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wifi-densepose/examples/research-sota/09-quantum-fusion
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rUv fecb1da252
research(R20.2): threshold-based hand-off — works at 0.5 m, harmonic gap at 1 m surfaces Pan-Tompkins requirement (#746) 
Implements R20.1's catalogued refinement: when NV conf > 60% AND
amplitude > 3 pT, trust NV entirely.

Mixed result (5 distances):
- 0.5 m: NV=72.00 ✓, smart=72.0 (+0.0 error, NV trusted) ✓
- 1.0 m: NV=144 (harmonic!), smart trusts wrong NV (+72 BPM error)
- 1.5 m+: falls back to weighted (NV conf below threshold)

Production lesson: the threshold-based policy is correct in spirit
but incorrect with simple FFT rate estimator (picks harmonics).
Production needs:
1. Harmonic rejection (Pan-Tompkins QRS or autocorrelation)
2. Cross-check vs breathing band
3. Per-frame plausibility window

R20.1's 'production needs Pan-Tompkins' note is confirmed BINDING,
not nice-to-have, before threshold hand-off can ship.

ADR-114 implementation budget refined: +30-50 LOC for Pan-Tompkins.

Five-step quantum arc:
- R20 vision (tick 37)
- Doc 17 bridge (tick 38)
- ADR-114 spec (tick 39)
- R20.1 working demo (tick 40)
- R20.2 threshold refinement (this tick)

Production ADR-114 cog now has all known refinements catalogued
BEFORE any Rust code is written.

Honest mixed result — catalogue-then-revisit pattern works:
R20.1 flagged production gap; R20.2 attempted fix; fix surfaced
deeper gap (harmonic rejection). Three layers of refinement.
 		2026-05-22 07:57:48 -04:00
..
README.md docs(examples/research-sota): add main + 9 sub-folder READMEs (follow-up to #744) (#745) 2026-05-22 07:54:19 -04:00
r20_1_fusion_results.json chore: organise examples/research-sota/ into 9 thematic folders with READMEs (#744) 2026-05-22 07:52:57 -04:00
r20_1_quantum_classical_fusion.py chore: organise examples/research-sota/ into 9 thematic folders with READMEs (#744) 2026-05-22 07:52:57 -04:00
r20_2_threshold_handoff.py research(R20.2): threshold-based hand-off — works at 0.5 m, harmonic gap at 1 m surfaces Pan-Tompkins requirement (#746) 2026-05-22 07:57:48 -04:00
r20_2_threshold_results.json research(R20.2): threshold-based hand-off — works at 0.5 m, harmonic gap at 1 m surfaces Pan-Tompkins requirement (#746) 2026-05-22 07:57:48 -04:00

README.md

09 — Quantum-classical fusion (ADR-114 demo)

Working numpy demo of the cog-quantum-vitals architecture: classical CSI for multi-subject context, NV-diamond magnetometry for per-patient HRV contour fidelity.

Scripts

Script Thread Headline
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).

Five confirmations from the demo

  1. Classical breathing rate is reliable — 15.00 BPM correct (14 dB SNR)
  2. Classical HR is unreliable — 105 BPM vs 72 truth, conf 38% (R13 NEGATIVE empirically confirmed)
  3. NV cardiac at 1 m works — 72.00 BPM correct, SDNN 119 ms (R13 recovery validated)
  4. Cube-of-distance falloff is real — 6.25 pT @ 1 m → 0.23 pT @ 3 m (27× drop, matches 1/r³)
  5. Fusion produces correct breathing + improved HR at bedside

The arc that produced this demo

Tick Output Time
37 R20 — quantum-classical vision 11:15 UTC
38 Doc 17 — quantum-classical bridge 11:25 UTC
39 ADR-114 — shippable cog spec 11:35 UTC
40 R20.1 — working numpy demo 11:40 UTC

Vision → integration → spec → working code in 25 minutes.

Production status

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.

Bedside cost (per ADR-114)

Component Cost
4× ESP32-S3 $60
1× NV-diamond (today / 2028) $200-2,000 / ~$200
Mount + calibration $50
Total $310-$2,110

vs clinical continuous monitor: $3,000-$10,000.

Honest scope

  • Synthetic NV signals (nvsim is also a simulator)
  • Cube-of-distance assumes clean dipole field
  • HRV extraction = simple threshold (production needs Pan-Tompkins QRS)
  • Naive Bayesian fusion (production needs threshold-based hand-off when NV confidence > 60%)

Composes with

  • 01-physics-floor/r6_1_multiscatterer.py — provides the forward operator the fusion extends
  • 06-structure-detection/r12_1_pose_pabs_loop.py — pose-PABS hook in ADR-114 architecture
  • 07-negative-results/r13_bp_physics_floor.py — the negative result this demo recovers

See also

  • ADR-114: docs/adr/ADR-114-cog-quantum-vitals.md
  • Quantum-sensing series: docs/research/quantum-sensing/{11..17}-*.md (especially doc 17 which bridges the loop with the existing series)
  • Research notes: docs/research/sota-2026-05-22/R20-*.md, R20_1-*.md