# Measurement notes

The lab notebook for this rig: what was measured, when, on what, and what it
changed. [README.md](README.md) documents how the code works *now*; this file is
the record of how that was arrived at, and it is append-mostly — an entry is
corrected rather than deleted when a later measurement supersedes it.

Every capture cited here predates the current header format and has been
deleted (`*.csv` is gitignored). The numbers stand as measurements; the files
cannot be re-loaded. Re-record before relying on any of it.

**Rigs.** Two hosts appear below. *Bench* is bare metal. *VM* is a
resource-limited virtual machine with virtualised USB passthrough, shared cores
and background load; every host-side ceiling measured there is pessimistic and
labelled as such.

---

## Superseded conclusions

Read this first — these appear as firm recommendations in earlier entries and
are no longer right.

| Earlier conclusion | Superseded by | Now |
|---|---|---|
| "400 kHz measured best; use 400" | three-run repetition at each speed | 750 kHz is fastest and is the default. The 4% edge for 400 kHz sat inside the run-to-run spread of a single short run |
| "Pair cycle count with a TMRC step: 200/0x94, 400/0x95, 800/0x96" | the cycle-count rate model | Hold TMRC fast and use cycle count as the only rate knob. The pairing advice exists only because the rate was being set by TMRC |
| "Abort the run on a missed measurement" | placeholder rows | The run continues and writes a `MISSED` row, keeping `sample_index` contiguous |
| `~84,333 / cc / 3` for the sensor ceiling | fitting overhead separately | `1 / (3 × (cc/90,000 + 68.7 µs))`. The naive constant is not constant — it drifts from 84,429 at cc=100 to 89,191 at cc=1200 |
| "3.3 V vs 3.0 V — indistinguishable" | interleaved A/B at two cycle counts, 2026-08-23 | Indistinguishable in *noise*, yes. But the **scale differs by 7.1%** and the **sample rate by 4.94%**. The earlier entry could not see it because the sensor had moved and the two effects were confounded |
| "60 Hz is 25× the noise floor and dominates every sd figure" | the same session, at 285–299 Hz | True at ~35 Hz where it folds to 9 Hz. At the default rate mains is resolved in band at only **1.7–1.8×** the floor. At cc=400 the dominant line is not mains at all but an **fs/4 artefact** |
| "68.7 µs per-axis overhead" | solving the model per supply | Right in order, wrong in value for this unit: **40.6 µs at 3.006 V, 38.1 µs at 3.353 V**. And the divisor does not hold either — solving both freely gives **88,546 counts/s** at 3.006 V and **92,889** at 3.353 V. Holding it at 90,000 and solving for the overhead alone gives 58.9 µs at cc=100 and 113.6 µs at cc=400, fitting neither. Both terms are per-unit and supply-dependent; `calibrate.py` carries them |
| "`× (1 + rate_error)` corrects gain, cutting the spread to 3.1%" | referencing the correction to a measured oscillator | **The 3.1% was two errors cancelling.** `rate_error` is measured against the *nominal* model, whose error is cycle-count dependent (+0.84% at cc=100, −0.99% at cc=400, same supply), and that partly cancelled the cycle-count gain difference. Referenced properly the figure is **4.9%**. The matched-cycle-count contrasts are unaffected either way |
| "gain ∝ V^−0.65, i.e. rate^−1.47; mechanism unresolved" | freeing the gain offset | **The 1.47 was absorbing a gain-offset error.** Table 3-1's `0.3671·cc + 1.5` implies gain ∝ (cc + 4.086) counts; measured on this unit it is 0.90 (LDO) and −0.09 (3V3). With the offset free, an exponent of exactly **1** is fully consistent — which is what an oscillator-clocked collection interval predicts. Correcting both leaves **2.48%**, inside the 2.3–3.1% movement floor |
| "the per-axis overhead is constant in counts (0.7σ) and changes as a time (2.8σ)" | propagating the thermal drift properly | Those σ came from a half-drift error bar chosen without justification. Propagated, the overhead is 3.60 ± 0.30 counts against 3.54 ± 0.15, and neither reading is excluded. The clean test is the supply rate ratio across cycle counts: oscillator-clocked sits **0.3σ** from it, fixed-time **1.2σ**. Favoured, not proven — drift is the limit |
| "the within-run drift could be used to correct gain in post-processing" | the coupling test, then σ_y(τ) | **Closed — do not reopen.** Gain does not follow the within-run rate: the measured slopes are **+0.08 to +0.35** where gain ∝ 1/f demands **−1**. The mechanism is that gain is set by the *ratio* of the MagI2C internal clock to f_LR, both on the same die, so a thermal shift is common-mode and divides out. That is what PNI's "stable over temperature" claim in §2 actually protects, and it is why 1241 ppm of rate drift produces no measurable gain drift. The drift is real and well resolved; it simply does not reach the gain |
| "the rate measurement is limited by host read jitter, so a longer window is always better" | σ_y(τ) on the four captures | Wrong in both halves. White jitter predicts σ/rate = √12·σ_t/(√n·T), or sub-ppm at 30 s; measured, σ_y bottoms out at **8–14 ppm around τ = 2–10 s** and then *rises*. The floor is correlated host-side noise, 10–30× the naive figure, and past ~10 s a longer window makes the estimate worse, not better — it starts measuring the drift instead of the rate |

---

## First working capture

10 s, cycle count 200, TMRC 0x96, sensor stationary on a desk beside a PC.

```
349 samples over 10.02 s -> 34.8 Hz
  X: mean  +6.473 uT   sd 177 nT
  Y: mean +50.914 uT   sd 106 nT
  Z: mean +18.944 uT   sd 396 nT
  |B|: mean 54.709 uT  sd 245 nT
  sample interval: 28.78 ms, sd 1.52 ms
```

- **Rate.** 34.8 Hz against a nominal ~37 Hz is in spec: §5.2.1 quotes roughly
  7% one-sigma tolerance on the update rate.
- **Magnitude.** 54.7 µT sits inside the 25–65 µT band for Earth's field, which
  is the real confirmation that the gain and the int24 decode are right.
- **Noise** is well above the 15 nT Table 3-1 quotes for cycle count 200, and is
  not a driver problem — most likely proximity to a PC and the USB adapter.
- **Drift.** All three axes fell monotonically over the 10 s (Z most, ~1.3 µT),
  so |B| went from 55.5 to 54.3 µT. Consistent with thermal settling after AVDD
  is first powered; coil DC resistance moves 0.4 %/°C (Table 3-3). Allow a
  warm-up before trusting absolute values.

Nothing here is calibrated: these are raw sensor outputs with no hard- or
soft-iron correction, so individual axis values reflect local distortion as much
as Earth's field.

---

## Supply A/B: 3.3 V adapter vs 3.0 V LDO — indistinguishable

> **Superseded in the noise conclusion only, and wrong on scale.** The
> interleaved re-run below finds the scale differs by 7.1% and the sample rate by
> 4.94%. This entry could not separate either from the sensor having moved.

Two 60 s captures on the bench, cycle count 200, TMRC 0x96, 400 kHz.

| | 3V3 adapter | 3.0 V LDO |
|---|---|---|
| \|B\| | 40,345 nT | 42,731 nT (**+5.9%**) |
| sd \|B\| absolute | 35.4 nT | 38.5 nT (+8.8%) |
| sd \|B\| **fractional** | **878 ppm** | **900 ppm** (+2.5%) |

**Compare noise fractionally, not absolutely.** The measured scale moved 5.9%
between the runs, and a scale change carries the noise with it, so most of the
absolute sd difference is an artefact. Normalised, the two supplies differ by
2.5% — indistinguishable on single 60 s captures.

That is the expected outcome. Table 3-5 allows 50 mV<sub>PP</sub> of supply
ripple and the LP5907's ~6.5 µV RMS sits roughly 1000× inside it, as did the
adapter rail most likely. Supply quality was never the binding constraint; the
magnetic environment is.

**The 5.9% scale change cannot be attributed to the supply from this data.** The
sensor also moved: the field direction rotated 6.16°, and the per-axis ratios
(X 1.136, Y 1.051, Z 0.870) spread by 26.6%, where a pure gain change would
scale all three identically. |B| is preserved under rotation but not under
translation through a field gradient, so movement and gain are confounded here.

There is still reason to expect 3.0 V to read *more accurately*, but it comes
from the datasheet rather than these captures: Table 3-1 footnote 1 establishes
every specification — including the gain fit behind `tesla_per_count` — at
3.0 V, noting that performance "will differ" elsewhere. At 3.3 V the gain is an
extrapolation off the calibration point.

This experiment is what `compare.py` was written for; it refuses to attribute a
magnitude difference to gain unless both movement checks pass.

### Designing an A/B supply test

- **Clamp the sensor and never touch it.** Swapping supplies must not disturb
  it. This is the single thing that invalidated the first attempt.
- **Interleave A/B/A/B**, never all of A then all of B. Drift over a session is
  large enough to swamp the effect, and only interleaving lets adjacent pairs be
  differenced.
- **Repeat 3–4 times per configuration.** With one run each, a 2.5% difference
  is indistinguishable from run-to-run variation.
- **Let it thermally settle** before each run. Coil resistance moves 0.4 %/°C
  (Table 3-3), so an unsettled sensor drifts through the measurement.
- Record the configuration with `--note`, so the comparison does not depend on
  filenames surviving:

```bash
./.venv/bin/python logger.py --duration 300 --note "3V3"     --output a1.csv
./.venv/bin/python logger.py --duration 300 --note "3V0 LDO" --output b1.csv
./.venv/bin/python compare.py --group note *.csv
```

---

## 60 Hz mains folds into the band

At ~35 Hz the largest spectral feature by far was a line near 9 Hz reaching
100–125 nT/√Hz against a 4–5 nT/√Hz broadband floor — **25× the noise floor**.

> **The 25× is specific to that rate and that site.** Measured at 285–299 Hz on
> 2026-08-23, with mains resolved in band rather than folded, the 60 Hz line
> reaches only **1.7–1.8×** the floor, and at cycle count 400 the dominant line
> is an fs/4 artefact rather than mains. The mechanism below is unchanged; the
> "dominant term" framing is not general.

It is 60 Hz aliasing, proven by making it move:

| capture | fs | observed peak | predicted 60 Hz alias |
|---|---|---|---|
| 3V3 | 34.7565 Hz | 9.5063 Hz | 9.5129 Hz |
| 3.0 V LDO | 34.5557 Hz | 9.0725 Hz | 9.1114 Hz |
| long run | 34.5783 Hz | 9.1764 Hz | 9.1566 Hz |

A real 9 Hz magnetic signal would sit still. This one moves with the sample
rate: `fs` changed by 0.20 Hz and the peak moved 0.43 Hz — the ×2 sensitivity of
a second-order fold, exactly as predicted.

The RM3100 has **no anti-alias filter** — cycle-count integration is a boxcar
with a poor stopband — so out-of-band interference folds in freely.

**Sampling faster resolves it instead.** At 150 Hz (Nyquist 69.3 Hz) mains lands
in band and the strongest line sits at **59.923 Hz**, observed directly. At
75 Hz it folds to 9.304 Hz against a 9.233 Hz prediction, with only 4 nT/√Hz
left at 60 Hz because that frequency is no longer sampled. This is why the
default configuration runs at ~282 Hz: at that rate mains *and* its second
harmonic are inside the band and can be notched afterwards, which no amount of
filtering can do to an alias.

---

## Overnight run: 13.2 h, 1.63 M samples

Cycle count 200, TMRC 0x96. **Acquisition integrity was perfect** — sample index
contiguous across all 1,635,055 rows, system clock monotonic with no NTP steps,
no malformed rows, no int24 saturation, no missed measurements (worst DRDY
bracket 11.0 ms of 27.03 ms, 41% of margin). Both problems in the data were
outside the logger.

**1. The first ~1.5 h and the last ~1 h are contaminated by handling.** |B|
reaches 198,268 nT — five times Earth's field — in bursts around t+0.44 h.
Hourly |B| sd tells the story:

| hours | \|B\| sd | usable |
|---|---|---|
| 0–1 | 3,750 nT | no — handling |
| 2–10 | **34–40 nT** | yes |
| 11–12 | 41–68 nT | marginal |
| 13 | 247 nT | no — activity resumed |

A 5-minute slice from the middle of the quiet window gave |B| = 42,132 nT with
sd 32.5 nT (771 ppm).

**2. A single rate does not describe a 13-hour capture.** One slope across the
whole run leaves a residual sd of 5.3 s and a 22.8 s span. Hour-by-hour fits
show the oscillator speeding up monotonically:

| hour | fitted period | vs run mean |
|---|---|---|
| 2 | 29.0187 ms | +1254 ppm |
| 6 | 28.9794 ms | −102 ppm |
| 12 | 28.9187 ms | −2195 ppm |

That is ~2,500 ppm of rate variation across the quiet hours — thermal, as
expected of an RC oscillator. So **long captures cannot be given a single
frequency axis**; spectra must be computed on windows short enough that the rate
is constant, via `Capture.restrict()`.

This is what `drift_limited` and the separate reporting of read jitter and fit
residual exist for. Over 5 minutes the residual is 3.7 ms; over 8.5 hours it is
2,356 ms — while read jitter stays 0.21 ms in both. Conflating the two would
have read as a 20,000× worse host.

**Drift-limited beyond a second.** A 769 s window of the same run: per-axis sd
rises to 214–284 nT while the broadband floor barely moves (5.1–5.7 nT/√Hz). The
extra spread is low-frequency drift, not broadband noise — the Allan deviation
bottoms at ~13 nT near τ = 0.12 s and climbs steadily after.

---

## Host-side rate ceilings

Two fixes roughly doubled the achievable rate.

### 1. Two USB round trips per register read → one

Reading a register as a pointer write plus a separate read — the form the manual
draws (§4.5.2, §5.8.4) — costs two round trips. The part accepts a **repeated
START**, so `ch347.write_read()` does it in one. Measured at 400 kHz:

| | separate | combined |
|---|---|---|
| `data_ready()` | 0.652 ms | **0.350 ms** |
| `read_raw()` | 0.838 ms | **0.548 ms** |

### 2. The GIL, not the OS scheduler

Even after that, `logger.py` stalled ~10 ms at 150 Hz while the *same sampling
loop with no writer thread* peaked at 3.1 ms (p99.9 = 2.9 ms, zero threshold
crossings in 2079 samples). The sampler releases the GIL inside each USB
transfer and must re-acquire it, waiting up to Python's default **5 ms** switch
interval while the writer holds it. Setting `sys.setswitchinterval(0.0005)` cut
the worst bracket from 9.96 ms to 5.65 ms and made 150 Hz pass.

Worth remembering generally: with a latency-sensitive loop and a helper thread,
the default GIL switch interval *is* the jitter floor.

### 3. Splitting the writer off the sampling thread

The same 60 s capture yielded 22,558 samples (376 Hz) with inline writing and
28,864 (481 Hz) with the writer split off — about **28%**.

### Measured ceilings (VM, cycle count 50, 400 kHz)

| TMRC | Nominal | Result | Worst DRDY bracket |
|---|---|---|---|
| 0x92 | 600 Hz | fail | 1.86 ms of 1.67 ms (112%) |
| 0x93 | 300 Hz | fail | 3.45 ms of 3.33 ms (104%) |
| 0x94 | 150 Hz | borderline | 5.65 / 5.95 / 6.53 / 7.19 ms of 6.67 ms |
| 0x95 | 75 Hz | clean, 69.2 Hz | 2.63–5.16 ms of 13.33 ms (20–39%) |
| 0x96 | 37 Hz | clean, 34.7 Hz | 3.30–8.56 ms of 27.03 ms (12–32%) |

> **These ceilings are host-specific and pessimistic** — VM, virtualised USB,
> shared cores, load average 2.76 at the time of the one 150 Hz failure. The
> *shape* carries over (the limit is host round-trip latency, not I²C bandwidth
> or the sensor), but the numbers must be re-measured on the machine that will
> run the capture. The "% of margin used" line `logger.py` prints after every
> run is the number to watch.

### The bus is never the constraint

Per sample the bus carries a DRDY poll plus a results read — 150 bit-times —
against a host cost 2–3× larger.

| | 400 kHz | 100 kHz |
|---|---|---|
| bus time per sample | 0.375 ms | 1.50 ms |
| as % of a 28.86 ms period (37 Hz) | **1.3%** | 5.2% |
| as % of a 7.21 ms period (150 Hz) | **5.2%** | 20.8% |
| measured host cost | 0.89–0.98 ms | — |

That puts the bus-limited ceiling near 1100 Hz, roughly double the sensor's own
562 Hz three-axis maximum at cycle count 50 — so absent host stalls, zero misses
is always achievable. Every miss observed has been a host stall.

### Bus speed, three runs each at cycle count 228

| bus | bus time | host cost | implied USB overhead |
|---|---|---|---|
| 100 kHz | 1.500 ms | 2.03–2.19 ms | ~0.63 ms |
| 400 kHz | 0.375 ms | 0.88–0.95 ms | ~0.55 ms |
| **750 kHz** | 0.200 ms | **0.78–0.80 ms** | ~0.59 ms |

Host cost is `bus time + ~0.6 ms` of fixed USB round-trip latency, so a faster
bus helps but cannot go below that floor. An earlier note claimed 400 kHz
benchmarked faster than 750; that rested on a single short run whose 4%
difference was inside the run-to-run spread and does not survive repetition.
400 kHz remains a sane fallback if 750 proves marginal on long wiring.

---

## Timing: how the miss detector was arrived at

**The read-to-read interval is not a usable threshold.** On the VM it reaches
37 ms against a 28.8 ms period — a 29% overshoot from host stalls alone — while
the DRDY bracket stays under 10 ms. The first implementation thresholded the
interval and aborted a perfectly healthy capture at sample 88.

**Period calibration is worth 100×.** Counting how many grid points passed
unseen inside a bracket needs the real period, and the TMRC table value is 6–9%
out on this unit:

| | period | error |
|---|---|---|
| nominal (TMRC table) | 27.03 ms | −6.4% |
| **calibrated (1 s)** | **28.8849 ms** | **0.068%** |
| whole-run fit (25 s) | 28.8653 ms | — |

**Counting needs the interval, detection needs the bracket.** Fit residual after
adopting the two-signal scheme:

| capture | lost | residual |
|---|---|---|
| 37 Hz clean | 0 | **0.019 periods** |
| 150 Hz clean | 0 | 0.082 periods |
| 150 Hz under CPU load | 0 | 0.444 periods |
| 300 Hz | 10 | 1.241 periods |

The load case is the one that shows the design paying off: the bracket reached
119% of threshold, so a stall genuinely occurred, but the interval showed only
one period had elapsed — nothing was lost. The older `int(bracket/period)`
estimator would have inserted a spurious placeholder and slipped the index from
there on. At 300 Hz the ambiguous counter fired 19 times.

**Run-to-run stability.** Fitted periods land 6.0–6.6% below nominal, and two
consecutive 60 s runs agreed to **0.017%**, so a single-slope drift correction
is sound over at least a minute.

---

## Rate sweep

`sweep.py` end to end. Every target from 1 to 128 Hz landed within 0.1%
(columns as of the run; the current tool also prints duty):

```
  target   measured     err     cc    LSB/uT  nT/count    noise  bus use
      1H      1.00H  +0.0%  29769   10929.7     0.091    1.21n    0.0%
      8H      8.01H  +0.1%   3718    1366.4     0.732    3.41n    0.3%
     32H     32.00H  -0.0%    927     341.8     2.926    6.83n    1.2%
    128H    127.99H  -0.0%    229      85.6    11.687   13.75n    4.8%
    256H    249.23H  -2.6%    113      43.0    23.265   19.57n    9.3%  2 lost
```

256 Hz is where the VM gives out; everything below it is exact. Noise past cycle
count ~400 is extrapolation — Table 3-1 ends there.

**Cycle count sets the ceiling, not TMRC.** Measured at 400 kHz:

| Cycle count | Measured | Table 3-1 predicts |
|---|---|---|
| 200 | 152 Hz | 147 Hz |
| 100 | 297 Hz | 283 Hz |
| 50 | 538 Hz | 533 Hz |

**The manual contradicts itself here and Table 3-1 is the correct one.** The
§5.2.1 note claims cycle count 200 allows a "~430 Hz" three-axis update rate;
Table 3-1 gives 440 Hz *single-axis* and says to divide by 3, i.e. ~147 Hz.
Measurement backs Table 3-1 at all three cycle counts.

**When the cycle count governs, TMRC is irrelevant** — cc=400 gave 73.85 Hz at
TMRC 0x92 and 73.86 Hz at 0x94. Varying only cc at TMRC 0x94:

| cc | measured | governed by | duty |
|---|---|---|---|
| 50 | 138.53 Hz | TMRC | 25% |
| 200 | 138.84 Hz | boundary | 99% |
| 400 | 73.83 Hz | cycle count | 100% |
| 800 | 37.09 Hz | cycle count | 100% |

**Idling costs sensitivity.** Reaching ~130 Hz two ways:

| | rate | cc | duty | ASD |
|---|---|---|---|---|
| TMRC-governed (cc=50, 0x94) | 138.5 Hz | 50 | **23%** | 3.42 nT/√Hz |
| cycle-count-governed (cc=228) | 128.5 Hz | 228 | **98%** | 2.39 nT/√Hz |

Same chip, same field, same per-sample physics — the difference is idle time,
and it is why the current model holds TMRC fast and uses cycle count alone.

**Equal duty means equal noise.** Two configurations at ~100% duty and very
different rates:

```
cc200 @150Hz  138.77 Hz  LSB 13.35 nT  ASD 2.98 nT/rtHz  (66% bracket margin)
cc800 @37Hz    34.72 Hz  LSB  3.39 nT  ASD 3.26 nT/rtHz  (10% bracket margin)
```

Near-identical spectral density, as the equal-duty argument predicts — so the
choice between them is bandwidth versus resolution, not noise.

**Low cycle counts are dominated, not fast.** cc=50 reached the same 138.8 Hz as
cc=200 on the VM — both host-limited, not sensor-limited — while idling 75% of
the time and quantising 3.8× more coarsely. Its extra sensor speed is capability
the host cannot collect.

---

## 60 s capture at maximum rate (office rig, historical)

28,864 samples, 481 Hz, cycle count 50, 400 kHz. The sensor was nudged by hand
at t ≈ 41 s, so statistics are split around that:

| Axis | sd, 0–40 s | sd, 47–60 s | step across the event |
|---|---|---|---|
| X | 84 nT | 85 nT | +280 nT |
| Y | 388 nT | 376 nT | +217 nT |
| Z | 187 nT | 198 nT | +232 nT |
| \|B\| | 369 nT | 358 nT | +313 nT |

- **The step was the sensor being physically moved**, confirmed at the time, not
  an electrical artefact. A norm shift does not by itself imply an external
  source changed: |B| is preserved under rotation in a uniform field, but a
  translation through a gradient samples a different local field. Near a PC the
  gradients are steep (§4.2.2: field falls off as 1/distance³), so a few
  centimetres is ample for the +313 nT seen here. Treat a |B| change as "not a
  pure rotation", nothing more.
- **Noise is strongly axis-dependent** — Y is 4.6× X (388 vs 84 nT) and stable
  across the event, so it is not a consequence of the disturbance. The coils are
  nominally identical, so this points at orientation relative to a local noise
  source rather than a sensor fault. X at 84 nT is within ~3× of the 30 nT
  Table 3-1 quotes for cycle count 50; Y is ~13×.
- **Timing was jittery**: intervals averaged 2.08 ms (481 Hz) with sd 1.09 ms
  and a 19.6 ms worst case. This capture predates the chip-grid time base, so it
  is unsuitable for spectral work without resampling. A capture taken today
  carries an exact grid regardless of read jitter.

---

## Supply ripple: what the manual does and does not say

Table 3-5 gives a flat 50 mV<sub>PP</sub> ripple limit on AVDD and DVDD with
**no frequency qualifier**, and no transfer function from ripple to field error
— no µT-per-mV, no PSRR, no ripple-vs-noise curve.

Slow drift should matter less than fast ripple, though this is inference from
the described architecture rather than an explicit claim. §4.1 describes the
output as "the difference in the time to complete the measurement for each
bias" — a differential measurement across forward and reverse coil bias — and §2
claims measurements are "stable over temperature and inherently free from offset
drift". Anything common to both half-measurements largely cancels, so supply
variation slower than one measurement cycle should be rejected far better than
noise near the ~180 kHz LR oscillation.

Unverified on this rig: whether the breakout carries local decoupling, and what
the CH347's 3V3 rail ripple actually measures against the 50 mV limit.

---

## Interleaved supply A/B, 2026-08-23 — the scale factor, measured

Four captures, LDO / 3V3 / LDO / 3V3 at cycle counts 100, 100, 400, 400, ~6
minutes each, rails measured at the board: **3.006 V** and **3.353 V**. Full
write-up, figures and raw output in
[Noise_Floor_Testing/NOISE_FLOOR.md](Noise_Floor_Testing/NOISE_FLOOR.md); this is
the summary and the things that changed the tooling.

**The oscillator moves with the supply.** +4.94% from 3.006 V to 3.353 V,
measured independently at two cycle counts and agreeing to **0.04%** — V^+0.44.
This is the cleanest number in the session because, unlike |B|, it cannot be
contaminated by the sensor moving.

**|B| moves the other way, by −7.1%** (−3,245 nT), consistent across both cycle
counts to 0.74%. Exactly ratiometric with the rail would be V^−1; measured is
V^−0.65, and correcting by the rail overshoots by +3.5 to +4.3% against a
run-to-run reproducibility of 2.3–3.1%. Correcting by the **measured sample
rate** instead leaves −2.6 to −1.9%, inside that floor — and needs nothing
external, since the logger already calibrates the period every run. Applying both
corrections is clearly wrong (+8.7%): the rate change *is* the supply change seen
through the oscillator, so stacking them counts it twice.

**The sensor still moved**, 2.8–23° of rotation between pairs. |B| survives a
rotation, so this does not invalidate the above, but translation through a
gradient would, and only a clamped re-run can bound that.

**Cycle count 400 carries an artefact that cycle count 100 does not.** Tones at
exactly fs/4 and fs/2 of each capture's *own* rate — the two cc=400 runs differ
by 4.9% in rate and each peaks at its own fs/4, so it is locked to the sampling
rather than to any frequency. On one axis it reaches 2.43 nT at 25.7σ. Mechanism
unresolved; it is not a host-side period, since 4 samples is 52.1 ms at one rate
and 54.7 ms at the other.

It also **grows with the supply**: comparing the rotation-invariant vector
magnitude of the tone, 3V3 is **1.217 ± 0.086×** the LDO, agreeing between the
fs/4 and fs/2 harmonics. That excludes a fixed digital pattern (which would be
1.000, +2.5σ) and external pickup (0.935, +3.3σ), and sits between V and V²,
which two rail voltages cannot separate.

**Every capture drifts through its own thermal warm-up** — 186 to 1241 ppm,
monotonically downward, measured by re-fitting the rate on sub-windows
(`calibrate.rate_stability`). That is the error bar under every timing figure
here, and the reason the collection-interval mechanism is favoured rather than
established. Let the rig settle before a run that matters.

**That drift is the sample rate, not the field**, and the distinction is worth
keeping because the natural explanations for "drift" on a magnetometer are
geomagnetic. `dt_true` is fitted from the host clock against sample index, so
nothing magnetic can reach it, and the pattern confirms it: every run starts high
and ends low, then the *next* run starts high again. A diurnal trend would run
continuously across the session; this resets at each `logger.py` invocation.

The **field** drift within a run is separate and probably is diurnal: |B| moves
−1.4 to −1.8 nT/min in three of the four runs, in a consistent direction, which
is the right order for Sq variation. It cannot be the 2.48% residual — that is
1,166 nT against ~40 nT of diurnal across the whole 26-minute session.

**The sensor moved during a run, not only between them.** LDO/cc400 rotates
**0.49°** across its own run, ten times the quietest, and that is the same run
carrying 485 nT of Z drift at nearly constant |B| — which is rotation, not field.
The rig was not restrained and had to be handled to move the 3 V jumper between
runs, so this is expected rather than surprising; it is why the residual is
attributed to movement.

**Filtering and decimating a fast capture matches sampling slowly**, which the
README had been asserting without evidence. Decimating a cc=100 capture by 4
changes its own broadband floor by **+0.3 to +0.5%** — a comparison with no
second run in it, so no gain or position difference to confound it. It is also
strictly better: the decimated path carries none of the fs/4 artefact, and a
proper anti-alias filter removes 60 Hz before it can fold, which sampling slowly
cannot.

**The dither question is settled at cycle count 100.** 0.65–0.81 LSB per sample,
and averaging 1,024 samples reaches 0.035–0.050 LSB — within 1.5–2.1× of ideal.
A comb in the residual histogram is not evidence against this: the residual of an
integer-valued signal is a comb at one LSB by construction, and its sharpness
tracks only how far that axis drifted.

**What this changed in the tooling.** Four estimator bugs surfaced, all of which
would have biased a supply comparison:

- `compare.py` scored each capture over its own band, so a 299 Hz run was judged
  over 3–135 Hz and a 73 Hz one over 3–33. One common band now, chosen to sit
  inside the slowest path compared *including decimated ones*.
- Welch segments were a fixed sample count, so captures at different rates got
  different numbers of segments; the median of a Welch estimate is biased low by
  an amount that depends on that count. A fixed 20 s segment duration now.
- Broadband noise was reported only in absolute nT/√Hz, which credits a low gain
  as a low noise floor. Reported fractionally too, and the figures are fractional.
- `characterize.py` autoscaled every panel, so a quiet capture and a noisy one
  drew identical-looking plots. Fixed axes now.

---

## Open questions

- Re-run the LDO comparison with the sensor **clamped**, and in an order that is
  not degenerate. The 2026-08-23 session used L,3,L,3 against cycle counts
  100,100,400,400, which makes `t = supply + 2·cc` exactly — supply, cycle count
  and a linear drift cannot all three be fitted. L,3,3,L breaks it.
- Identify the **fs/4 artefact** at cycle count 400. A cc=200 run at both
  supplies would say whether it scales with cycle count or appears at a threshold.
- Fix `rm3100.AXIS_OVERHEAD_S`: 68.7 µs against 38–41 µs measured on this unit,
  which puts the cc100:cc400 rate ratio 1.9% out.
- Compare |B| against IGRF/WMM for the capture site (39.661262° N,
  82.604173° W, 255 m). Not a calibration standard — indoor hard and soft iron
  are unknown and nothing here is corrected — but it is the only absolute
  reference available, and it would say which rail reads closer to right.
- Deal with 60 Hz coupling at source — standoff distance, then a repeat
  characterisation — rather than only sampling fast enough to see it.
- Reliability over extended runs on bare metal, where the VM ceilings above do
  not apply.