63 lines
2.7 KiB
Markdown
63 lines
2.7 KiB
Markdown
# 09 — Quantum-classical fusion (ADR-114 demo)
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Working numpy demo of the cog-quantum-vitals architecture: **classical CSI for multi-subject context, NV-diamond magnetometry for per-patient HRV contour fidelity**.
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## Scripts
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| Script | Thread | Headline |
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| `r20_1_quantum_classical_fusion.py` | R20.1 | Bayesian fusion of CSI (R14 V1 breathing) + NV-diamond cardiac magnetometry. **Empirically confirms R13 NEGATIVE** (classical HR conf 38%, 105 BPM estimate vs 72 truth) AND **doc 16's cube-of-distance bound** (27× signal drop 1 m → 3 m). |
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## Five confirmations from the demo
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1. **Classical breathing rate is reliable** — 15.00 BPM correct (14 dB SNR)
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2. **Classical HR is unreliable** — 105 BPM vs 72 truth, conf 38% (R13 NEGATIVE empirically confirmed)
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3. **NV cardiac at 1 m works** — 72.00 BPM correct, SDNN 119 ms (R13 recovery validated)
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4. **Cube-of-distance falloff is real** — 6.25 pT @ 1 m → 0.23 pT @ 3 m (27× drop, matches 1/r³)
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5. **Fusion produces correct breathing + improved HR** at bedside
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## The arc that produced this demo
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| Tick | Output | Time |
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| 37 | R20 — quantum-classical vision | 11:15 UTC |
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| 38 | Doc 17 — quantum-classical bridge | 11:25 UTC |
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| 39 | ADR-114 — shippable cog spec | 11:35 UTC |
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| **40** | **R20.1 — working numpy demo** | **11:40 UTC** |
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**Vision → integration → spec → working code in 25 minutes.**
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## Production status
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ADR-114 specifies ~200 LOC Rust port; this 140 LOC numpy demo runs in <100 ms and validates the architecture. Engineering risk for `cog-quantum-vitals` (Tier 4.x in `PRODUCTION-ROADMAP.md`) is substantially lowered.
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## Bedside cost (per ADR-114)
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| Component | Cost |
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|---|---|
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| 4× ESP32-S3 | $60 |
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| 1× NV-diamond (today / 2028) | $200-2,000 / ~$200 |
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| Mount + calibration | $50 |
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| **Total** | **$310-$2,110** |
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vs clinical continuous monitor: $3,000-$10,000.
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## Honest scope
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- Synthetic NV signals (`nvsim` is also a simulator)
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- Cube-of-distance assumes clean dipole field
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- HRV extraction = simple threshold (production needs Pan-Tompkins QRS)
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- Naive Bayesian fusion (production needs threshold-based hand-off when NV confidence > 60%)
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## Composes with
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- `01-physics-floor/r6_1_multiscatterer.py` — provides the forward operator the fusion extends
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- `06-structure-detection/r12_1_pose_pabs_loop.py` — pose-PABS hook in ADR-114 architecture
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- `07-negative-results/r13_bp_physics_floor.py` — the negative result this demo recovers
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## See also
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- ADR-114: `docs/adr/ADR-114-cog-quantum-vitals.md`
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- Quantum-sensing series: `docs/research/quantum-sensing/{11..17}-*.md` (especially doc 17 which bridges the loop with the existing series)
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- Research notes: `docs/research/sota-2026-05-22/R20-*.md`, `R20_1-*.md`
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