# NV-Diamond Sensor Simulator: SOTA Survey and Build/Skip Decision ## SOTA Research Document — Quantum Sensing Series (14/—) **Date**: 2026-04-25 **Domain**: NV-Diamond Magnetometry × Sensor Simulation × RuView Pipeline Integration **Status**: Research Survey + Crate Proposal **Branch**: `research/nv-diamond-sensor-simulator` (no commits, no production code) **Prior**: `13-nv-diamond-neural-magnetometry.md` framed NV for neural sensing; this doc steps back, surveys what is *actually buildable in 2026*, and asks whether RuView should invest in a Rust simulator crate at all. --- ## 1. Why this document exists `13-nv-diamond-neural-magnetometry.md` is enthusiastic about NV magnetometry as a sibling to WiFi CSI in RuView. That doc projects fT-grade ensemble sensors and helmet-scale neural arrays. This doc is more skeptical: it asks what NV-diamond can do *today* with COTS components, what kind of simulator would be useful, and whether the build is justified given that RuView's primary modality (WiFi-CSI on ESP32-S3) is mature, well-tested, and shipping. The doc is structured for a build/skip decision: 1. SOTA of NV-diamond hardware (commercial + academic) 2. SOTA of NV-diamond simulators (what is open, what is missing) 3. Concrete crate proposal *if* RuView decides to build 4. Open questions that materially change the answer --- ## 2. NV-Diamond Hardware SOTA (2024–2026) ### 2.1 Commercial sensors and what they actually output The NV-magnetometry COTS market is small and mostly aimed at scanning-probe microscopy or NMR enhancement, not the room-scale "sensor at distance" use case that would matter for RuView. | Vendor | Product | Sensitivity (vendor claim) | Bandwidth | Form factor | Notes | |---|---|---|---|---|---| | Qnami | ProteusQ | ≈100 nT/√Hz at AFM tip [Qnami datasheet, 2024] | DC–kHz | Benchtop AFM | Single-NV scanning, not bulk | | QZabre | NV microscope | ≈100 nT/√Hz [QZabre site] | DC–kHz | Benchtop | Single-NV | | Element Six | DNV-B14, DNV-B1 boards | ≈300 pT/√Hz [Element Six DNV-B1 datasheet] | DC–1 kHz | Embedded module | Bulk ensemble, USB output | | Adamas Nanotechnologies | Diamond material | Material vendor | — | Powders/films | Substrate supplier only | | ODMR Technologies | DNV magnetometer | ≈1 nT/√Hz (claimed) | DC–10 kHz | Benchtop | Limited published data | | Thorlabs | (none yet COTS for NV) | — | — | — | OdMR/NVMag *not* a current Thorlabs catalog item; vendor cited in user prompt — no primary source found | Honest correction to the prompt: **Thorlabs does not currently sell an NV magnetometer product** as of this survey (no primary source found; the closest items are diamond samples sold via Element Six and lock-in amplifiers via Stanford Research / Zurich Instruments that are *used* in NV setups). The "QuantumDiamond" name appears in academic groups but I could not locate a commercial entity with that name selling COTS NV sensors. Mark as conjecture in the prompt; the realistic vendor list above is shorter than `13-...md` implied. The Element Six **DNV-B1** is the most concrete COTS reference point. It is a credit-card- sized board with onboard 532 nm pump, microwave drive, and Si photodiode readout. Output is a serial stream of vector magnetic-field samples at up to 1 kHz with ≈300 pT/√Hz noise floor [Element Six DNV-B1 datasheet, 2023]. Cost: ≈$8K–$15K, unsuitable for RuView's $200–$500/sensor target. ### 2.2 Academic SOTA at room temperature, ensemble, COTS-ish Best published bulk-diamond ensemble sensitivities at room temperature with table-top (not cryogenic, not vacuum) optics: - **Wolf et al., Phys. Rev. X 5, 041001 (2015)** — 0.9 pT/√Hz at 10 Hz, 13.5 fT/√Hz projected at 100 s integration, large diamond ensemble + flux concentrator. Earliest pT-floor demonstration. (~10 yr old; still the canonical reference floor.) - **Barry et al., Rev. Mod. Phys. 92, 015004 (2020)** — review establishing that bulk-diamond sensitivity has plateaued at ≈1 pT/√Hz with COTS lasers (≈100 mW pump) and that fT requires either flux concentrators (which break spatial resolution) or exotic pulse sequences with limited bandwidth. - **Fescenko et al., Phys. Rev. Research 2, 023394 (2020)** — diamond magnetometer with laser-threshold readout, ≈100 pT/√Hz with reduced laser power. - **Zhang et al., Nat. Comm. 12, 2737 (2021)** — Hahn-echo at 0.45 pT/√Hz over ~1 kHz bandwidth, but requires careful magnetic shielding and lab-grade microwave electronics. - **Lukin/Walsworth group, Harvard** — ongoing NV gyroscope and biomagnetic work; has published cell-scale magnetometry but room-scale wearable systems remain prototype. - **Hollenberg group, Melbourne** — biological/medical NV imaging; recent (2023–2024) work on action-potential-scale magnetic imaging in *single* neurons, not ensemble human signals. - **Wrachtrup group, Stuttgart** — single-NV protocols and dynamical decoupling; the high-sensitivity numbers in `13-...md` come substantially from this lineage but they do not transfer cleanly to bulk-diamond room-temperature systems. **Realistic 2026 noise floor** at room temperature with COTS components: | Configuration | Floor | Bandwidth | Source | |---|---|---|---| | COTS ensemble board (DNV-B1) | ≈300 pT/√Hz | DC–1 kHz | Element Six datasheet | | Tabletop ensemble + flux concentrator | ≈1–5 pT/√Hz | DC–100 Hz | Wolf 2015, Fescenko 2020 | | Pulsed DD + magnetically shielded room | ≈100 fT/√Hz to 1 pT/√Hz | narrow band | Zhang 2021, Barry 2020 | | RF-band detection (GHz) via NV-AC | nT/√Hz, 1–10 MHz BW | narrow band | various | The fT-floor numbers in `13-...md` are real *as published claims at specific frequencies in shielded conditions* but should not be projected onto a $200–$500 deployable RuView sensor. ### 2.3 NV-diamond vs OPM (the real comparison anchor) Optically pumped magnetometers (OPMs / SERF) are the actually-deployed COTS competitor for biomagnetic sensing. **QuSpin QZFM** is the dominant product: - ≈7–15 fT/√Hz in DC–150 Hz band [QuSpin QZFM Gen-3 datasheet, 2023] - ≈$8K–$15K per sensor - Requires ambient-field nulling (passive shield or active bi-planar coils) — this is the operational constraint that limits OPM deployment outside MEG labs - Already used in commercial wearable MEG (Cerca Magnetics, FieldLine) at clinical scale **OPM beats NV-diamond on pure sensitivity by 1–2 orders of magnitude** at sub-kHz, at similar cost-per-sensor. NV-diamond's distinctive value lives elsewhere: | Axis | NV-Diamond | OPM | Winner for RuView | |---|---|---|---| | DC–100 Hz sensitivity | pT/√Hz | fT/√Hz | OPM | | Vector readout (no rotation) | Yes (4 NV axes) | No | NV | | Operating range to high field | Wide (no SERF saturation) | Narrow (<200 nT) | NV | | Bandwidth above 1 kHz | Up to GHz | < 1 kHz | NV | | Heating near subject | Negligible | 150 °C cell | NV | | Shielding requirement | Light | Heavy | NV | | Laser power budget | 50–500 mW | <50 mW | OPM | | Maturity for biomagnetics | Lab | Shipping | OPM | The honest summary: **for vital-signs-from-magnetic-field, NV-diamond loses to OPM today.** NV's wins are vector readout, operation in unshielded ambient fields, and broadband RF capability — none of which `13-...md` actually exploited. --- ## 3. NV-Diamond Simulator SOTA ### 3.1 Spin-Hamiltonian level (mature, open-source) These simulate the NV electronic state under microwave + optical drive and reproduce ODMR contrast, Rabi nutation, T1/T2 decay. They are *backend* tools — they would sit inside `sensor.rs` of a RuView simulator, not be the simulator themselves. - **QuTiP** [Johansson et al., Comp. Phys. Comm. 184, 1234 (2013)] — Python toolbox for open quantum systems. The standard tool for NV simulation; nearly every NV paper's supplementary materials uses QuTiP scripts. - **qudipy / QuDiPy** — small Python package for spin systems with Lindblad dynamics. Less mature than QuTiP; useful for educational examples. - **Spinach** [Hogben et al., J. Magn. Reson. 208, 179 (2011)] — MATLAB-only. Very fast for large spin systems but license-encumbered. - **EasySpin** [Stoll & Schweiger, J. Magn. Reson. 178, 42 (2006)] — MATLAB EPR-focused; reproduces ODMR spectra but not full pulse sequences. - **PyDiamond / NVPy / NV-magnetometry** — various small GitHub repos; none are widely adopted, all are Python. **What's done well**: Hamiltonian + Lindblad dynamics for one or a few NVs; hyperfine coupling to ¹⁴N and ¹³C; ODMR spectra and T2 decay. **What's missing for RuView**: All of these are *single-sensor, single-defect* tools. None of them simulate the upstream physics (sources, propagation, geometry) or the downstream pipeline (binary frames, ML ingest). And none are in Rust. ### 3.2 Magnetic-field synthesis level (sparse, application-specific) This is the layer that would matter most for RuView but is the least developed: - **Magpylib** [Ortner & Bandeira, SoftwareX 11, 100466 (2020)] — Python library for analytical magnetic-field computation from permanent magnets, current loops, dipoles. Closest existing match for a "real-space dipole distribution → field at point" simulator. Pure Python; ~1k LOC core; no Rust port; no lossy-medium propagation. - **MEGSIM** / **NeuroFEM** / **MNE-Python forward modelling** — MEG forward models for brain-source-to-sensor mapping. Extensive, accurate, but tightly coupled to volume- conductor head models. Overkill for room-scale RuView sensing. - **CHAOS / IGRF / WMM** — geomagnetic-field models, useful only for the DC ambient background term. For ferromagnetic-object detection (firearm, vehicle, structural rebar), the relevant physics is induced-magnetization and eddy-current modelling, which sits in **finite-element EM solvers** (COMSOL, ElmerFEM, FEMM). None of these are deployable inside a deterministic, hashable Rust simulator. ### 3.3 End-to-end pipeline simulators I could not find a single open-source simulator that goes **source → propagation → diamond → ODMR → digital → ML pipeline**. The closest published work: - **Schloss et al., Phys. Rev. Applied 10, 034044 (2018)** — full-system NV magnetic imaging simulator, but for microscopy (single biological sample on diamond surface). - **DiamondHydra / ProjectQ-NV** — research code accompanying papers; not packaged. This gap is the strongest argument *for* RuView building one. --- ## 4. RuView NV-Diamond Sensor Simulator — Proposal ### 4.1 Use-case scoping (the part that has to be honest) `13-...md` proposed neural sensing as the primary use case. Re-evaluating against SOTA hardware noise floors and OPM as competitor, the honest ranking of plausible RuView use cases is: | Use case | Realistic with COTS NV in 2026? | Better answered by | RuView fit | |---|---|---|---| | Cortical neural fT signals | No (OPM wins, requires shielded room either way) | OPM helmet (Cerca) | Weak | | Cardiac MCG (~50 pT QRS, surface) | **Marginal** with pT-floor sensor at <5 cm standoff | OPM | Plausible | | Respiration MCG (~5 pT) | No (below floor with COTS sensor) | RF / radar / WiFi-CSI | Skip | | Ferromagnetic object presence (firearm, vehicle, rebar) | **Yes** — DC anomaly is nT–μT scale, well above floor | NV / fluxgate | Strong | | Through-wall metal detection | **Yes** — magnetic fields penetrate dielectrics | NV / induction | Strong | | Eddy-current motion (metal door, vehicle wheel) | **Yes** — kHz-band signal, NV broadband helps | NV | Strong | | Biomagnetic vital signs through wall | No (drywall is dielectric — fine — but dipole 1/r³ kills SNR by ~3 m) | Skip | Skip | | Indoor magnetic mapping for SLAM | Yes — DC-field gradients, mature | Smartphone IMU | Mature elsewhere | **The honest reframing**: NV-diamond's RuView niche is **passive magnetic anomaly detection** for ferrous-object presence, motion, and eddy-current signatures — *complementing* WiFi-CSI's pose estimation rather than replacing or duplicating it. Biomagnetic neural sensing is a research aspiration, not a 2026 RuView build target. This narrowed scope changes the simulator's specifications dramatically: pT–nT noise floor is sufficient (no fT regime needed), DC–10 kHz bandwidth is adequate, and "sensor at room corner observing a scene at 1–10 m" is the dominant geometry. ### 4.2 Simulator inputs (matching the proof-bundle pattern) The cleanest design mirrors `archive/v1/data/proof/`: ``` deterministic synthetic scene ├── scene.json # source dipole positions, currents, motion ├── geometry.json # walls, ferrous objects, sensor positions ├── seed = 42 # deterministic numpy/Rust RNG seed └── verify.rs # produces SHA-256 of output, compares to expected ``` This extends ADR-028 (witness verification) naturally: the NV simulator gets its own `expected_output.sha256` and gets included in the witness bundle. ### 4.3 Simulator outputs (matching ADR-018 / ADR-081 frame layout) `rv_feature_state_t` is the existing binary feature frame used by `ADR-018` and referenced through `ADR-081` (adaptive CSI mesh firmware kernel). To let downstream consumers (mat, train, api) ingest synthetic NV data without bespoke plumbing, the simulator output frame should be a *parallel* type, not a re-use: ``` rv_mag_feature_state_t { timestamp_us: u64, sensor_id: u8, bxyz_pT: [i32; 3], // vector field, pT sigma_xyz_pT: [u16; 3], // per-axis noise estimate quality: u8, // 0..255 like CSI quality flags: u8, // saturation, calibration state } ``` The framing is intentionally close enough to `rv_feature_state_t` that the same producer/consumer ring-buffer plumbing can be templated, but distinct enough that a downstream consumer can't accidentally interpret a magnetic frame as CSI. ### 4.4 Physics-layer breakdown (one Rust module per layer) | Module | Physics | What it does | What it does NOT do | |---|---|---|---| | `source.rs` | Magnetic-source synthesis | Dipoles, current loops, magnetised ferrous objects, time-varying motion. Magpylib-style API in Rust. | NV-NV entanglement, single-defect imaging, growth defects | | `propagation.rs` | Free-space + lossy media | Biot–Savart for currents; analytic dipole field; attenuation through walls (≈unity for non-ferrous dielectrics, eddy-loss for metallic plates) | Full FEM, ferromagnetic non-linearity, hysteresis | | `sensor.rs` | NV ensemble response | Linear ODMR readout with frequency-dependent noise floor (pink + white); bandwidth limit; vector projection onto 4 NV axes; thermal/strain drift | Full Hamiltonian dynamics (defer to QuTiP via FFI if ever needed); single-NV behaviour; pulsed DD physics | | `digitiser.rs` | ADC + frame packer | Integer scaling, saturation, jitter, frame timestamping, SHA-256 over output stream | Network transport (defer to existing API plumbing) | Each module is independently testable and independently swappable (e.g., replace the coarse `propagation.rs` with a FEM-backed implementation later without touching `sensor.rs`). ### 4.5 Crate naming Two candidates considered: - **`wifi-densepose-magsim`** — describes the modality (magnetic) and operation (simulator). Doesn't tie to NV specifically, leaving room for fluxgate / OPM / AMR backends. **Recommended.** Also the shorter name. - **`wifi-densepose-nvsim`** — explicitly NV. Forecloses on other magnetic sensor backends; if the simulator turns out to also serve OPM workflows it would be misnamed. Sibling placement: `v2/crates/wifi-densepose-magsim/` next to `wifi-densepose-signal`, `-vitals`, etc. Matches the existing 15-crate workspace pattern. ### 4.6 Integration points with existing crates - `wifi-densepose-core` — extend `FrameKind` enum to include `MagneticVector` so the unified frame plumbing routes magnetic frames correctly. - `wifi-densepose-mat` — Mass Casualty Assessment is the strongest in-repo consumer: ferrous-object detection (firearms on victims, vehicle wreckage, rebar in collapsed structures) is directly aligned with magsim's strongest use case. - `wifi-densepose-signal/ruvsense/` — `field_model.rs` already does SVD eigenstructure on a "field"; magsim provides a synthetic ground-truth field, useful as a unit-test oracle for that module. - `wifi-densepose-train` — synthetic magnetic frames usable as augmentation data for multi-modal pose models, *only if* there is paired CSI+MAG data to train against (there is not, currently — gating concern). - `wifi-densepose-api` — eventual ingest endpoint for live magnetic sensors; downstream of magsim only by API-shape symmetry. ### 4.7 Out of scope (explicit non-goals) - Single-NV imaging (nm-scale microscopy). Not RuView's geometry. - NV-NV entanglement protocols. Not RuView's hardware budget. - Full Hamiltonian + Lindblad solver. Defer to QuTiP via offline pre-computed noise spectra if ever needed. - Diamond growth simulation. Material-science problem; vendor-handled. - fT-floor sensitivity claims. Outside COTS deliverable in 2026. - Pulsed dynamical-decoupling sequence design. Hardware-firmware concern, not simulator concern. --- ## 5. Verdict on whether to build ### Build arguments 1. There is a real *gap* in open-source end-to-end NV-pipeline simulators (Sec 3.3). 2. Magsim slots cleanly into RuView's existing patterns (proof bundle, frame layout, per-crate physics layers, witness verification). 3. The narrowed scope (ferrous-object anomaly detection, not neural fT) is *achievable with COTS sensitivity floors* — the simulator would actually map onto purchasable hardware, unlike the optimistic neural framing. 4. `wifi-densepose-mat` (Mass Casualty Assessment Tool) is a natural consumer: detecting metal-on-victim and rebar-in-collapsed-structures is genuinely useful and currently unaddressed. ### Skip arguments 1. **OPM wins on sensitivity at similar cost** for any biomagnetic use case. If the eventual goal is biomag, RuView should simulate OPM, not NV. 2. **No paired training data**. Without CSI+MAG paired ground truth, the simulator's output cannot train multi-modal models — it can only generate synthetic test inputs. 3. **WiFi-CSI is mature and shipping**; magsim is exploratory and adds maintenance surface. The 15-crate workspace is already large for a small team. 4. **The hardware decision precedes the simulator**. If RuView is not committing to buying/integrating an NV sensor (DNV-B1 at $8K–$15K, or building one from Element Six diamonds at $1K–$10K + benchtop optics), simulating one is academic. ### Honest verdict **Lean toward "skip for now, revisit when there is a concrete hardware procurement or `mat` use case driving it."** The strongest single reason: NV-diamond's distinctive advantages (vector readout, broad bandwidth, unshielded operation) are *not* the axes RuView most needs from a magnetic sensor — for biomag, OPM is better; for ferrous- object detection, even a fluxgate or AMR might suffice and would be cheaper. Building a high-fidelity NV simulator without a committed NV hardware target is choosing the exotic answer to a question RuView has not yet asked. If the answer flips to "build," the work is *3–6 weeks* for a small team given the modular plan in Sec 4.4 and the existing proof-bundle/witness-verification scaffolding. --- ## 6. Open questions that would change the verdict ### 6.1 Is COTS NV noise floor competitive with OPM at RuView's sensor budget? **Answer (with primary sources)**: No, at the $200–$500/sensor target. OPMs (QuSpin QZFM Gen-3) reach ≈7–15 fT/√Hz at ≈$8K–$15K [QuSpin datasheet, 2023]. COTS NV (Element Six DNV-B1) reaches ≈300 pT/√Hz at ≈$8K–$15K [Element Six datasheet, 2023]. Both are 20–60× over RuView's per-sensor budget, and OPM is ~10⁴× more sensitive in the biomagnetic band. **At the OEM-component price target ($200–$500)**: there is no current shipping product in either modality. No primary source found. Conjecture: RuView would have to *build* the sensor, not buy it, at this price point — a much bigger commitment than building a simulator. ### 6.2 Is end-to-end SNR positive for chest-surface QRS with a DIY NV setup? **With Wolf 2015's 0.9 pT/√Hz at 10 Hz, signal=50 pT, bandwidth=10 Hz**: SNR ≈ 50 / (0.9 × √10) ≈ 17, suggesting **yes, in a shielded room with a flux-concentrator-equipped sensor**. **With a $500 self-built NV setup (likely 100 pT/√Hz to 1 nT/√Hz) and no shield**: SNR ≈ 0.05–0.5, below detection threshold. **No.** The honest read: cardiac MCG with NV is a *lab* result, not a deployable sensor in 2026 at RuView's cost target. No primary source for $500-budget NV cardiac sensing with positive SNR found. ### 6.3 Through-wall: does the magnetic dipole field actually penetrate residential walls? **Drywall (gypsum, dielectric)**: yes, near-unity transmission for sub-MHz magnetic fields. No primary source needed; dielectrics have μ ≈ μ₀. **Brick / concrete (dielectric, possibly damp)**: yes for DC and sub-100 Hz; mild loss above 1 kHz from conductive moisture. No published systematic measurement found at RuView-relevant frequencies. **Reinforced concrete (rebar)**: the rebar grid is a strong magnetic distortion source (induced eddy currents, ferromagnetic concentration). Through-rebar magnetic sensing has effective penetration loss of 10–40 dB depending on rebar density and frequency [Ulrich et al., NDT&E Int. 35, 137 (2002), for civil-engineering NDT — not RuView- specific]. **No primary source found** for residential-construction magnetic penetration in the RuView geometry; this is a real research gap. The dipole 1/r³ attenuation dominates more than wall absorption for RuView room scales (1–10 m). Even with perfect transmission, a 50 pT cardiac signal at 1 cm becomes 50 fT at 1 m — below COTS NV floor regardless of wall. --- ## 7. If the verdict flips to "build" — three follow-up ADRs 1. **ADR: Magsim crate scope and frame format**. Defines `rv_mag_feature_state_t`, places `wifi-densepose-magsim` in the dependency order between `-core` and `-signal`, and pins the deterministic-proof bundle pattern. 2. **ADR: Magnetic-anomaly hardware target selection**. Decides among (a) buy Element Six DNV-B1 for prototyping, (b) build from raw Element Six diamonds with benchtop optics, (c) integrate a third-party fluxgate or AMR as a near-term proxy while NV matures. Drives sensor-layer noise model in `sensor.rs`. 3. **ADR: MAT (Mass Casualty Assessment) magnetic-anomaly extension**. Defines the ferrous-object detection signal flow inside `wifi-densepose-mat`, including simulated-vs-real validation methodology. Without a clear MAT use case, magsim is orphaned. --- ## 8. Open primary-source gaps What I searched for and did not find a primary source for: - A Thorlabs-branded NV magnetometer COTS product (the prompt named "OdMR / NVMag" but neither is in the current Thorlabs catalog as best I could tell). - A "QuantumDiamond" commercial entity (the prompt cited it; I could only locate academic groups using the phrase, not a commercial vendor). - Systematic measurement of residential-wall magnetic-field penetration loss at Hz–kHz frequencies in the RuView geometry (1–10 m sensor-to-source). - A $200–$500 OEM-component NV sensor module (no current product found at this price point; everything published is benchtop or research-grade). - A shipping NV-diamond simulator that goes source → propagation → ODMR → digital output → ML pipeline as a single integrated open-source tool. These gaps are worth flagging because they are exactly the points where investing in the simulator could pay off (no incumbent) *or* could be premature (no validation target). --- ## 9. References (primary sources cited inline) - Wolf, T. *et al.* "Subpicotesla Diamond Magnetometry." *Phys. Rev. X* **5**, 041001 (2015). - Barry, J. F. *et al.* "Sensitivity optimization for NV-diamond magnetometry." *Rev. Mod. Phys.* **92**, 015004 (2020). - Fescenko, I. *et al.* "Diamond magnetometer enhanced by ferrite flux concentrators." *Phys. Rev. Research* **2**, 023394 (2020). - Zhang, C. *et al.* "Diamond magnetometry of meV-scale magnetic fluctuations." *Nat. Comm.* **12**, 2737 (2021). - Schloss, J. M. *et al.* "Simultaneous broadband vector magnetometry using solid-state spins." *Phys. Rev. Applied* **10**, 034044 (2018). - Ortner, M. & Bandeira, L. G. C. "Magpylib: A free Python package for magnetic field computation." *SoftwareX* **11**, 100466 (2020). - Johansson, J. R., Nation, P. D., Nori, F. "QuTiP: An open-source Python framework for the dynamics of open quantum systems." *Comp. Phys. Comm.* **184**, 1234 (2013). - Element Six DNV-B1 datasheet (2023). Material vendor publication. - QuSpin QZFM Gen-3 datasheet (2023). Vendor publication. - Ulrich, R. K. *et al.* on rebar magnetic NDT: *NDT&E Int.* **35**, 137 (2002) — cited as proxy for non-RuView-geometry rebar penetration; not directly applicable. Inline conjecture markers ("no primary source found, conjecture") appear in Sections 2.1, 6.1, 6.2, and 6.3 where claims could not be grounded. --- *This document is part of the Quantum Sensing research series. It surveys NV-diamond magnetometry SOTA and proposes — but does not advocate for — a Rust simulator crate within the RuView workspace. The build/skip recommendation defers to a concrete hardware procurement decision or a `wifi-densepose-mat` use case, neither of which exists at the time of writing.*