Search for cosmic rays in GRANDProto300

Hanrui Wang; Jolan Lavoisier; Kumiko Kotera; Mauricio Bustamante (for the GRAND collaboration); Takashi Sako; Xishui Tian

REVIEW 4 major objections 7 minor 15 references

Search for cosmic rays in GRANDProto300

T0 review · 4 major / 7 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read Six filtering stages applied to 533,466 coincidence-triggered events yield 41 cosmic-ray candidates, of which 26 survive reconstruction-quality checks and are presented as solid detections from the 46-antenna GRANDProto300 prototype.

desk verdict A transparent prototype result: first GP300 CR candidates, but the count of 26 rests on manual visual cuts with an admitted northern bias, so treat the number as provisional. read the letter →

arxiv 2507.06695 v2 pith:7BGZUSLU submitted 2025-07-09 astro-ph.IM astro-ph.HEhep-ex

Jolan Lavoisier , Xishui Tian , Kumiko Kotera , Takashi Sako , Hanrui Wang , Mauricio Bustamante (for the GRAND Collaboration) This is my paper · ORCID

classification astro-ph.IMastro-ph.HEhep-ex

keywords cosmicraysradiodetectionGRANDProto300airshowerspipelinepolarizationcutb-ratioprototypearray

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 first cosmic-ray search in data from GRANDProto300, a 300-antenna radio array prototype under deployment in the Gobi Desert. With only 46 antennas collecting stably between November 2024 and May 2025, the authors build and run a six-step filtering pipeline—coincidence triggering, planar-wavefront direction reconstruction, clustering removal of noise bursts, a polarization cut, footprint-size selection, and systematic plus visual quality cuts—over 533,466 coincident events. The pipeline returns 41 candidate events, and a reconstruction-quality stage reduces these to 26 solid cosmic-ray candidates. The aim is to show that autonomous radio detection can identify cosmic rays in the $10^{17}$–$10^{18.5}$ eV range, the energy window spanning the transition from Galactic to extragalactic sources, while the full array is still being built.

What carries the argument

The load-bearing estimator is the b-ratio, $e_V\cdot e_B$: the cosine between the voltage vector measured by an antenna and the local geomagnetic field direction. Because geomagnetic emission from an air shower is polarized along $\mathbf{k}\times\mathbf{B}$, a genuine cosmic-ray signal should have $e_V\cdot e_B\approx 0$, whereas randomly polarized noise is spread over all values; the cut keeps events with median $e_V\cdot e_B < 0.25$. Around this estimator, the clustering cut uses Planar Wave Front (PWF) arrival-direction reconstruction to reject bursts that repeat within $\Delta\theta = 5^\circ$ and $\Delta t = 5$ s, and the footprint and timing cuts rely on the expectation that cosmic-ray events trigger a compact cluster of 5–10 antennas over a 1–10 km$^2$ footprint.

What would settle it

Re-run the pipeline on time-scrambled or phase-randomized versions of the coincident-event data: if a comparable number of candidates survive the visual cuts, the selection is not isolating physical air showers; alternatively, repeating the manual cuts with azimuth hidden would reveal whether the 26 candidates disappear or concentrate toward the transformer and aircraft directions.

Watch

Extended reading notes

Core claim

The paper's central claim is that the GRANDProto300 pipeline, applied to the first stable dataset, isolates cosmic-ray events from a radio background dominated by transient noise. Starting from 533,466 coincidence-triggered events, a clustering cut removes 79% of events as bursts from an electric transformer and hovering aircraft; a polarization cut based on the b-ratio $e_V\cdot e_B$ (the component of the measured electric field along the geomagnetic field) removes another 22%; further cuts on footprint size ($\ge 5$ antennas), zenith angle ($60^\circ$–$88^\circ$), planar-wavefront reconstruction error, signal-to-noise ratio, and RMS noise remove most of the rest. The surviving events are inspected visually for short low-frequency pulses, a compact footprint of 5–10 antennas, and timing consistent with a plane wave front, yielding 41 candidates. Three independent reconstruction methods—lateral distribution function, angular distribution function, and graph neural networks—then confirm 26 of these as solid cosmic-ray candidates, with reconstructed energies consistent with the array's exposure calculations.

Load-bearing premise

The manual visual cuts—trace shape, footprint compactness, and timing consistency—are assumed to separate real cosmic-ray signals from noise, and the reviewers' stated preference for northern azimuths is assumed not to bias which events survive.

Editorial extensions

If this is right

The 26 solid candidates demonstrate that the 46-antenna prototype can already pick out cosmic-ray-like events from a noisy radio environment, validating the autonomous-detection concept before the array is complete.
The cut-efficiency table provides a quantitative noise budget: clustering alone removes 79% of coincident events, so most of GP300's current trigger rate is transient local interference rather than astrophysical signal.
The polarization cut keeps more than 99% of simulated cosmic-ray signals while rejecting roughly a fifth of the data, showing that the b-ratio is a workable positive identifier even before antenna polarity calibration is fully settled.
The reconstruction-quality stage is deliberately conservative, keeping only 26 of 41 candidates, and this purity-over-efficiency choice sets the template for the next stage of the analysis.
Once the full 300-antenna configuration is deployed in 2026, the authors expect around 130 cosmic-ray events per day, which would make the Galactic-to-extragalactic transition region accessible with the same pipeline.

Reading between the lines

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

A testable extension the paper does not pursue: re-running the manual cuts with azimuth information blinded would measure how much of the documented northern-sky preference biases the surviving candidate list and could convert the 26 candidates into an unbiased sample.
Because the paper notes that the real background b-ratio distribution is non-uniform, a future pipeline could model the actual noise polarization density instead of assuming uniform noise; that should improve background rejection beyond the reported level and recover candidates currently lost.
The visual cuts—pulse widths of 50–100 ns, compact 5–10 antenna footprint, PWF-timing consistency—could be codified as quantitative features and automated, which is the natural bridge to the machine-learning cuts the authors list as a next step.
If the 26 candidates are genuine, their rate with 46 antennas over the studied months can be combined with the published exposure to produce a first flux estimate in the $10^{17}$–$10^{18.5}$ eV band, a step the paper defers until the dataset is larger.

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Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

First: the paper reports the first batch of cosmic-ray candidate events from GRANDProto300, 26 in number, found with a pipeline that is mostly a recombination of previously published techniques (clustering, polarization, footprint, PWF). That is a legitimate detector milestone, and the authors deserve credit for stating their biases openly, including the manual visual cuts and the northern-azimuth preference in Section 3. The polarization cut is grounded in ZHAireS simulations with data-based noise, which is a reasonable way to set this kind of threshold at prototype level. The cut-efficiency table (Fig. 5) is useful, and the pipeline description is sufficiently concrete to be replicated in spirit.

Now the soft spots, in proportion. The main one is that the 26 candidate count is not robust against the manual visual cuts. Section 2.5 lists three criteria — trace shape, footprint compactness, timing consistency — but none is reduced to a quantitative rule, and Section 3 states that 'particular attention' was given to northern azimuths during those cuts. Without an inter-reviewer consistency check or a blinded re-review, there is no way to know whether the number 26 is a stable pipeline output or a reflection of the reviewers' prior. The candidate list and arrival-direction map are not shown, so the claim cannot be independently audited from the text. The stress-test note is right: this is load-bearing, not a side concern.

Several smaller issues: cut efficiencies are quoted without uncertainties; the SNR threshold of ≥5 on the Y channel is called 'arbitrary' by the authors themselves; the zenith cut to 60–88° means the sample is restricted, which is fine but should be stated when interpreting the arrival directions. The polarization cut uses noise events from the same dataset that is later filtered; this has some circular flavor, but the signal model is independent, so I consider it a minor concern. The paper is a proceedings, so the absence of a full candidate table is expected, but it does limit the strength of the claim.

Verdict: conditional, as the reader says. This is a promising prototype result, not a physics discovery. The honest writing and transparent pipeline make it worth a serious referee — if submitted to a journal, I would send it out, with the requirement that the manual cuts be replaced or augmented by a blinded or quantitative scoring, and that the 26 candidates be listed with their directions and basic signal parameters. Without that, the central number 26 is a claim about human judgment, not about the detector.

Referee Report

4 major / 7 minor

Summary. The manuscript presents the first cosmic-ray search pipeline for GRANDProto300, applied to 533,466 coincident events recorded between December 2024 and March 2025 with 46 antennas. The pipeline combines coincidence, clustering, polarization, and quality cuts (antenna number, zenith, PWF error, SNR, RMS) followed by manual visual cuts and a reconstruction-quality selection. The authors report 41 candidate events after the systematic pipeline and 26 "solid" candidates after manual and reconstruction-quality cuts, with energy reconstructions consistent with the expected range.

Significance. If the 26 candidates are genuine cosmic rays, the work demonstrates the autonomous radio-detection technique at the prototype scale and supports the GRAND design. The paper is transparent about its preliminary nature and provides efficiency estimates for each cut based on ZHAireS simulations with data-based noise. However, the load-bearing manual visual cuts are subjective and the admitted northern-azimuth bias in Section 3 undermines the robustness of the reported candidate count without additional checks.

major comments (4)

[§2.5, §3] The manual visual cuts (trace shape, footprint compactness, timing consistency) are not defined by quantitative thresholds, and Section 3 states that "particular attention was given to the Northern part of our dataset when performing manual cuts." Because the final count of 26 candidates is obtained after these manual cuts, the central claim is not reproducible and may be biased; the paper provides no inter-reviewer consistency check, blinded re-review, or test of the azimuthal sensitivity of the selection. This needs to be addressed, e.g., by specifying measurable criteria (pulse width, spectral slope, footprint ellipticity, timing-residual limits), performing a blinded re-review, and comparing the candidate azimuthal distribution to the detector exposure.
[§2.3] The polarization cut is calibrated using a noise sample consisting only of events from the plane and transformer directions, but it is then applied to the full dataset; the reported 38% noise rejection may not hold for the broader noise population. Moreover, the noise distribution used to choose (eV·eB)_cut is drawn from the same dataset that is later filtered, introducing a partial circularity that should be mitigated with a disjoint calibration sample or a hold-out period.
[Fig. 5 (right)] The cut-efficiency table reports percentages without uncertainties, and the final line "Full pipeline 7×10^{-5}%" is ambiguous: 41/533,466 ≈ 7.7×10^{-5} is the retained fraction, not the excluded fraction, and it is inconsistent with the column header. Uncertainties on the retained fraction, ideally including the manual-cut step, should be provided to support the claimed purity of the sample.
[§2.4] The SNR cut (SNR_Y ≥ 5) is described as "arbitrary" and the PWF-error cut as "more artificial." The paper does not demonstrate that the final candidate list is stable under reasonable variations of these thresholds; a one-at-a-time sensitivity scan showing the number of candidates as a function of each threshold would substantiate the claim that the 26 candidates are not an artifact of the specific cut choices.

minor comments (7)

[Abstract] The abstract contains a typo: "Between November 2024 u to May 2025" should read "November 2024 and May 2025."
[§2.1] The phrase "transient noise induces events" would be clearer as "transient noise produces events."
[§2.3] The notation for the b-ratio (e𝑉· e𝐵) has inconsistent spacing between the vector dot; please use consistent math formatting throughout.
[§3] The sentence "26 solid cosmic-ray candidates, displayed in [1], Figure 5" appears to refer to a companion paper's figure, but this manuscript contains its own Figure 5; please clarify the intended cross-reference.
[Fig. 5 (right)] The final row "7×10^{-5}%" should be rewritten as 7.7×10^{-5} (the retained fraction) or 7.7×10^{-3}% to avoid confusion with the column header indicating the excluded proportion.
[§2.2] The definition of angular distance Δ𝜗 = min(Δ𝜃, Δ𝜙) is confusing because Δ𝜃 and Δ𝜙 have different units; either define the minimum of the absolute zenith difference and the wrapped azimuth difference, or use an angular separation on the sky.
[§2.5] The statement that cosmic-ray traces are characterized by "low-frequency signals" should be quantified (e.g., peak frequency below 100 MHz) to make the visual cut reproducible.

Circularity Check

2 steps flagged · score 3.0 of 10

Central candidate search is not circular; two consistency checks in Section 3 reduce to the cuts by construction.

self definitional [Section 3, 'First batch of cosmic-ray candidates', discussion of Figure 6 (polarization distribution)]
"The polarization distribution gives similar results to Fig. 2 right: the cosmic-ray polarization distribution peaks at lower eV·eB values than the distribution for all dataset."

Every candidate event must pass the polarization cut with parameter (eV·eB)_cut = 0.25, so the retained sample has median eV·eB < 0.25 by construction. Presenting the candidate polarization distribution as 'similar results' to the simulation-based expectation is therefore a consistency check that is guaranteed by the cut itself, not independent evidence. The noise distribution used to optimize the cut also comes from the same dataset that is later filtered, so this step provides no out-of-sample confirmation of the cosmic-ray nature of the candidates.
self definitional [Section 2.5 'Manual quality cuts' and Section 3, discussion of Figure 6 (number of antennas)]
"Specifically, the triggered antennas should form a concentrated footprint of 5 to 10 antennas (see [11]). ... The number of antennas triggered aligns with expectations from [11], which suggest that the event’s footprint should range between ∼ 1− 10 km2 ... This corresponds to between 5 and 10 triggered antennas with GP300."

The manual footprint cut is defined using the [11] expectation of 5–10 antennas, and the systematic N_DU cut requires at least 5 triggered DUs. Therefore the candidate sample's triggered-antenna distribution is forced to lie in or near the 5–10 antenna range. Citing the same expectation afterward as an alignment is circular: the check and the cut are the same condition. This does not invalidate the candidate count, but it removes any confirmatory value from the stated agreement.

full rationale

The central claim of the paper is that the described pipeline, applied to GP300 data, yields 41 candidates and, after reconstruction-quality cuts, 26 solid cosmic-ray candidates. That count is not circular: it is the output of applying a fixed sequence of cuts (clustering, polarization, N_DU, zenith, PWF error, SNR, RMS, manual visual cuts, reconstruction quality) to the data, and no fitted parameter is renamed as a prediction. The polarization threshold is chosen using independent ZHAireS simulations as signal and data-based noise; although the noise sample overlaps the data being filtered, that is an in-sample optimization issue rather than a definitional circularity, and the paper does not present the candidate count as a statistically validated prediction. The manual cuts are subjective and the paper candidly discloses the northern-azimuth attention, which is a selection-bias concern, not a circularity. The genuine circular steps are the two consistency checks in Section 3: the candidates' low polarization is guaranteed by the polarization cut, and their 5–10 antenna footprint is guaranteed by the N_DU and manual footprint cuts. These checks reduce by construction and therefore cannot serve as independent confirmation, but they are not load-bearing for the derivation of the candidate count itself. The score reflects these minor by-construction validations rather than any circularity in the central search result.

Assumptions & free parameters 9 free parameters · 5 assumptions · 0 invented entities

The paper introduces no new physical entities. Its central claim depends on a series of hand-selected analysis thresholds and on the accuracy of external simulation and reconstruction software, all listed above.

free parameters (9)

Polarization cut threshold (e_V.e_B)_cut = 0.25
Chosen to maximize simulated signal efficiency (about 99%) over noise exclusion (about 38%) using ZHAireS simulations and data-based noise. Hand-tuned in Section 2.3.
Clustering cut angular window Delta_theta_cut = 5 degrees
Hand-chosen conservative value based on the distribution of angular distances between consecutive events (Section 2.2).
Clustering cut time window Delta_t_cut = 5 s
Hand-chosen to remove bursts of transient noise while retaining cosmic-ray-like isolated events (Section 2.2).
Minimum number of triggered antennas N_DU,min = 5
Set to match the expected footprint size of 5 to 10 antennas for GP300 sensitivity (Section 2.4, ref. [11]).
Zenith angle range = 60 to 88 degrees
GP300's sparse array is most sensitive to highly inclined showers; near-horizon events are excluded due to reconstruction difficulty (Section 2.4).
PWF error threshold = 0.5 degrees
Hand-chosen to reject events with a poor plane-wave-front fit (Section 2.4).
SNR_Y threshold = 5
Arbitrarily chosen to keep clean traces, acknowledged as a commissioning-stage cut (Section 2.4).
RMS limits for frequency bands = RMS_X,Y(50-80 MHz)<2 mV; RMS_X(160-225 MHz)<1 mV; RMS_Y(160-225 MHz)<3 mV
Set based on observed transformer emission bands (Section 2.4).
Reconstruction quality criteria = >=5 DUs with E-field, energy<1e20 eV, ADF chi2<25
Additional quality filter on reconstructed candidates (Section 3).

assumptions (5)

domain assumption Air-shower radio emission is dominated by the geomagnetic effect, producing linear polarization along k x B
Invoked in Section 2.3 to justify the polarization cut and the b-ratio estimator from ref. [9].
domain assumption ZHAireS simulations accurately model radio emission from air showers for proton and iron primaries in the 1e16.5 to 1e18.6 eV range
Used as the signal template to optimize the polarization cut (Section 2.3).
domain assumption Superimposing data-based stationary background noise on simulated traces reproduces real detector conditions
Used to compute the polarization cut efficiency (Section 2.3).
standard math Planar Wave Front reconstruction (from ref. [8]) provides valid arrival directions for distant air-shower radio pulses
Basis for both the clustering cut (Section 2.2) and the PWF error cut (Section 2.4).
domain assumption GRANDlib's RF chain simulation correctly propagates simulated electric fields through the antenna and trigger system
Used to convert ZHAireS fields to voltage traces (Section 2.3).

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Cite this review

Pith. "Pith review of Search for cosmic rays in GRANDProto300." pith.science (2026). https://pith.science/paper/7BGZUSLU

@misc{pith2026250706695,
  author       = {Pith},
  title        = {Pith review of: Search for cosmic rays in GRANDProto300},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/7BGZUSLU}},
  note         = {Machine review of arXiv:2507.06695}
}

abstract

GRANDProto300 (GP300) is a prototype array of the GRAND experiment, designed to validate the technique of autonomous radio-detection of astroparticles by detecting cosmic rays with energies between 10$^{17}$-10$^{18.5}$ eV. This observation will further enable the study of the Galactic-to-extragalactic source transition region. Between November 2024 u to May 2025, 46 out of 300 antennas have been operational and collecting data stably. We present here our cosmic-ray search pipeline, which involves several filtering steps: (1) coincidence search for signals triggering multiple antennas within a time window, (2) directional reconstruction of events, (3) exclusion of clustered (in time and space) noise events, (4) polarization cut, (5) selection based on the size of the footprint, and (6) other less mature cuts in this preliminary stage, including visual cuts. The efficiency of the pipeline is evaluated and applied to the first batch of data, yielding a set of cosmic-ray candidate events, which we present.

Figures

Figures reproduced from arXiv: 2507.06695 by the authors.

**Figure 1.** Mean number of coincident events per day (in units of 104 ) in each dataprocessed periods (orange blocks) from Dec. 2024 to Mar. 2025. Gray areas indicate nonprocessed periods and red stars mark cosmicray candidate events selected via the pipeline described in this proceeding. this pipeline, we aim to adopt a conservative approach, prioritizing purity over efficiency in our cosmic-ray identification process. 2.2 … view at source ↗

**Figure 2.** Left: Clustering cut efficiency. Distribution of angular Δ𝜗 and temporal Δ𝑡 distances to the nearest neighbor events. The cumulative sums of these distributions are shown in gray. The red [yellow, orange] line indicates the regions in the parameter-space that corresponds to (and hence can be excluded) specific cut parameters sets (Δ𝜗cut = 5 ◦ [10◦ , 10◦ ] Δ𝑡cut = 5 s [5 s, 10 s]). Right: Polarization cut efficiency.… view at source ↗

**Figure 3.** Examples of event visualization, for a cosmic-ray candidate that passed the entire pipeline, including manual cuts. The displayed information includes for each panel (top left) the distribution of polarization levels (e𝑉 · e𝐵) of the signal at triggered antennas in the event (mean and median values for the event indicated at the top), (bottom left) the position of the triggered antennas (antenna positions are indica… view at source ↗

Figures from the paper (3 more)

**Figure 4.** Figure 4: Same as [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]

**Figure 5.** Figure 5: Left: Arrival directions (zenith 𝜃 and azimuth 𝜙 angles where 𝜃 = 0 indicates up and 𝜙 = 0 indicates north) of the cosmic-ray candidates in polar representation. Right: Cut efficiencies of each process of our cosmic-ray search pipeline, applied to our dataset. The perc…

**Figure 6.** Figure 6: Left: Normalized distribution of polarization in cosmic-ray candidates and for all dataset. Right: Normalized distribution of the number of antennas triggered for cosmic-ray candidates and all dataset. References [1] GRAND Collaboration, O. Martineau PoS ICRC2025 (2025…

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Reference graph

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Pith tools

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

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