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REVIEW 3 major objections 5 minor 1 cited by

Detecting clusters and groups of galaxies populating the local Universe in large optical spectroscopic surveys

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read This paper claims that three group finders recover at least 80% of simulated galaxy groups and clusters above $10^{13}$ solar masses, with contamination below 10%, and that total stellar luminosity or mass beats velocity dispersion as a…

desk verdict A genuinely useful head-to-head benchmark of three group finders, though the headline completeness rests on a permissive matching rule that needs a sensitivity test. read the letter →

arxiv 2411.16455 v1 pith:JVLQL4XL submitted 2024-11-25 astro-ph.GA astro-ph.HE

I. Marini , P. Popesso , K. Dolag , M. Bravo , A. Robotham , E. Tempel , Q. Li , X. Yang
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B. Csizi P. Behroozi V. Biffi A. Biviano G. Lamer N. Malavasi D. Mazengo V. Toptun
This is my paper · ORCID
classification astro-ph.GAastro-ph.HE
keywords galaxygroupsclustersgroupfinderalgorithmsmocksurveyshalomassproxiesspectroscopiccompletenessandcontaminationconditionalluminosityfunction
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

This paper tries to establish that optical spectroscopic surveys can reliably find galaxy groups and clusters in the local Universe, despite the systematics that worry observers. The authors run three established group-detection algorithms on the same mock galaxy catalogue, built to mimic a wide deep spectroscopic survey down to redshift 0.2, and measure how well each recovers the known halos. They find that all three detect at least 80% of halos with $M_{200}\geq10^{13}\,M_\odot$, keep contamination below 10% at those masses, and assign member galaxies with at least roughly 70% accuracy above the group mass scale. They also find that total stellar luminosity or total stellar mass recovers halo mass more accurately than velocity dispersion, which matters because velocity-dispersion masses inherit membership errors. If correct, the result validates optical selection for dense regions and gives a practical recipe for using optical group catalogues in combination with X-ray data.

What carries the argument

The mechanism that carries the argument is a controlled mock experiment. A hydrodynamical cosmological simulation provides the true halo population; a lightcone (a redshift-bounded cone of mock sky) is converted into a galaxy catalogue with observed-frame magnitudes, Gaussian redshift errors of $\sigma=45\,\mathrm{km\,s^{-1}}$, stellar-mass errors of 0.2 dex, and 5% catastrophic redshift failures; and the three group finders are run on this catalogue. Their output is matched to the input halos by a cylinder defined by a projected offset of $R_{200}$ and a redshift window of $3\times10^{-3}$, with a factor-of-six mass-dominance rule used to decide which halo a detection belongs to when several fall inside. Detections are classified as primary, secondary fragments, or spurious, and these classes feed directly into the completeness and contamination numbers. The halo mass proxies are calibrated scaling relations (BCG stellar mass, total stellar mass, and $r$-band luminosity) whose logarithmic scatters are compared to those of the finders' own velocity-dispersion masses.

What would settle it

Rerun the same three finders on an independent mock and match using a stricter cylinder, for example half the virial radius and a redshift window of $10^{-3}$; if completeness at $M_{200}>10^{13}\,M_\odot$ drops below 80% or contamination rises above 10%, the headline numbers are artifacts of the matching convention rather than intrinsic properties of the finders.

Watch

Extended reading notes

Core claim

The central claim is a benchmark result, stated per group finder but holding for all three: on a simulated spectroscopic survey matching the depth and completeness of a wide local-Universe survey (redshift below 0.2, stellar masses complete above $10^{9.8}\,M_\odot$), the finders recover more than 80% of halos with $M_{200}$ above $10^{13}\,M_\odot$ and keep the fraction of spurious detections below 10% in that regime. Membership is at least 70% accurate above the group mass scale, rising further when measured by the brightest galaxies; the recovered conditional luminosity function of members matches the input halo catalogue. Because membership errors bias velocity-dispersion masses, the paper argues that the best halo mass proxy is the total stellar luminosity of the group (scatter 0.24--0.40 dex), closely followed by total stellar mass, and that using either proxy allows even low-richness groups to be kept in the catalogue. The comparison to a simulated X-ray observation of the same mock sky shows the optical catalogues are more complete at group scales, which the authors present as support for stacking X-ray data on optically selected groups.

Load-bearing premise

The completeness and contamination results depend on the paper's own matching rule, a correct detection being one within one virial radius and a redshift window of $3\times10^{-3}$ of a true halo, with the most massive halo selected when several fall in the cylinder, and this rule is not checked for sensitivity.

Editorial extensions

If this is right

  • For $M_{200}>10^{13}\,M_\odot$, all three finders recover at least 80% of halos, so optically selected group catalogues can be used to probe dense environments in the local Universe.
  • Contamination below $10^{13}\,M_\odot$ is dominated by interlopers and fragmentation, so low-mass groups projected near massive halos should be treated with caution.
  • Velocity-dispersion masses inherit membership errors, while total stellar luminosity or total stellar mass keeps the scatter small even when not all members are recovered; the paper recommends luminosity-based masses.
  • The recovered conditional luminosity function matches the input, so the finders are reliable for studying galaxy populations and evolution as a function of environment.
  • Optical selection yields a more complete halo mass distribution at group scales than the X-ray selection from the same simulation, supporting X-ray stacking on optically selected samples.

Reading between the lines

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

  • Editorial extension: the reported numbers are tied to the depth of a wide deep local-Universe survey; a direct test would rerun the same three finders on a mock of a shallower survey and measure whether completeness at $10^{13}\,M_\odot$ still holds.
  • Editorial extension: the matching rule could be made probabilistic, assigning detections to halos by membership overlap rather than a six-times-dominance criterion, and the comparison would show how much of the fragmentation statistics is an artifact of the matching convention.
  • Editorial extension: the luminosity-proxy result suggests a practical recipe for X-ray-era work: stack X-ray photons on optically selected groups chosen by luminosity-based masses, reaching below the X-ray detection threshold.
  • Editorial extension: the alternative-mock robustness check in the appendix only re-runs one finder; extending it to the other two finders would test whether the completeness result depends on the specific simulation's stellar mass function.
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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 / 5 minor

Summary. This paper benchmarks three optical group finders (Robotham et al. 2011, Yang et al. 2005, and Tempel et al. 2017) on a GAMA-like mock galaxy survey built from the Magneticum hydrodynamical simulation lightcone LC30. The authors simulate a spectroscopic galaxy sample down to z < 0.2 with stellar mass completeness M_star >= 10^9.8 M_sun, run the three finders, and compare their outputs to the SubFind halo catalogue. They report that all three finders achieve >80% completeness for halos with M200 > 10^13 M_sun, contamination below 10% in that regime, membership accuracy of at least 70% above the group scale, and that total stellar luminosity or total stellar mass are more reliable halo mass proxies than velocity dispersion. They also compare the optical catalogues with an X-ray eROSITA mock from the same simulation and check the impact of Magneticum's top-heavy GSMF using a UniverseMachine lightcone in Appendix A.

Significance. If the headline results are robust, this paper provides a useful, directly comparative calibration of three widely used group finders on the same simulation, which is valuable for interpreting current and upcoming spectroscopic surveys (SDSS, GAMA, DESI, WAVES) and for stacking eROSITA X-ray data on optically selected groups. The use of a realistic lightcone, a ground-truth SubFind halo catalogue, and an external UniverseMachine check are strengths. The authors are also transparent about several caveats, including the GSMF tension in Magneticum and the effect of membership errors on velocity-dispersion masses. However, the central quantitative claims rest on a matching rule that is not sensitivity-tested, and the mass-proxy comparison mixes an in-sample calibration with an external relation; these issues need to be addressed before the conclusions can be considered fully supported.

major comments (3)
  1. [Section 4.1 and Fig. 3] The definitions of completeness and contamination rely entirely on the hand-chosen matching rule: a detection is correct if its centre lies within R200 of a true halo and within dz < 3e-3, with a factor-of-six dominance criterion for multiple matches. No sensitivity analysis is provided for these parameters. The paper itself shows that the stricter DET+MEMB definition (at least 50% member-galaxy overlap, dashed lines in Fig. 3) reduces completeness at M200 > 10^13 M_sun to roughly 70%, below the headline >80% value. This indicates that the headline numbers are definition-dependent and should not be presented as absolute without demonstrating that the matching thresholds are inconsequential. I recommend reporting both definitions prominently in the abstract and adding a robustness test varying R200, the redshift window, and the dominance factor.
  2. [Section 4.3 and Table 2] The comparison of halo mass proxies is unfair because the total stellar mass proxy is calibrated directly on the Magneticum scaling relation, while the r-band luminosity proxy is taken from an external relation (Popesso et al. 2007). Consequently, the smaller scatter reported for luminosity in Table 2 may simply reflect that the luminosity relation is not fitted to the same simulation, whereas the stellar-mass relation absorbs Magneticum's specific scatter. To support the claim that stellar luminosity is the best proxy, both proxies should be calibrated on independent data or on the same simulation with an out-of-sample split. The in-sample nature of the stellar-mass calibration is a load-bearing issue for the central recommendation in the abstract.
  3. [Appendix A] The UniverseMachine check is presented as evidence that the results are robust to the Magneticum GSMF tension, but it only runs one of the three finders (R11) and only tests completeness, contamination, and the stellar-mass proxy scatter. It does not test the membership accuracy, the luminosity proxy comparison, or the fragmentation behaviour for the other two finders. Additionally, the reported velocity-dispersion scatter in the UniverseMachine test (0.71 dex) is twice that in Magneticum (0.35 dex), a major discrepancy that deserves explicit discussion rather than a one-line remark. The claim that the findings are 'robust' is therefore only partially supported.
minor comments (5)
  1. [Abstract and Section 2.2] The abstract states the survey is complete for M_star >= 10^9.8 M_sun, but Section 2.2 says 'no magnitude cut is applied.' Please clarify that the completeness refers to the stellar mass resolution limit of the simulation, not a survey selection.
  2. [Section 6, first bullet] The summary states the FOF catalogue is 'accurate (~80%)' in assigning galaxy members above 10^13 M_sun, while the abstract and Fig. 3 dashed lines indicate 70%. These numbers should be made consistent.
  3. [Table 1] In the last two rows, the T17 column increases from 14,185 (no FRAG_2) to 14,194 (no FRAG_2 and no SPUR_2). Since the latter is a subset of the former, this is impossible and is likely a typo; please check all entries in these rows.
  4. [Section 6] The summary lists SDSS bandpass as 'u, v, g, r, and i'; SDSS uses u, g, r, i, z, and the 'v' should be removed.
  5. [Section 4.2] The text says 'In the high mass end, contamination is mostly due to SPUR_2 sources,' but Fig. 4 shows that fragmentation also increases strongly with mass. Please clarify how SPUR_2 and FRAG_2 are distinguished in the contribution to contamination at the high-mass end.

Circularity Check

1 steps flagged · score 4.0 of 10

Detection benchmark is independent, but the stellar-mass/BCG halo-mass proxy comparison is partly in-sample: relations calibrated on Magneticum are evaluated against Magneticum halos in the same LC30 sample, so the quoted scatter is a fit residual rather than an out-of-sample prediction.

  1. fitted input called prediction [Section 4.3 (Halo mass proxies), Table 2 and Fig. 6]
    "We extract from Magneticum the scaling relation between total stellar mass and M200 and calibrate the halo mass proxy. ... Table 2 illustrates the result for the sample of groups in LC30. ... Both metrics show that the stellar luminosity is the mass proxy with the smallest scatter, followed by the total stellar mass."

    The total stellar mass and BCG stellar mass proxies are calibrated from the same Magneticum-based sample (LC30) whose SubFind M200 values are then treated as 'truth' in Table 2 and Fig. 6. The quoted scatter for these proxies (0.37-0.49 dex for total stellar mass in the summary) is therefore the residual of an in-sample fit, not an out-of-sample prediction: a relation fitted to a sample reproduces that sample with minimal scatter by construction. This calibrate-and-evaluate-on-the-same-data loop is used to conclude that luminosity and total stellar mass yield more accurate halo masses than velocity dispersion, while the velocity dispersion estimates use fixed external calibrations. The luminosity proxy uses an external Popesso et al.

full rationale

The central completeness and contamination claims are benchmarked against the independent SubFind halo catalogue, so they are not circular; the matching rule in Sect. 4.1 is hand-chosen and permissive (the paper's own DET+MEMB definition drops completeness to about 70% at M200 > 10^13 Msun), but that is a robustness/sensitivity limitation, not a definitional reduction. The UniverseMachine check in Appendix A provides an external cross-check, and the luminosity proxy is calibrated with the published Popesso et al. (2007) relation, so self-citations are not load-bearing. The one circular element is the in-sample calibration of the total stellar mass and BCG stellar mass proxies in Sect. 4.3: the relation is extracted from Magneticum and then evaluated against Magneticum halos in the same LC30 sample, making the reported scatter a fit residual. This affects the secondary claim that luminosity/mass proxies are more accurate than velocity dispersion, but the completeness and membership findings remain independent. Score 4 reflects partial circularity in one supporting claim, not in the paper's main detection benchmark.

Assumptions & free parameters 5 free parameters · 4 assumptions · 0 invented entities

The central numbers rest on two layers: the fidelity of the Magneticum mock (galaxy magnitudes, redshifts, errors, completeness) and the matching rule that defines a correct detection. The three group finders carry tuned parameters from their original papers, and the stellar mass proxy is calibrated and scored in-sample. No new physical entities are introduced; the SPUR and FRAG labels are analysis categories, not postulates.

free parameters (5)
  • R11 FOF linking length parameters = 2 base + 5 density contrast + 1 brightness parameters (brightness scaling set to 0 here)
    Calibrated in Robotham et al. 2011 against simulated lightcones; adopted unchanged except brightness scaling, affecting group merging and masses (Section 3.3).
  • T17 linking length ratio = radial = 10 x transversal; transversal from Tempel et al. 2014
    Chosen in prior work; the 10x ratio sets how many galaxies merge along the line of sight (Section 3.1).
  • Y05 background level B = 10
    Membership assignment threshold for PM(R, dz) >= B; changing it changes contamination and completeness (Section 3.2).
  • Mock error model parameters = sigma_v = 45 km/s; sigma_logMstar = 0.2 dex; 5% catastrophic failures
    Hand-set to mimic GAMA spectroscopic completeness; they shape the noise the finders see (Section 2.2).
  • Matching thresholds = R200 offset, dz = 3e-3, dominant mass ratio = 6
    Hand-chosen criteria define what counts as a correct detection; they directly set the reported completeness and contamination numbers (Section 4.1).
assumptions (4)
  • domain assumption The SubFind/FOF halo catalogue from Magneticum is a faithful ground truth for the halo population.
    The whole matching exercise treats these halos as truth; any error in halo identification propagates into completeness and contamination (Sections 2.2 and 4.1).
  • domain assumption The CIGALE SED fitting and K-correction step in the mock reproduces observed-frame magnitudes well enough for the finders.
    Magnitudes and redshifts drive the FOF linking and luminosity proxies; errors here are not propagated (Section 2.2).
  • domain assumption The top-heavy GSMF of Magneticum does not bias the relative performance of the finders.
    Acknowledged as a tension in Figure 2; Appendix A checks only R11 with UniverseMachine, so for T17 and Y05 the assumption stands unverified.
  • ad hoc to paper The matching rule (within R200 and dz < 3e-3, factor-of-six dominance) is a valid definition of a correct detection.
    This rule is introduced in Section 4.1 and is not externally calibrated; it determines the headline completeness and contamination values.

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Pith. "Pith review of Detecting clusters and groups of galaxies populating the local Universe in large optical spectroscopic surveys." pith.science (2026). https://pith.science/paper/JVLQL4XL

@misc{pith2026241116455,
  author       = {Pith},
  title        = {Pith review of: Detecting clusters and groups of galaxies populating the local Universe in large optical spectroscopic surveys},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/JVLQL4XL}},
  note         = {Machine review of arXiv:2411.16455}
}
abstract

Wide-field cosmological surveys provide hundreds of thousands of spectroscopically confirmed galaxy groups and clusters, valuable for tracing baryonic matter distribution. However, controlling systematics in identifying host dark matter halos and estimating their properties is crucial. We evaluate three group detection methods on a simulated dataset replicating the GAMA selection to understand systematics and selection effects. This is key for interpreting data from SDSS, GAMA, DESI, WAVES, and leveraging optical catalogues in the (X-ray) eROSITA era to quantify baryonic mass in galaxy groups. Using a lightcone from the Magneticum hydrodynamical simulation, we simulate a spectroscopic galaxy survey in the local Universe (down to $z<0.2$ and stellar mass completeness $M_{\star}\geq10^{9.8} M_{\odot}$). We assess completeness and contamination of reconstructed halo catalogues, evaluate membership accuracy, and analyse the halo mass recovery rate of group finders. All three group finders achieve high completeness ($>80\%$) at group and cluster scales, confirming optical selection's suitability for dense regions. Contamination at low masses ($M_{200}<10^{13} M_{\odot}$) arises from interlopers and fragmentation. Membership is at least 70\% accurate above the group mass scale, but inaccuracies bias halo mass estimates using galaxy velocity dispersion. Alternative proxies, like total stellar luminosity or mass, yield more accurate halo masses. The cumulative luminosity function of galaxy members matches predictions, showing the group finders' accuracy in identifying galaxy populations. These results confirm the reliability and completeness of spectroscopic catalogues produced by state-of-the-art group finders. This supports studies requiring large spectroscopic samples of galaxy groups and clusters, as well as investigations into galaxy evolution across diverse environments.

Figures

Figures reproduced from arXiv: 2411.16455 by the authors.

Figure 1
Figure 1. Distribution of the galaxies in LC30. A stellar mass cut ≥ 109.8M⊙ is applied to the galaxy sample. The survey is depicted in the redshift space down to redshift z < 0.2. scribes the optical halo finders run to detect the galaxy groups and clusters. Sect. 4 illustrates the outcome of the detection pro￾cedure evaluating completeness, contamination, and halo mass proxies. Sect. 5 focuses on the optical selection effec… view at source ↗
Figure 2
Figure 2. GSMF of the lightcone from Magneticum and UniverseMachine within z < 0.2. The mock catalogues are compared to the results from the SerExp model in Bernardi et al. (2013). the same volume but produced with UniverseMachine (Behroozi et al. 2019, 2023). We create a galaxy mock catalogue on which we run a group finder to test the hypothesis on the assumed GSMF in Magneticum. This is possible since the UniverseMa￾chine m… view at source ↗
Figure 3
Figure 3. Completeness (left panel) and contamination (right panel) as a function of halo mass. The shaded bands mark the binomial confidence interval. The solid lines report the definitions in Eq. 2–3 whereas the dashed lines report stricter ones provided in the main text. Notice that the y-axis is different in the two panels [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: Statistical distribution of the fragmentation as a function of the halo mass (left) and redshift (right panel). The shaded bands mark the binomial confidence interval. This represents the fraction of systems that have one or more fragments in the FOF catalogue. The col…
Figure 5
Figure 5. Figure 5: Percentage of BCG correctly identified for each detected halo in the input catalogue. The shaded band marks the dispersion given by the binomial confidence interval. galaxy member population. In other words, after matching the halo catalogues, we cross-match their gala…
Figure 6
Figure 6. Figure 6: Comparison of the estimated halo mass in the FOF catalogues as a function of the true input mass from Magneticum. Each row represents the results from the different group finders: R11, T17, and Y05 from top to bottom. Each panel reports a different halo mass proxy. The…
Figure 7
Figure 7. Figure 7: Scatter plot of the luminosity-based mass (best proxy) and true mass colour-coded for the accuracy of the membership Fgal for the three group finders. We define Fgal in Eq. 4. observational data, however, it provides us with insights into the recovery rate of the group…
Figure 8
Figure 8. Figure 8: CLF of all the member galaxies (left panel), only central galaxies (central panel), and only satellites (right panel) as a function of halo mass. The halo masses are split into five equally spaced logarithmic bins, whose median is reported in the legend. The samples of…
Figure 9
Figure 9. Figure 9: Number count distribution of the halo masses in the input cata￾logue (black dashed line) and the other samples. We report the Poisso￾nian uncertainty with the shaded area. We argue that the larger statistics offered by the optical selec￾tion allow one to study halos at…

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    No current simulation simultaneously reproduces observed halo hot-gas fractions and local galaxy star-formation/quenching demographics; strong AGN feedback overquenches, weak feedback retains too much gas.

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