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The uncommon intracluster medium features of the first massive clusters selected independently of their baryon content

T0 review · 3 major / 3 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read Four clusters selected by mass, not gas, show far more rare gas features than gas-selected samples predict, evidence that our picture of cluster gas is systematically biased.

desk verdict Careful multi-wavelength follow-up of four shear-selected clusters, but the claimed 10x excess of rare ICM features rests on a biased null and needs to be softened or re-derived. read the letter →

arxiv 2501.07635 v1 pith:VWLC3W5N submitted 2025-01-13 astro-ph.CO

S. Andreon , M. Radovich , A. Moretti , F.-X. Desert , T. Hamana , M. Pizzardo , C. Romero , H. Roussel
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G. Trinchieri
This is my paper · ORCID
classification astro-ph.CO
keywords galaxyclustersweakgravitationallensingintraclustermediumX-rayluminositySunyaev-Zeldovicheffectselectionbiasmass-observablescalingrelationsmass-selectedsamples
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 argues that most knowledge of the hot gas (intracluster medium, ICM) in galaxy clusters comes from clusters that were themselves selected by that gas, which biases the resulting picture. It studies four massive clusters chosen purely by weak gravitational lensing, meaning selection depends on total mass rather than baryon content, and measures seven ICM-related properties for them. Relative to gas-selected clusters of the same mass, the four clusters show on average about two rare (more than 2σ) features per property, while only about 0.2 are expected if gas-selected samples faithfully represent the population. The paper concludes that X-ray- and Sunyaev-Zeldovich-selected catalogs are missing a real population of massive, gas-poor clusters, and that scaling relations built from those catalogs are biased.

What carries the argument

The load-bearing device is a sample selected by weak gravitational lensing from the HSC shear-selected catalog, whose inclusion probability depends on total mass rather than on baryon content. The comparison machinery is a set of seven ICM observables—richness, core-excised X-ray luminosity, Compton Y, electron density and pressure profiles, and their central values—measured for the four clusters from shear, X-ray, and SZ data and compared with gas-selected reference samples, notably SZ-selected profile libraries and X-ray-selected scaling relations. A Bayesian forward-modeling code (MBProj2 extended to shear) derives masses and profiles while applying a Tinker mass-function prior to correct for Eddington bias; for the two out-of-equilibrium clusters the analysis deliberately avoids assuming hydrostatic equilibrium.

What would settle it

Take a complete sample of 50 or more clusters selected purely by weak lensing in the same mass and redshift range and measure the same seven ICM properties; if the fraction of >2σ outliers per property is close to the expected 5% rather than the roughly 50% seen here, the anomaly is a property of these four objects rather than of ICM-selected sampling.

Watch

Extended reading notes

Core claim

The central discovery is that a small, shear-selected sample of four massive clusters is dramatically more unusual in its ICM properties than gas-selected samples would predict. Cluster id5, the most striking object, has a weak-lensing mass of log M500/Msun = 14.68 ± 0.10 but a core-excised X-ray luminosity and richness that sit far below the relations defined by X-ray- and SZ-selected clusters, and its pressure and density profiles fall below the ±2σ range of SZ-selected clusters; an independent caustic analysis confirms its mass. The other unusual object, id34, is similarly low in pressure and Compton Y. Across seven explored properties, the sample shows 12 outliers beyond 2σ where about 1.4 would be expected by chance in four objects, or an average of two rare features per property against an expected 0.2. The paper interprets this excess as evidence that the thermodynamic properties of clusters derived from ICM-selected samples are fundamentally biased: massive clusters with low gas content exist and are largely absent from those samples.

Load-bearing premise

The four clusters are taken from a weak-lensing shear-peak catalog that is assumed to be unbiased with respect to baryon content and ICM properties, and the two most massive plus two high-signal-to-noise clusters are treated as representative of the larger mass-selected population.

Editorial extensions

If this is right

  • If the paper is right, X-ray and SZ cluster catalogs are incomplete not only at the faint end but across a population of massive gas-poor clusters, so mass-observable scaling relations derived from them underpredict scatter and overpredict gas content at fixed mass.
  • A massive cluster like id5 can be absent from an X-ray cosmological survey such as eROSITA DR1 even at redshift 0.25, implying that X-ray mass completeness is lower than commonly assumed.
  • The population of low-Compton-Y clusters that a previous analysis of X-ray-selected data had to postulate in order to correct its scaling relation is directly observed in id5 and id34, supporting selection-effect corrections of that type.
  • Baryon-independent, lensing-based selection becomes a necessary tool for measuring cluster thermodynamics and for calibrating the mass-observable relations used in cluster cosmology.

Reading between the lines

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

  • My inference: if the anomaly is driven by the infalling groups seen in id5 and id34, then a mass-selected sample split by dynamical state should show the outliers concentrated in merging clusters, making the bias partly a dynamical-state bias rather than purely a gas-fraction bias.
  • My inference: the true intrinsic scatter of X-ray luminosity at fixed mass may be sample-dependent, so calibrating cluster scaling relations for cosmology may require explicitly modeling the population that gas-selected surveys cannot see.
  • A testable extension: applying the same seven-property comparison to roughly 50 to 100 lensing-selected clusters would directly measure the outlier rate and reveal which of the seven properties suffer the strongest selection bias, guiding which scaling relations need re-derivation.
  • My inference: if low-richness massive clusters like id5 are common, richness-based mass estimates can be wrong by large factors for a minority of objects, which would affect optically selected cluster cosmological samples.
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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

3 major / 3 minor

Summary. The paper presents a pilot study of four massive galaxy clusters selected from the HSC weak-lensing survey, i.e. independently of their baryon content. For each cluster the authors derive shear-based masses (with Eddington-bias correction), core-excised X-ray luminosities, electron density and pressure profiles, Compton-Y parameters, and optical richness. They compare seven of these properties with those of ICM-selected comparison samples and report an excess of rare (>2 sigma) features: they expect on average 0.2 such features per property but observe about two per property. The two most extreme objects, id5 and id34, are dynamically complex, and id5 is scrutinized in detail with DESI spectroscopy, caustic masses, KiDS shear, and contamination tests. The paper concludes that ICM-selected samples are biased in our knowledge of cluster thermodynamic properties.

Significance. If the central statistical claim were fully supported, the paper would be important: it would demonstrate that X-ray and SZ selected samples miss a real population of massive, gas-poor clusters and that scaling relations built on those samples are correspondingly biased. The strengths of the paper are substantial: the Eddington-bias treatment is explicit and careful; the X-ray background and PSF handling is detailed; the mass of id5 is cross-checked with caustics and independent KiDS ellipticities; and hydrostatic equilibrium is avoided for the two clusters where it is risky. The data themselves, including the new Swift/Chandra and NIKA2/ACT measurements, are valuable. However, the headline '10x excess' calculation in Sec. 3.1 depends on a null model whose scatter is taken from the very ICM-selected samples that Sec. 1 argues are biased, and several of the counted outliers are shown elsewhere in the paper to disappear once a selection-unbiased comparison is used. The claim therefore needs substantial reworking before it can support the stated conclusion.

major comments (3)
  1. [Sec. 3.1, Fig. 13] The central statistical claim is not a valid null test as presented. The expected number of >2 sigma outliers is computed using the intrinsic scatter of the ICM-selected comparison samples (Pratt et al. 2022; Ghirardini et al. 2020; Nagarajan et al. 2019), but Sec. 1 argues that those samples have severely underestimated scatter (0.02-0.17 dex versus 0.4-0.5 dex in samples selected without the ICM). A 2 sigma threshold defined by an underestimated scatter is not a null distribution for a mass-selected population. The paper itself provides the concrete counterexample: Sec. 2.6 and Fig. 9 state that id5 is 6 sigma below the SZ-selected L_X relation but only 0.4 sigma from the X-ray-unbiased XUCS relation, so the counted id5 luminosity outlier disappears with an unbiased null. Similarly, Sec. 2.7.2 and Fig. 12 show that the low-Y outliers of id5 and id34 fall exactly where the selection-corrected Nagarajan et al. (2019) relation postulates clusters. The expected-outlier calculation must either use scatter estimates from unbiased samples (e.g. XUCS or the recent eROSITA-based scatter of Ghirardini et al. 2024) or be reframed as 'rare relative to a biased ICM-selected sample', which would not support the abstract's conclusion of a fundamental bias.
  2. [Sec. 2.1, Sec. 3.1] The four clusters are not a random draw from a mass-selected population, so the binomial or Poisson statistics in Sec. 3.1 do not directly apply. The selection is described as 'the two most massive clusters' and 'randomly two, out of three clusters with largest signal-to-noise visible in the spring nights', and after Eddington correction the selected masses shift substantially. Because shear-peak S/N correlates with concentration, dynamical state, and line-of-sight projection, the sample may be biased in exactly the properties being tested. The two most anomalous objects, id5 and id34, are both dynamically complex with infalling groups (Sec. 3.1), and id5 is the highest-S/N massive cluster in the parent sample; the observed outlier excess could then be a property of the selection rather than of the general cluster population. The authors should either demonstrate that the sample is representative by resampling from the parent shear-selected catalog, or explicitly present the paper as a pilot study whose conclusion is limited to the four objects and not yet a population statement.
  3. [Sec. 3.1, Fig. 13] The analysis treats the seven non-independent features as if they provide seven independent tests. The text admits that the features are non-independent, and then tries to mitigate this by 'focusing on just one ICM-based feature', but the abstract and the per-feature average still quote the aggregated number '12 outliers among 7 non-independent features' and 'two rare features in each one of the seven properties'. Since L_X, Y, pressure, and electron density are physically correlated, and since id5 and id34 contribute the majority of the outliers, the effective number of independent trials is much smaller than 28 (4 clusters x 7 properties). The p-values quoted in Fig. 13 should be replaced by a joint test that accounts for covariance among properties, or by a conservative count based on the number of independent clusters showing any rare feature. Without this, the reported significance is overstated.
minor comments (3)
  1. [Sec. 3.1, Fig. 13] The text and figure should state explicitly whether '>2 sigma' means a one-sided 2.3% threshold or a two-sided 5% threshold; the expected count of 0.2 per four objects per property corresponds to a two-sided 95% interval, whereas many readers will interpret '2 sigma' as one-sided 2.3%, which changes the expected counts by a factor of about two.
  2. [Sec. 2.1, Sec. 2.6] There are several typos and spacing issues: 'Miyakasi et al. (2018)' should be 'Miyazaki et al. (2018)', 'Andreon & Weaver 2015abouthowtodealwiththiscase' in Sec. 1 is missing a space, and 'core-excised X-ray ray luminosity' in Sec. 2.6 has a duplicated word.
  3. [Table 1, Sec. 2.7.2] The text says that the quoted Y_sph,500 values in Table 1 are as measured and that a 0.06 dex correction is applied only for comparison, but the abstract and Fig. 12 do not make this distinction clear; a short statement in the table caption would prevent misinterpretation.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the outlier-excess claim is an empirical comparison against external ICM-selected samples, not a fit disguised as a prediction.

full rationale

The derivation chain is not circular. The paper's headline claim is an empirical outlier count: four shear-selected clusters are compared, property by property, to external ICM-selected samples (Pratt et al. 2022; Ghirardini et al. 2020; Nagarajan et al. 2019), and the number of >2σ deviations is compared with the expected 0.2 per feature under a Gaussian null. The expected number is a fixed statistical calculation (4 objects x 5% per feature), not a parameter fitted from the data whose output equals the input. The 'biased null' tension is real but is an inconsistency in the choice of null, not a definitional circularity: the paper uses the ICM-selected scatter as the null precisely to test whether it is too small, and then supports that interpretation by showing that one supposedly rare object (id5) is typical when compared to the XUCS sample selected independently of ICM (Andreon et al. 2016). The XUCS comparison is an external benchmark, not a theorem imported from the same authors. The richness-mass calibration (Andreon 2015) is a standard empirical calibration based on clusters with known masses, and the paper makes multiple independent cross-checks (caustic mass, KiDS shear, DESI spectroscopy) for the key outlier id5. No step in Secs. 2-3 reduces an equation to itself or renames a fitted value as a prediction. The self-citations are numerous but not load-bearing in a circular sense: they provide datasets and calibrations, and the central conclusion is falsifiable by external samples. Score 0.

Assumptions & free parameters 6 free parameters · 6 assumptions · 0 invented entities

The central claim rests mostly on observational data and external comparisons; the only invented thing is the hypothesis of a gas-poor cluster population, which is not a mechanism or entity. The key free parameters are nuisance parameters of the X-ray, SZ, and shear models. The most consequential assumptions are the unbiasedness of the lensing selection and the correctness of the comparison-sample scatters.

free parameters (6)
  • n0 (electron density normalization) = not reported individually
    Six-parameter modified beta model (Eq. 1) fitted to X-ray surface brightness profiles; the profile shapes are regularizing kernels and are not the target of the paper.
  • alpha, beta, epsilon, rc, rs (density profile shape parameters) = not reported individually (poorly constrained)
    Same Eq. 1; the authors state alpha and epsilon are poorly determined and profiles are used as regularizing kernels.
  • Tm, rt, b, c (temperature profile parameters) = not reported
    Vikhlinin temperature model (Eq. 2) used for disjoint (non-hydrostatic) fits of id5 and id34 to derive pressure profiles.
  • NFW concentration (c) = not reported
    Fitted to shear, with log-uniform prior 0.1-30 (Hamana et al. 2023) and Dutton and Maccio (2014) c-M prior for shear-only fits; affects mass profile and pressure profile normalization.
  • X-ray background scaling parameter = close to 1, well determined
    Marginalized with Gaussian prior centered on 1 with 10% sigma to absorb differences between cluster and control-field backgrounds.
  • Metallicity = poorly determined
    Left free with a uniform prior in X-ray spectral fits.
assumptions (6)
  • domain assumption Weak-lensing shear selection is independent of the baryon content and ICM properties of clusters.
    Stated in Sec 1 and Sec 2.1; this is the premise that makes the four-cluster sample unbiased. If shear-peak selection correlates with concentration or dynamical state, the outlier excess may not generalize.
  • domain assumption The Tinker et al. (2008) mass function is the correct prior for Eddington-bias correction.
    Used in Sec 2.5 to correct shear-derived masses for the steep mass function; under-correction would bias masses high and make clusters appear gas-poor.
  • domain assumption Hydrostatic equilibrium holds for id17 and id48.
    Assumed in joint X-ray plus shear fits (Sec 2.5) to derive pressure and mass profiles; if violated, derived thermodynamic profiles could be biased.
  • domain assumption Spherical symmetry holds for the modeled clusters, or for id34 in the restricted radial range.
    Used in X-ray and SZ profile modeling (Sec 2.5, Appendix E).
  • domain assumption The reference ICM-selected samples (Ghirardini et al. 2020; Pratt et al. 2022; Nagarajan et al. 2019) have correct means and intrinsic scatters for defining >2-sigma rarity.
    The expected number of 0.2 outliers per feature is computed from these distributions; if their scatter is underestimated, the observed excess is less significant.
  • domain assumption The Dutton and Maccio (2014) concentration-mass relation applies to the shear-only fits of id5 and id34.
    Used in Sec 2.5 for shear-only fits; it affects the mass profile and hence the scaling-relation comparisons.

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Cite this review

Pith. "Pith review of The uncommon intracluster medium features of the first massive clusters selected independently of their baryon content." pith.science (2026). https://pith.science/paper/VWLC3W5N

@misc{pith2026250107635,
  author       = {Pith},
  title        = {Pith review of: The uncommon intracluster medium features of the first massive clusters selected independently of their baryon content},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VWLC3W5N}},
  note         = {Machine review of arXiv:2501.07635}
}
abstract

Our current knowledge of the thermodynamic properties of galaxy clusters comes primarily from detailed studies of clusters selected by their minority components: hot baryons. Most of these studies select the clusters using the component that is being investigated, the intracluster medium (ICM), making the sample choice prone to selection effects. Weak-gravitational lensing allows us to select clusters by the total mass component and, being independent of the type of matter, makes the sample choice unbiased with respect to the baryon content. In this paper, we study four galaxy clusters at intermediate redshift ($0.25<z<0.61$), selected from the weak-lensing survey of Miyazaki et al. (2018). We derive core-excised X-ray luminosities, richness-based masses, Compton parameters, and profiles of mass, pressure and electron densities. These quantities are derived from shear data, Compton maps, and our own X-ray and SZ follow-up. When compared to ICM-selected clusters of the same mass, in the range $2$ to $5 \ 10^{14}$ M$_\odot$, our small sample of four clusters is expected to have on average 0.2 rare ($>2\sigma$) features, while we observed on average two rare features in each one of the seven explored properties: richness, core-excised luminosity, Compton parameter, pressure and electron pressure profiles, and central values of them. The abundance of rare and unique features in such a small sample indicates a fundamental bias in our knowledge of the thermodynamic properties of clusters when derived from ICM-selected samples.

Figures

Figures reproduced from arXiv: 2501.07635 by the authors.

Figure 1
Figure 1. Top panel: Mass-redshift plot of the ≥ 4.98 sample with available masses. Bottom panel: detection (shear) S/N - redshift plot of the sub-sample with 𝑀500 > 4.3 1014 M⊙. In both panels the followed up clusters are indicated by a solid circle. Masses in this figure are as in Miyazaki et al. (2018). al. (2021) catalog. id48 has also been spectroscopically confirmed by Ebeling et al. (2024). DESI reshifts (DESI collabor… view at source ↗
Figure 2
Figure 2. Redshift distribution in the id5 line of sight (within 𝑟500, blue histogram, the cluster is the peak at 𝑧 = 0.256) and average background distribution around id5 (red filled histogram, barely visible because it is very close to zero at all redshifts), normalized to the cluster solid angle. There is only one cluster in the id5 line of sight. 0 1 2 3 4 5 r [Mpc] 4000 2000 0 2000 4000 ¢ vlos [k m / s] [PITH_FULL_IMAGE… view at source ↗
Figure 3
Figure 3. Velocity differences Δvlos as a function of clustercentric distance 𝑟 for individual galaxies in the field-of-view of the id5 cluster. Curves show the caustic profile estimated by the caustic technique. Shaded areas report the uncertainty of the caustics. Id5 cluster is a massive cluster, with log M200,caustics/M⊙ = 14.8. brighter galaxies risk to be saturated in HSC images. Therefore, for those two clusters and for… view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: Binned tangential shear profile of the four clusters. The solid line with yellow shading indicates the mean model and 68% uncertainty fitted to shear and X-ray data (id17 and id48) or shear only (id5 and id34) data. Uncertainty in the model also accounts for intrinsic …
Figure 5
Figure 5. Figure 5: id17 surface brightness profiles (points with error bars) in the X-ray bands with 68% uncertainties on the fitted model (red line and yellow shading). The green line with lime shading (barely visible) is the background radial profile and its 68% uncertainty. The analys…
Figure 6
Figure 6. Figure 6: Cumulative mass profile of the four clusters (solid line with 68% uncertainty in yellow). The mass profile is constrained by weak-lensing data at large radii and, in the case of joint fits, by X-ray data at small radii (roughly, 𝑟 < 500 kpc). Id5 cumulative mass profil…
Figure 7
Figure 7. Figure 7: Mass-redshift plot. We plot the SZ-selected Planck sample of clusters (Planck collab. 2016, gray points) and the studied, shear selected, sample with both the masses at the time of the selection (large blue circles) and those derived in this work (red large circles). P…
Figure 8
Figure 8. Figure 8: Mass-Mass plot of our studied sample (green squares) and of the X-ray selected comparison sample in Andreon (2016). The abscissa is the mass estimated from the richness, the ordinate is our fitted (mostly weak￾lensing based) mass for our sample and the caustic mass for…
Figure 10
Figure 10. Figure 10: Electron density profile of the four shear-selected clusters (posterior mean value with 68% uncertainty shaded) and of SZ-selected clusters (Ghirardini et al. 2020) of the same mass (red line with dashed corridor marking the ±2𝜎 range). The inset indicates the type of…
Figure 11
Figure 11. Figure 11: Pressure density profile of the four shear-selected clusters (posterior mean value with 68% uncertainty shaded) and of SZ-selected clusters (Ghirardini et al. 2020) of the same mass (red line with dashed corridor marking the ±2𝜎 range). The inset indicates the type of…
Figure 12
Figure 12. Figure 12: 𝑌sph,500 − 𝑀 plot for our shear-selected sample and for the biased sample formed by X-ray selected clusters at 𝑧 < 0.55 (from Marrone et al., 2012 and Nagarajan et al., 2019). The solid line indicates the fit to Nagarajan et al.(2019) data, that accounting for sample …
Figure 14
Figure 14. Figure 14: Mass-redshift plot of the eROSITA cosmological sample (black dots) and of our weak-lensing selected sample (blue circles with error bars). eROSITA masses are, in practice, count-rates converted to mass assuming that clusters have exactly the average X-ray luminosity f…

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