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REVIEW 4 major objections 6 minor 30 references

The deployment of a geomagnetic variometer station as auxiliary instrumentation for the study of Unidentified Aerial Phenomena

T0 review · 4 major / 6 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read The paper's central claim is that a solar-powered, buried vector magnetometer records one-second geomagnetic field variations at a quality comparable to a nearby national reference observatory, validating the project's approach to…

desk verdict A transparent, reproducible engineering report whose core claim holds; the INTERMAGNET-grade comparison is visual only and needs quantification before that line is published. read the letter →

arxiv 2507.11355 v1 pith:2D4VISCT submitted 2025-07-15 astro-ph.IM

Foteini Vervelidou , Alex Delacroix , Laura Domine , Ezra Kelderman , Sarah Little , Abraham Loeb , Eric Masson , Wes A. Watters
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Abigail White
This is my paper · ORCID
classification astro-ph.IM
keywords geomagneticvariometervectorfluxgatemagnetometermagneticanomalydetectionunidentifiedaerialphenomenaUAPinstrumentationstorminstrumentcalibration1-seconddata
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper reports the commissioning of the project's first geomagnetic variometer station: a three-axis fluxgate magnetometer buried at a quiet rural site and powered by solar panels, built to look for magnetic anomalies that might accompany reported UAP encounters. Its central claim is that the station's one-second recordings match, after a baseline shift, the recordings of a nearby national reference observatory closely enough that the data quality is comparable to that observatory's. The evidence includes quiet-day traces that agree to a few nT, a partial record of the May 2024 extreme geomagnetic storm, and controlled local interference tests, including detection of a roughly 3 nT jump caused by spraying the site's electric fence with water. If the claim holds, the station meets and exceeds the project's stated requirement to resolve nanotesla-level anomalies, and the deployment becomes the template for future monitoring sites.

What carries the argument

The load-bearing object is a geomagnetic variometer: a vector fluxgate magnetometer that continuously records changes in Earth's magnetic field relative to its own unchanging baseline, which is sufficient for detecting transient anomalies without the weekly absolute calibration an observatory would use. The argument is carried by the comparison of the station's one-second values, baseline-adjusted to the nearby reference observatory's data, across quiet days, a storm, and controlled interference tests. Supporting the comparison are the temperature calibration performed with a scalar reference in a climate chamber, the non-magnetic and thermally insulated underground deployment, and the orientation of the sensor to geographic north using the World Magnetic Model.

What would settle it

Deploy a second identically built variometer a few tens of meters from a national reference observatory's own magnetometer and run both for several weeks, comparing one-second traces before and after baseline adjustment; if the second instrument does not reproduce the observatory's traces at roughly the few-nT level, then the agreement reported here would be attributable to spatial coherence of the natural field rather than to the instrument's fidelity.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is that a single, solar-powered, buried magnetometer, operated as a variometer with no baseline-drift correction, can record geomagnetic field variations at one-second resolution with quality similar to that of a national reference magnetic observatory located about 60 km away. Comparing the station's data with that observatory after adjusting the baseline, the paper finds visual agreement on quiet days down to few-nT fluctuations, agreement during the portions of a Kp=9 geomagnetic storm that were captured, and clear detection of local, controlled magnetic disturbances such as a several-hundred-nT spike from a steel tool and a few-nT spike from water on the fence. The authors conclude that the instrumentation satisfies and surpasses the science-traceability requirement of resolving signals on the order of 1 nT, and they designate the station as the model for future sites.

Load-bearing premise

The comparison assumes the magnetic field variations at the station and at the reference observatory, about 60 km apart, are effectively identical at the one-second timescale, so any disagreement reflects instrument error rather than real spatial differences in ionospheric, magnetospheric, or locally induced currents; the paper does not quantify the expected spatial coherence over that distance.

Editorial extensions

If this is right

  • A station that resolves few-nT variations can be used to search for local magnetic anomalies that coincide in time with detections from the co-located optical, infrared, acoustic, and weather sensors.
  • The same system can record hundreds-of-nT variations during geomagnetic storms while powered, which helps separate natural space-weather signals from candidate anomalies.
  • The full 0 to 806 Hz bandwidth covers the roughly 10 Hz magnetic oscillations reported in the UAP literature, so the archived data support that search.
  • The deployment recipe of burial, thermal insulation, non-magnetic materials, and geographic orientation can be repeated, so the station serves as the blueprint for a multi-site network.
  • The variometer design avoids weekly absolute calibration while still meeting the project's anomaly-detection requirement, lowering the operational cost of future stations.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A station validated against a nearby reference observatory cannot be assumed valid at a remote site with no such reference; future deployments would need an on-site scalar magnetometer or absolute measurement program to reach the same confidence.
  • If the deployment is replicated at multiple sites, the network would distinguish local transient sources, which appear at one station only, from ionospheric or magnetospheric signals, which appear at all stations together; a single station cannot make that distinction.
  • The raw-data spikes that the paper could not trace to the fence imply that any future anomaly search will need to classify these spikes explicitly before attributing a candidate magnetic event to a UAP.
  • The roughly 50 nT baseline shift observed after the steel-tool test, attributed by the authors to possible ground vibration moving the sensor, implies that mechanical stability of the buried mount is a named risk for long deployments; a tilt-sensing or position-monitoring add-on would make such shifts diagnosable in real time.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 6 minor

Summary. This manuscript reports the design, calibration, deployment, and six-month operation of a geomagnetic variometer station at a Galileo Project field site near Boulder, Colorado. The system consists of a Bartington Mag-13MS100 three-axis fluxgate magnetometer, a Bartington power supply, a National Instruments ADC and chassis, and an Intel NUC, with data recorded at 1612.9 Hz and processed to 1-second values. The magnetometer was calibrated at the USGS Boulder (BOU) magnetic observatory using a scalar-reference method over a limited temperature range. The paper presents comparisons between the station's 1-second data and BOU data for a quiet day, the May 2024 geomagnetic storm (partial coverage), controlled interference tests, and examples of unexplained noise spikes. The central claim is that the data are of similar quality to an INTERMAGNET observatory, based on visual agreement with BOU after baseline adjustment.

Significance. If convincingly established, the claim would show that a relatively inexpensive, solar-powered variometer station can record 1-second geomagnetic field variations suitable for the Galileo Project's goal of identifying anomalous magnetic signals, and the station would serve as a template for future deployments. The paper's strengths include open data and code (Zenodo), an absolute scalar-based calibration, and controlled experiments (water-spray and steel-tool tests) that demonstrate sensitivity to local magnetic sources. However, the central quality claim currently rests on visual, baseline-adjusted comparisons over selected intervals, with no quantitative error statistics or noise-floor measurements; the presence of unresolved spikes in the 1-second data further complicates the claim. These issues are fixable with additional analysis of the already-public data.

major comments (4)
  1. [Section 7, Discussion] The claim that 'the quality of our data is similar to that of an INTERMAGNET observatory' is not supported by quantitative evidence. The comparison with BOU in Figures 9, 11, 12, and 14 is visual only; the paper reports no RMS difference, correlation coefficient, coherence, or noise-floor estimate between the GP and BOU 1-second time series. Because the baseline is adjusted to BOU and the diurnal variation is tens of nT, visual agreement on selected segments cannot bound the instrument noise at the few-nT level or below. I recommend computing quantitative metrics (e.g., RMS differences after detrending, spectral coherence, and a quiet-time noise floor) over multiple days and reporting them in Section 7.
  2. [Section 6, paragraph 1; Section 7] The comparison with BOU assumes that the geomagnetic field variations at the GP site and at BOU, approximately 60 km apart, are effectively identical at the 1-second timescale. The manuscript neither cites nor quantifies the spatial coherence of 1-second ionospheric and magnetospheric variations over this distance, nor does it account for differences in local induction and cultural noise. Without such an assessment, the observed agreement could reflect true spatial coherence rather than instrument fidelity, and real spatial differences could be misattributed to instrument error. The authors should either provide a quantitative estimate of expected spatial coherence (from the ULF pulsation literature or a nearby magnetometer array) or temper the claim to 'the data reproduce the large-scale variations seen at BOU.'
  3. [Section 6.4, Figure 14] The recurring spikes of unknown origin—up to hundreds of nT in the raw data, with residual spikes of about 2 nT in the 1-second Z component (Figure 14d)—are not reconciled with the claim of INTERMAGNET-quality data. INTERMAGNET 1-second data are quality-controlled and flagged; the GP data are presented without spike removal or flagging. The residual 2-nT spikes are comparable to the 3-nT controlled signals used to demonstrate sensitivity in Section 7, so the effective noise floor of the 1-second product is not established. The paper explicitly states that spikes were not removed in post-processing; this limitation should be acknowledged in the quality claim, or the spikes should be characterized and handled in the final data product.
  4. [Section 7, paragraph 1] The statement that detecting the 3-nT water-spray signal 'exceeds the magnetometer's performance requirements by one order of magnitude' is not justified. The STM requirement is a resolution of order ~nT; detecting a known 3-nT spike demonstrates sensitivity at that level, not a tenfold better resolution (~0.3 nT). The residual ~2-nT spikes in Figure 14d suggest a noise floor of a few nT in the 1-second data. A quantitative noise-floor estimate from a quiet interval is needed before this statement can be supported.
minor comments (6)
  1. [Section 4, Figure 3] There is a labeling inconsistency in the description of Figure 3: the text refers to panels (a-c), (d-f), and (h-i), but there are three orthogonality coefficients (a12, a13, a23) and only two panels are listed; the panel (g) is skipped. Please correct the panel labels and ensure all nine coefficients are shown.
  2. [Section 6, first paragraph] The statement that 'we applied a 1-second moving average window on our raw data and we down-sampled by selecting 1 out of 1613 data points' should clarify the exact filter and decimation procedure; a simple moving average has a non-ideal frequency response and may allow aliasing if not combined with appropriate filtering. Please specify whether the moving average is the anti-aliasing filter and whether decimation is performed after filtering.
  3. [Abstract and Section 7] The abstract states that the data 'meet and even surpass the requirements laid out in GP's Science Traceability Matrix,' but the supporting evidence is visual and the 'one order of magnitude' statement is not quantitatively demonstrated. Please align the abstract with the quantitative metrics suggested for Section 7.
  4. [Section 5, Deployment] There are minor typographical issues in Section 5: 'within a 160,000 m 2 horse ranch' contains an extra space before the superscript, and 'the data acquisition system ... were installed' has a subject-verb agreement error. These should be corrected.
  5. [Section 2, Instrumentation] The specification 'measurement noise floor ≤ 10 pTrms/√Hz at 1 Hz' is the sensor's specification, not necessarily the system noise floor of the deployed station. Please clarify whether any system-level noise measurement was performed, and if not, note that this is the sensor specification only.
  6. [Section 6.2] The power outage during the May 2024 storm meant that only the initial and final phases were recorded; this is a limitation of the demonstration and should be stated in the conclusions as well as in the results.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the data-quality claim rests on an external INTERMAGNET benchmark and independent calibration, not on a self-referential derivation.

full rationale

I find no circularity in this paper. The central claim—that the GP variometer data are of similar quality to an INTERMAGNET observatory—is evaluated against an external, independent benchmark: 1-second vector data from the USGS Boulder observatory (BOU), openly available through INTERMAGNET. The GP baseline is adjusted to that of BOU only to remove an irrelevant absolute offset, and the agreement of the recorded variations is a genuine empirical check rather than an equation that reproduces its own input. The temperature calibration uses a scalar magnetometer at the USGS Boulder observatory as an absolute reference, following the Merayo et al. (2000) protocol, which is an external standard independent of the present deployment. The controlled interference tests (spraying the fence with water and using a steel post driver near the magnetometer) provide independent sensitivity checks. The only self-citations are to the project's own Science Traceability Matrix (Watters et al. 2023) and commissioning paper (Domine et al. 2025), but these state project requirements and methodology rather than supplying the empirical evidence, so they are not load-bearing in a circular sense. The qualitative, visual nature of the BOU comparison and the unquantified assumption of spatial coherence over the 60 km separation are legitimate scientific weaknesses, but they concern evidentiary strength and correctness risk, not circularity. No fitted parameter is relabeled as a prediction, and no result is defined in terms of itself.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The central claim rests on calibration and baseline-adjustment fits and on the assumption that the BOU reference is transferable over 60 km. No new physical entities are introduced.

free parameters (3)
  • Temperature-dependent calibration coefficients (a_ij(T), O_i(T)) = Least-squares best-fit lines from measurements at 23, 28, 33 deg C (see Fig. 3)
    Fitted to calibration data; used in the empirical calibration evaluation (Fig. 4) but not applied to the main field data because temperature varied less than 0.3 deg C per day. Values are instrument-specific.
  • Per-component baseline offsets applied to GP 1-sec data to match BOU = Not reported; chosen per component to align baselines
    Applied in Section 6 to compare variations only; this conceals absolute accuracy and is a free adjustment for the comparison claim.
  • Scalar-vector magnetometer offset correction (about 3 m separation) = Not reported
    Used during calibration to rescale coefficients; a small empirical correction.
assumptions (4)
  • domain assumption Spatial coherence of geomagnetic variations between GP site and BOU (60 km apart) is high enough for direct comparison
    Section 6 treats BOU as reference without quantifying expected differences from local ionospheric or magnetospheric currents or geology.
  • domain assumption Magnetometer orientation remained stable over the deployment except for a single noted baseline shift
    Section 5 set orientation once; no continuous attitude monitoring; Section 7 hypothesizes ground vibration caused a shift after the fence-post driver event.
  • domain assumption Diurnal temperature stability (less than 0.3 deg C) makes temperature calibration unnecessary for the field data
    Section 6.1: because the measured temperature variation is small, no temperature correction was applied.
  • standard math Calibration model of Merayo et al. (2000) (Eq. 1) and the inversion script by Barraud and Lesecq (2008) correctly determine the scale, orthogonality, and offset coefficients
    The calibration procedure relies on these external methods.

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Cite this review

Pith. "Pith review of The deployment of a geomagnetic variometer station as auxiliary instrumentation for the study of Unidentified Aerial Phenomena." pith.science (2026). https://pith.science/paper/2D4VISCT

@misc{pith2026250711355,
  author       = {Pith},
  title        = {Pith review of: The deployment of a geomagnetic variometer station as auxiliary instrumentation for the study of Unidentified Aerial Phenomena},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/2D4VISCT}},
  note         = {Machine review of arXiv:2507.11355}
}
read the original abstract

Witness reports of Unidentified Aerial Phenomena (UAP) occasionally associate UAP sightings with local electromagnetic interferences, such as spinning magnetic compasses onboard aircraft or sudden malfunctions of mechanical vehicles. These reports have motivated the incorporation of a magnetometer into the instrumentation suite of the Galileo Project (GP), a Harvard-led scientific collaboration whose aim is to collect and analyze multi-sensor data that collectively could help elucidate the nature of UAP. The goal of the GP magnetometry investigation is to identify magnetic anomalies that cannot be readily explained in terms of a natural or human-made origin, and analyze these jointly with the data collected from the other modalities. These include an ensemble of visible and infrared cameras, a broadband acoustic system and a weather-monitoring system. Here, we present GP's first geomagnetic variometer station, deployed at the GP observatory in Colorado, USA. We describe the calibration and deployment of the instrumentation, which consists of a vector magnetometer and its data acquisition system, and the collection and processing of the data. Moreover, we present and discuss examples of the magnetic field data obtained over a period of 6 months, including data recorded during the May 2024 G5 extreme geomagnetic storm. We find that the data meet and even surpass the requirements laid out in GP's Science Traceability Matrix. Key to the evaluation of our data is the proximity of the variometer station to the USGS magnetic observatory in Boulder, Colorado. By comparing the two sets of data, we find that they are of similar quality. Having established the proper functioning of the first GP variometer station, we will use it as the model for variometer stations at future GP observatories.

Figures

Figures reproduced from arXiv: 2507.11355 by the authors.

Figure 1
Figure 1. The elements comprising the instrumentation system of our geomagnetic variometer station, assembled in our lab. The magne￾tometer is a three-axes fluxgate Bartington Instruments magnetometer and is powered by a Bartington Instruments power supply unit (PSU). The analogue-to-digital converter (ADC) is a NI-9239 from National Instruments. Data acquisition is managed by a NI cDAQ-9171 (chassis) and a mini PC by Intel (… view at source ↗
Figure 2
Figure 2. The measurement setup during the temperature calibration of our magnetometer at the USGS Boulder magnetic observatory. (a) Our vector magnetometer mounted on a theodolite by means of a 3D printed mount. (b) The vector magnetometer mounted on the theodolite, and the scalar magnetometer mounted on a tripod, inside the climate-controlled chamber. where Xraw, Yraw, and Zraw are the raw measurements along the X, Y, and Z… view at source ↗
Figure 3
Figure 3. The calibration coefficients of our vector magnetometer, as a function of temperature. (a-c) The offset coefficients. (d-f) The scaling coefficients. (h-i) The orthogonality coefficients. Blue circles correspond to the values we obtained for 23 ◦C, 28 ◦C and 33 ◦C. The red solid lines correspond to the least squares best-fit lines. The dashed black lines correspond to 1-σ uncertainties derived from the least squares… view at source ↗
Figures from the paper (11 more)
Figure 4
Figure 4. Figure 4: The results of an empirical evaluation of our temperature calibration, during an 1-hour recording under natural temperature variation. Black line: the intensity of the raw vector data. Magenta line: the intensity of the calibrated vector data. Grey lines: the maximum a…
Figure 5
Figure 5. Figure 5: Diagram of the deployment site, showing the location of various instruments, including the magnetometer, and the distance among them. The blue circle shows the location of the hole, inside which the magnetometer was deployed. The blue rectangular shows the location of …
Figure 6
Figure 6. Figure 6: The waterproof, plastic enclosure with the data acquisition system of the magnetometer, mounted on wooden posts and covered by a sunshade. the west (see [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 7
Figure 7. Figure 7: The custom-made mount for the magnetometer. (a) A schematic diagram showing the mount inside the bucket. (b) A picture of the magnetometer placed on the mount. the bucket were lined with thermal insulation. For additional insulation, one blanket was wrapped around the …
Figure 8
Figure 8. Figure 8: The magnetometer buried underground. (a) A picture of the hole in which the magnetometer was deployed. Shown are the yellow inspection chamber, the bucket with its lid open, the magnetometer on the mount, and the trench enclosing the magnetometer cable inside a plastic…
Figure 9
Figure 9. Figure 9: Vector magnetic field data recorded on May 9, 2024, a magnetically quiet day (Kp<3). Black solid line shows our 1-sec magnetic field data, after their baseline has been adjusted to the nearest USGS magnetic observatory, which is located in Boulder, Colorado (BOU). Red …
Figure 10
Figure 10. Figure 10: Raw temperature data, recorded with the integrated temperature sensor on May 9, 2024. Temperature readings vary by less than 0.3 ◦C, as a result of the thermal insulation measures we took during deployment. Similar diurnal temperature variations characterize all our d…
Figure 11
Figure 11. Figure 11: Magnetic field data during the geomagnetic storm on May 10-12, 2024. (a) The magnetic field component pointing Down (Z), from noon on May 10 to 9 am on May 12, in UTC time. Black solid line shows our 1-sec magnetic field data, after adjusting the baseline to BOU’s bas…
Figure 12
Figure 12. Figure 12: Magnetic field data over two days with controlled human-made electromagnetic interference. Our 1-sec magnetic field data, after their baseline has been adjusted to that of BOU, are shown in black solid line. The 1-sec magnetic field data recorded at BOU are shown in r…
Figure 13
Figure 13. Figure 13: Installation of ferrites around the cables to suppress high frequency electronic noise. ferrites (i.e., magnetic components that suppress high-frequency noise) around the cables inside the electronics enclosure. On September 7th, we installed five ferrites, one around…
Figure 14
Figure 14. Figure 14: Our magnetic field measurements showing noise in the form of spikes (see text for details). (a) Raw (i.e., unprocessed) measure￾ments of the magnetic field component pointing North (X) on September 9, 2024. Note the spike at about 13:45 UTC (marked by the arrow). (b) …

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Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.