wifi-ruview/examples/research-sota

SOTA Research Loop — Examples Overview

Pure-numpy reference implementations from the 2026-05-22 autonomous SOTA research loop. Every script is self-contained, prints headline numbers, and writes a machine-readable JSON result file alongside.

Folder map

Folder	Threads	What it covers
01-physics-floor/	R1, R6, R6.1	Bedrock physics — ToA CRLB, single-scatterer Fresnel, multi-scatterer forward model
02-placement/	R6.2 family (7 sub-ticks)	Antenna placement search — 2D / 3D / multi-anchor / chest-centric / multi-subject
03-spatial-intelligence/	R5, R7	Subcarrier saliency + Stoer-Wagner mincut adversarial defence
04-rssi/	R8, R9	RSSI-only counting + RSSI fingerprint K-NN
05-cross-room-reid/	R3 arc (3 ticks)	Cross-room person re-identification — naive, physics-informed, embedding-level
06-structure-detection/	R12 arc (3 ticks)	RF-weather eigenshift → PABS → pose-PABS closed loop (NEGATIVE → POSITIVE)
07-negative-results/	R13	Physics-floor scrutiny — why contactless BP from CSI doesn't work
08-verticals/	R10, R11	Exotic vertical physics — wildlife (foliage attenuation) and maritime (through-bulkhead)
09-quantum-fusion/	R20.1	Quantum-classical Bayesian fusion (ADR-114 cog-quantum-vitals demo)

Running any example

All scripts are pure NumPy. No external dependencies beyond numpy itself.

python examples/research-sota/01-physics-floor/r6_fresnel_zone.py
python examples/research-sota/02-placement/r6_2_5_multi_subject.py
# etc.

Each script:

• Prints headline numbers to stdout
• Writes <script_name>_results.json next to itself
• Runs in <2 minutes on a laptop (most run in <10 seconds)

Cross-folder dependency graph

01-physics-floor  ──┐
       │            │
       ▼            │
02-placement   ◀────┤
       │            │
       ▼            │
03-spatial-intel ◀──┤
       │            │
       ▼            │
06-structure-detection  ◀──┘
       │
       ▼
09-quantum-fusion  (composes 01+03+06)

04-rssi      (independent, uses 01 forward model)
05-cross-room-reid   (uses 01+03)
07-negative-results  (uses 01)
08-verticals  (uses 01)

Headline findings

Finding	Source
93× sensing-coverage lift from physics-aware placement	02-placement (R6.2)
9.36× intruder-detection lift from pose-PABS closed loop	06-structure-detection (R12.1)
100% coverage of 1-4 occupant household at N=5 anchors	02-placement (R6.2.5)
~50% breathing-band SNR cost from realistic body multi-scatterer	01-physics-floor (R6.1)
RSSI alone preserves 95% of full-CSI person count	04-rssi (R8)
Stoer-Wagner mincut catches 3/3 adversarial spoofs	03-spatial-intelligence (R7)
Contactless BP/HRV-contour: 5 dB short, physically blocked	07-negative-results (R13)
NV-diamond cardiac magnetometry recovers R13 at bedside	09-quantum-fusion (R20.1)

Related loop output

• Research notes: docs/research/sota-2026-05-22/R{1..20}-*.md
• Per-tick summaries: docs/research/sota-2026-05-22/ticks/tick-{1..40}.md
• Production roadmap: docs/research/sota-2026-05-22/PRODUCTION-ROADMAP.md
• ADRs from the loop: docs/adr/ADR-{105..109,113,114}-*.md
• Quantum-sensing series: docs/research/quantum-sensing/{11..17}-*.md

Honest scope

All scripts are synthetic-physics derivations, not bench measurements. Real ESP32-S3 deployments may diverge from these numbers by 5-30% due to multipath, hardware tolerance, environmental drift. Bench validation is the critical next step for any production use; see PRODUCTION-ROADMAP.md Tier 2.3.

Reading order for newcomers

1. Start with 01-physics-floor/R6 (Fresnel forward model) — bedrock for everything else
2. Then 02-placement/R6.2.5 (multi-subject) — practical placement recipe
3. Then 06-structure-detection/R12.1 (pose-PABS) — the security feature
4. Then 09-quantum-fusion/R20.1 (Bayesian fusion) — the future direction