical Sensing](12-quantum-biomedical-sensing.md) | 1,157 | Biomagnetic mapping, neural field imaging, circulation sensing, coherence diagnostics, non-contact vitals, ambient health monitoring, BCI |
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---
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## Key Findings
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### Resolution
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- 16 ESP32 nodes at 1m spacing → **30-60 cm** spatial granularity
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- Dual-band (2.4 + 5 GHz) → **6 cm** theoretical coherent limit
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- Information-theoretic limit: **8.8 cm** for dense deployment
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### Computational Feasibility
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- Stoer-Wagner on 16-node graph: **~2,000 operations** per sweep
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- At 20 Hz: **0.07%** of one ESP32 core
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- Full pipeline CSI → mincut: **< 100 ms** latency budget
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### Quantum Enhancement
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- NV diamond: 100-1000× sensitivity improvement at room temperature
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- Rydberg atoms: self-calibrated, SI-traceable RF field measurement
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- D-Wave quantum annealing: native QUBO solver for graph cuts
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### Biomedical Extension
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- Non-contact cardiac monitoring at 1-3m with quantum sensors
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- Coherence-based diagnostics: disease as topological change in body's EM graph
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- Same graph algorithms (mincut, spectral) apply to both room sensing and medical
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---
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## Proposed ADRs
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- **ADR-044**: RF Topological Sensing (Document 10)
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- **ADR-045**: Quantum Biomedical Sensing Extension (Document 12)
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## Implementation Phases
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1. **Phase 1** (4 weeks): 4-node POC — detect person in room
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2. **Phase 2** (8 weeks): 16-node room — track movement boundaries < 50 cm
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3. **Phase 3** (16 weeks): Multi-room mesh — cross-room transition detection
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4. **Phase 4** (2027-2028): Quantum-enhanced — NV diamond + ESP32 hybrid
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5. **Phase 5** (2029+): Biomedical — coherence diagnostics, ambient health
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