REVIEW 3 major objections 4 minor 227 references
This paper shows that among isolated galaxies, lower-mass galaxies with lopsided 21-cm hydrogen profiles have higher specific star formation rates, a correlation predicted by cosmological simulations and pointing to stellar feedback as a dr
Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →
A new catalog of 389 isolated galaxies with clean 21-cm asymmetry measurements shows that low-mass asymmetric galaxies have elevated specific star formation, matching EAGLE predictions.
T0 review reviewed 2026-08-01 challenge →
load-bearing objection Solid reference catalog of isolated galaxies with HI asymmetry measurements; the EAGLE-like sSFR trend is plausible but the S/N robustness test is missing. the 3 major comments →
Asymmetries in spatially unresolved 21-cm emission line profiles of isolated galaxies
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
Core claim
The paper claims that in isolated galaxies, the lopsidedness of the integrated 21-cm profile (A_l, the fractional difference between the fluxes on the two velocity sides of the line) is a clean tracer of internal disturbance, and that its dominant driver depends on stellar mass. Based on 153 galaxies from UNAM-KIAS and 236 from AMIGA, it reports that A_l is independent of stellar mass, morphology, bar presence, HI fraction, and recent merger history, but that below M* ~ 10^10.3 Msun the most asymmetric galaxies have systematically higher specific star formation rates than their symmetric counterparts. The same behavior has been predicted for central galaxies in a large cosmological hydrodyna
What carries the argument
The key object is the lopsidedness measure A_l, computed from the fluxes on the low- and high-velocity halves of the 21-cm profile about its systemic velocity, which ranges from 0 (perfect symmetry) to 1. The analysis also relies on a beam-coverage selection using the HI size-mass relation to ensure that the single-dish beam captures most of the neutral gas, and on signal-to-noise and velocity-channel cuts designed to keep noise from inflating A_l. The A_l measure carries the entire asymmetry analysis: its convergence properties under noise determine which galaxies can be trusted and therefore what trends can be claimed.
Load-bearing premise
The claim that the S/N=10 cutoff yields reliable asymmetry measurements for the statistics used in this paper; the paper's own appendix shows that full convergence within 20% requires S/N about 60 over much of the asymmetry range, so if noise inflates A_l preferentially in low-mass, high-sSFR galaxies, the central correlation could be a noise artifact.
What would settle it
Take the released sample, keep only the galaxies with S/N above 60 (or apply a noise-debiasing correction), and recompute the median sSFR for the most versus least asymmetric quartiles below 10^10.3 Msun. If the positive offset disappears, the central claim fails; if it remains, the claim is confirmed. Alternatively, compare the A_l distribution of low-mass galaxies with high sSFR to a matched sample of low-sSFR galaxies at the same S/N.
If this is right
- If correct, the 389-galaxy catalog provides a reference set of isolated HI sources for comparing against galaxies in groups and clusters, where external perturbations are supposed to elevate asymmetry.
- The low-mass sSFR-A_l correlation implies that stellar feedback can leave a measurable imprint on the global HI profile, not just on resolved kinematics.
- The correlation gives modelers a direct test: galaxy formation simulations that predict the strength of feedback-driven outflows should reproduce the amplitude and mass dependence of the A_l-sSFR trend.
- The null results (independence from bars, morphology, merger stage) simplify the interpretation of asymmetry in isolated systems: those properties do not need to be controlled for in environmental comparisons.
- The paper's finding that isolated galaxies have higher HI fractions and lower star formation efficiencies than typical late-type centrals means that environmental references must use isolated samples, not field averages.
Where Pith is reading between the lines
- If the noise inflation at low S/N preferentially affects the lowest-mass galaxies (which also tend to have the highest sSFR), part of the reported correlation could be an artifact; re-analyzing with the S/N>60 subsample would settle this.
- The beam-coverage cut, while correct on average, may exclude the most extended HI disks; if those disks are also the most asymmetric, the absolute A_l distribution in the released catalog could be biased low, affecting any quantitative comparison with simulations.
- A natural extension would be to measure A_l for galaxies in the same mass range but in richer environments using the same pipeline; the difference in the sSFR-A_l slope between environments would directly isolate the external vs internal contribution.
- If the correlation holds, it suggests that a simple proxy — sSFR — could be used to predict which isolated galaxies are likely to show lopsided HI, useful for target selection with future high-resolution radio facilities.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper compiles new samples of isolated galaxies from the UNAM-KIAS and AMIGA catalogs with H I 21-cm line profiles from five single-dish surveys (H I-MaNGA, NIBLES, KLUN, ALFALFA, xGASS). Quality cuts include near-complete beam coverage using the Wang et al. (2016) size–mass relation, S/N>10, at least 20 velocity channels, and m_r<15.2, yielding 153 and 236 galaxies respectively. The authors measure the lopsidedness A_l using the Busy-function edge method of Manuwal et al. (2022), and derive ancillary stellar, gas, morphological, merger, and halo properties for the released catalog. The main physical claims are that isolated galaxies are predominantly late-type, star-forming, H I-rich, low-SFE systems, that bar fractions resemble normal spirals, that merger fractions are unexpectedly high, and—the headline result—that more H I-asymmetric galaxies have higher sSFRs below M*~10^10.3 Msun, in agreement with EAGLE predictions for centrals.
Significance. If the central trend is robust, the paper delivers a valuable reference catalog for environmental studies of H I asymmetry and provides observational support for stellar-feedback-driven asymmetries in low-mass isolated galaxies. The catalog construction is careful: cross-matching across five surveys, explicit beam-coverage cuts, channel-resolution requirements, and public release of measurements and ancillary properties are clear strengths. The convergence tests in Appendix A are also a useful addition to the literature. However, the headline sSFR–asymmetry correlation rests on A_l values measured at S/N=10, and the paper’s own Appendix A shows that this threshold is only reliable for A_l≳0.05–0.06. Because low-mass, high-sSFR galaxies are plausibly closer to the S/N cut, a direct S/N-robustness check is needed before the EAGLE-agreement claim can be considered established.
major comments (3)
- [Sec. 3.1.3, Eq. (3); Appendix A, Figs. A3–A4; Sec. 4.6, Fig. 12] The S/N=10 threshold is load-bearing for the headline sSFR–A_l trend. Appendix A shows that full-range 20% convergence of A_l requires S/N≈60, and that at S/N=10 only A_l≳0.05–0.06 is reliable. If low-mass galaxies in the sample have lower S/N near the cut (plausible for fainter, more distant or H I-poor objects), noise will preferentially inflate their A_l and push them into the upper quartile used in Fig. 12, potentially manufacturing the positive sSFR correlation at M*<10^10.3 Msun. The current manuscript reports neither S/N distributions per mass bin nor a high-S/N subsample test for Fig. 12. I request (i) S/N versus M* plots, (ii) a rerun of the Fig. 12 quartile analysis restricted to S/N≥20 and S/N≥30, and (iii) explicit discussion of how many low-mass galaxies have A_l below the reliable threshold. This is directly testable with the released catalog and is essential to the abstrac
- [Sec. 4.6, Fig. 12] The quartile split in Fig. 12 is presented without error bars, without confidence intervals on the medians, and without stating the minimum number of galaxies per mass bin. The two panels show UNAM-KIAS and AMIGA separately, but 59 galaxies are shared between the samples (Sec. 3.1.4), so the panels are not fully independent; it is not stated whether the trend in Fig. 12 persists if shared objects are removed from one sample. Given that Fig. 12 is the main observational result, the authors should add bootstrap confidence intervals, report significance tests (e.g., KS or permutation) per mass bin, and show the trend for the independent subsamples. Without these, the visual separation in the low-mass bins is not yet quantitatively established.
- [Sec. 4.6 and Sec. 6] The interpretation that the low-mass sSFR–A_l correlation is caused by stellar-feedback-driven outflows relies on the EAGLE analysis of Manuwal et al. (2022), which uses the same A_l definition and the same edge-finding method as the present paper. This is a methodological lineage rather than circular reasoning, but the agreement is less independent than it might appear. The paper should state explicitly that the EAGLE prediction is generated with the same asymmetry pipeline, and should note that the observational trend is also consistent with other mechanisms that raise both sSFR and H I asymmetry (e.g., recent gas accretion) before settling on feedback. A brief acknowledgment of this degeneracy would make the conclusion appropriately cautious.
minor comments (4)
- [Fig. 12 caption] The caption says 'orange curve shows the median asymmetry' but the plotted quantity is median sSFR. Please correct to 'median sSFR'.
- [Throughout] The text uses 'Hiline' as a single word in many places; this is typographically inconsistent (e.g., 'H I line' or 'H I-line' would be clearer). Also, 'eagle' appears lowercase in the abstract and text; consider using 'EAGLE' consistently.
- [Appendix A, Fig. A4] The description of the color coding mentions green points for v_eff=10 km/s at v_res=1.2, 2.6, 5.5 and orange for v_res=1.4, but in the figure the color legend is not fully self-explanatory. A short caption expansion would help the reader follow which survey each resolution combination represents.
- [Sec. 5, Eq. (14)] The conversion A_l = |A_fr−1|/(A_fr+1) is correct, but the text refers to 'the asymmetry measure' without noting that A_fr in the original papers uses the ratio of integrated fluxes defined in different ways (e.g., high/low vs. low/high). Please state explicitly that the convention is consistent with Eq. (2) so that readers can verify the conversion.
Circularity Check
No significant circularity: self-citations are methodological lineage, and the EAGLE comparison is an independent test rather than a fitted input.
full rationale
The paper's derivation chain is observational: it assembles isolated-galaxy samples from UNAM-KIAS and AMIGA, retrieves single-dish HI spectra, measures the lopsidedness A_l (Eq. 1), applies S/N and velocity-channel cuts, and compares the sSFR of A_l quartiles to the EAGLE prediction from Manuwal et al. (2022). No parameter is fitted to reproduce the headline sSFR–asymmetry trend. The A_l definition and edge-finding method come from Manuwal et al. (2022), and the same measure is used in the EAGLE comparison; this is methodological consistency, not a circular reduction, because the observed A_l values are independent data and the EAGLE prediction is an external simulation output. The S/N=10 threshold is acknowledged in Appendix A and Sec. 3.1.3 to give only ~20% convergence for A_l ≳ 0.05 and to require S/N≈60 for full-range convergence; the paper justifies the lower cut partly with a cited expectation that very symmetric profiles are rare (Watts et al. 2020b; Glowacki et al. 2022; Manuwal et al. 2022). That is a robustness/correctness concern, not a logical equivalence: the observed sSFR–A_l relation is not constructed from that expectation, and the paper discloses the limitation. No uniqueness theorem is imported from the authors' prior work, and no ansatz is disguised as externally established fact. The self-citations are dense but load-bearing only as methodology and as an independent simulation comparison, so the central claim retains independent empirical content.
Axiom & Free-Parameter Ledger
free parameters (3)
- S/N cut =
10
- Intrinsic disk thickness q =
0.2
- Beam coverage factor =
1
axioms (7)
- domain assumption The Wang et al. (2016) HI size–mass relation and self-similar HI profiles hold for isolated galaxies and predict total HI diameter from catalog M_HI.
- domain assumption Busy-function-fitted profile edges from Manuwal et al. (2022) approximate the noiseless line edges of observed single-dish spectra.
- domain assumption Unresolved HI profile asymmetry, measured by A_l, is a statistically unbiased population-level tracer of intrinsic HI asymmetry for randomly oriented galaxies.
- domain assumption The Tinker (2021) group catalog provides accurate halo masses and central/satellite assignments for isolated galaxies at z<0.08.
- domain assumption GSWLC-X2 SED-based stellar masses and SFRs remain on a consistent scale after cross-calibration relations from Durbala et al. (2020), Chang et al. (2015), and Siudek et al. (2024).
- standard math Standard frequentist statistics (KS, Mood's median, Spearman rank, bootstrap) are appropriate for the sample sizes and selection.
- domain assumption The Nevin et al. (2023) LDA merger classifier with a probability threshold of 0.9 reliably separates mergers from non-mergers at the population level.
Cite this review
Pith. "Pith review of Asymmetries in spatially unresolved 21-cm emission line profiles of isolated galaxies." pith.science (2026). https://pith.science/paper/2DUVEZQC
@misc{pith2026260716700,
author = {Pith},
title = {Pith review of: Asymmetries in spatially unresolved 21-cm emission line profiles of isolated galaxies},
year = {2026},
howpublished = {\url{https://pith.science/paper/2DUVEZQC}},
note = {Machine review of arXiv:2607.16700}
}
read the original abstract
The origin of asymmetry in the ${\rm H}\,{\scriptsize{\rm I}}$ of galaxies remains an elusive problem, largely due to the difficulties associated with distinguishing between its secular and external contributors. We have compiled a sample of local isolated galaxies from the UNAM-KIAS and the latest AMIGA samples with near-complete beam coverage and robust estimates of ${\rm H}\,{\scriptsize{\rm I}}$ line asymmetry. The ${\rm H}\,{\scriptsize{\rm I}}$ measurements are based on single-dish spectra sourced from five surveys: ${\rm H}\,{\scriptsize{\rm I}}$-MaNGA, NIBLES, KLUN, ALFALFA, and xGASS. Our galaxies tend to be late-type, star-forming centrals at all masses but exhibit slightly lower specific star formation rates (sSFRs) and higher ${\rm H}\,{\scriptsize{\rm I}}$ contents than expected. The latter is likely driven by lower star formation efficiency, weaker outflows, and additionally, higher accretion rate of gas onto the galaxy at $M_\star\lesssim 10^{10.3}\,\mathrm{M}_\odot$. AMIGA, however, shows systematically higher ${\rm H}\,{\scriptsize{\rm I}}$ masses than UNAM-KIAS, which we attribute to higher local densities probed by the latter. Furthermore, both samples show bar frequencies similar to normal spirals, indicating that the gravitational instabilities leading to bars predominantly stem from internal processes, as suggested by recent works. Our galaxies show unexpectedly high merger fractions, possibly due to sampling bias and/or the inability of the classification method to distinguish between flybys and encounters leading to coalescence. We also find higher sSFRs for asymmetric galaxies below $M_\star\sim 10^{10.3}\,\mathrm{M}_\odot$, in agreement with the predictions for centrals from the ${\scriptsize{\rm EAGLE}}$ simulation. We release the ${\rm H}\,{\scriptsize{\rm I}}$ measurements along with ancillary galaxy and halo properties for public use.
Figures
Reference graph
Works this paper leans on
-
[1]
Abazajian K. N., et al., 2009, @doi [ ] 10.1088/0067-0049/182/2/543 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..543A 182, 543
-
[2]
Adelman-McCarthy J. K., et al., 2007, @doi [ ] 10.1086/518864 , https://ui.adsabs.harvard.edu/abs/2007ApJS..172..634A 172, 634
doi:10.1086/518864 2007
-
[3]
Aguerri J. A. L., M \'e ndez-Abreu J., Corsini E. M., 2009, @doi [ ] 10.1051/0004-6361:200810931 , https://ui.adsabs.harvard.edu/abs/2009A&A...495..491A 495, 491
-
[4]
Ahn C. P., et al., 2014, @doi [ ] 10.1088/0067-0049/211/2/17 , https://ui.adsabs.harvard.edu/abs/2014ApJS..211...17A 211, 17
-
[5]
Aquino-Ort \' z E., Cervantes-Sodi B., Chim-Ramirez K., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2512.21303 , https://ui.adsabs.harvard.edu/abs/2025arXiv251221303A p. arXiv:2512.21303
-
[6]
Argudo-Fern \'a ndez M., et al., 2014, @doi [ ] 10.1051/0004-6361/201322498 , https://ui.adsabs.harvard.edu/abs/2014A&A...564A..94A 564, A94
-
[7]
Argudo-Fern \'a ndez M., et al., 2015, @doi [ ] 10.1051/0004-6361/201526016 , https://ui.adsabs.harvard.edu/abs/2015A&A...578A.110A 578, A110
-
[8]
Argudo-Fern \'a ndez M., Shen S., Sabater J., Duarte Puertas S., Verley S., Yang X., 2016, @doi [ ] 10.1051/0004-6361/201628232 , https://ui.adsabs.harvard.edu/abs/2016A&A...592A..30A 592, A30
-
[9]
Astropy Collaboration et al., 2018, @doi [ ] 10.3847/1538-3881/aabc4f , https://ui.adsabs.harvard.edu/abs/2018AJ....156..123A 156, 123
-
[10]
Athanassoula E., Machado R. E. G., Rodionov S. A., 2013, @doi [ ] 10.1093/mnras/sts452 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.429.1949A 429, 1949
-
[11]
Barazza F. D., Jogee S., Marinova I., 2008, @doi [ ] 10.1086/526510 , https://ui.adsabs.harvard.edu/abs/2008ApJ...675.1194B 675, 1194
doi:10.1086/526510 2008
-
[12]
Barbani F., Pascale R., Marinacci F., Sales L. V., Vogelsberger M., Torrey P., Li H., 2023, @doi [ ] 10.1093/mnras/stad2152 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524.4091B 524, 4091
-
[13]
Becerra F., Escala A., 2014, @doi [ ] 10.1088/0004-637X/786/1/56 , https://ui.adsabs.harvard.edu/abs/2014ApJ...786...56B 786, 56
-
[15]
Bickley R. W., et al., 2021, @doi [ ] 10.1093/mnras/stab806 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.504..372B 504, 372
-
[16]
Bilicki M., et al., 2021, @doi [ ] 10.1051/0004-6361/202140352 , https://ui.adsabs.harvard.edu/abs/2021A&A...653A..82B 653, A82
-
[18]
Blanton M. R., et al., 2005, @doi [ ] 10.1086/429803 , https://ui.adsabs.harvard.edu/abs/2005AJ....129.2562B 129, 2562
doi:10.1086/429803 2005
-
[19]
Blanton M. R., et al., 2017, @doi [ ] 10.3847/1538-3881/aa7567 , https://ui.adsabs.harvard.edu/abs/2017AJ....154...28B 154, 28
-
[20]
Blumenthal K. A., Barnes J. E., 2018, @doi [ ] 10.1093/mnras/sty1605 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479.3952B 479, 3952
-
[21]
Bok J., Blyth S. L., Gilbank D. G., Elson E. C., 2019, @doi [ ] 10.1093/mnras/sty3448 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484..582B 484, 582
-
[22]
Boquien M., Burgarella D., Roehlly Y., Buat V., Ciesla L., Corre D., Inoue A. K., Salas H., 2019, @doi [ ] 10.1051/0004-6361/201834156 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.103B 622, A103
-
[23]
Boselli A., Cortese L., Boquien M., Boissier S., Catinella B., Gavazzi G., Lagos C., Saintonge A., 2014, @doi [ ] 10.1051/0004-6361/201322313 , https://ui.adsabs.harvard.edu/abs/2014A&A...564A..67B 564, A67
-
[24]
Bournaud F., Combes F., 2002, @doi [ ] 10.1051/0004-6361:20020920 , https://ui.adsabs.harvard.edu/abs/2002A&A...392...83B 392, 83
-
[25]
Bournaud F., Combes F., Jog C. J., Puerari I., 2005, @doi [ ] 10.1051/0004-6361:20052631 , https://ui.adsabs.harvard.edu/abs/2005A&A...438..507B 438, 507
-
[26]
Bradford J. D., Geha M. C., Blanton M. R., 2015, @doi [ ] 10.1088/0004-637X/809/2/146 , https://ui.adsabs.harvard.edu/abs/2015ApJ...809..146B 809, 146
-
[27]
H., Rhee M.-H., 1997, , https://ui.adsabs.harvard.edu/abs/1997A&A...324..877B 324, 877
Broeils A. H., Rhee M.-H., 1997, , https://ui.adsabs.harvard.edu/abs/1997A&A...324..877B 324, 877
1997
-
[28]
M., Governato F., Quinn T., Brook C
Brooks A. M., Governato F., Quinn T., Brook C. B., Wadsley J., 2009, @doi [ ] 10.1088/0004-637X/694/1/396 , https://ui.adsabs.harvard.edu/abs/2009ApJ...694..396B 694, 396
-
[30]
Bundy K., et al., 2015, @doi [ ] 10.1088/0004-637X/798/1/7 , https://ui.adsabs.harvard.edu/abs/2015ApJ...798....7B 798, 7
-
[31]
Buta R. J., et al., 2019, @doi [ ] 10.1093/mnras/stz1780 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.2175B 488, 2175
-
[32]
CHIME Collaboration et al., 2022, @doi [ ] 10.3847/1538-4365/ac6fd9 , https://ui.adsabs.harvard.edu/abs/2022ApJS..261...29C 261, 29
-
[33]
Calette A. R., Avila-Reese V., Rodr \' guez-Puebla A., Hern \'a ndez-Toledo H., Papastergis E., 2018, @doi [ ] 10.48550/arXiv.1803.07692 , https://ui.adsabs.harvard.edu/abs/2018RMxAA..54..443C 54, 443
-
[34]
R., Avila-Reese V., Rodr \' guez-Puebla A., Lagos C
Calette A. R., Avila-Reese V., Rodr \' guez-Puebla A., Lagos C. d. P., Catinella B., 2021, @doi [ ] 10.1093/mnras/stab1282 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505..304C 505, 304
-
[35]
H., eds, , Secular Evolution of Galaxies
Calzetti D., 2013, in Falc \'o n-Barroso J., Knapen J. H., eds, , Secular Evolution of Galaxies. p. 419, @doi 10.48550/arXiv.1208.2997
-
[37]
Catinella B., et al., 2018, @doi [ ] 10.1093/mnras/sty089 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.476..875C 476, 875
-
[38]
Cavanagh M. K., Bekki K., 2020, @doi [ ] 10.1051/0004-6361/202037963 , https://ui.adsabs.harvard.edu/abs/2020A&A...641A..77C 641, A77
-
[39]
Cen R., Pop A. R., Bahcall N. A., 2014, @doi [Proceedings of the National Academy of Science] 10.1073/pnas.1407300111 , https://ui.adsabs.harvard.edu/abs/2014PNAS..111.7914C 111, 7914
-
[40]
Chakrabarti S., Bigiel F., Chang P., Blitz L., 2011, @doi [ ] 10.1088/0004-637X/743/1/35 , https://ui.adsabs.harvard.edu/abs/2011ApJ...743...35C 743, 35
-
[41]
Chang Y.-Y., van der Wel A., da Cunha E., Rix H.-W., 2015, @doi [ ] 10.1088/0067-0049/219/1/8 , https://ui.adsabs.harvard.edu/abs/2015ApJS..219....8C 219, 8
-
[42]
Chen X., 2011, @doi [Scientia Sinica Physica, Mechanica & Astronomica] 10.1360/132011-972 , https://ui.adsabs.harvard.edu/abs/2011SSPMA..41.1358C 41, 1358
-
[43]
S., 2007, @doi [ ] 10.1086/511060 , https://ui.adsabs.harvard.edu/abs/2007ApJ...658..884C 658, 884
Choi Y.-Y., Park C., Vogeley M. S., 2007, @doi [ ] 10.1086/511060 , https://ui.adsabs.harvard.edu/abs/2007ApJ...658..884C 658, 884
doi:10.1086/511060 2007
-
[45]
Comerford J. M., et al., 2024, @doi [ ] 10.3847/1538-4357/ad1a15 , https://ui.adsabs.harvard.edu/abs/2024ApJ...963...53C 963, 53
-
[46]
Correa C. A., Schaye J., Wyithe J. S. B., Duffy A. R., Theuns T., Crain R. A., Bower R. G., 2018a, @doi [ ] 10.1093/mnras/stx2332 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473..538C 473, 538
-
[47]
A., Schaye J., van de Voort F., Duffy A
Correa C. A., Schaye J., van de Voort F., Duffy A. R., Wyithe J. S. B., 2018b, @doi [ ] 10.1093/mnras/sty871 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478..255C 478, 255
-
[48]
Correa C. A., Schaye J., Trayford J. W., 2019, @doi [ ] 10.1093/mnras/stz295 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.4401C 484, 4401
-
[49]
Davies J. J., Crain R. A., Oppenheimer B. D., Schaye J., 2020, @doi [ ] 10.1093/mnras/stz3201 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.4462D 491, 4462
-
[50]
Dawson K. S., et al., 2013, @doi [ ] 10.1088/0004-6256/145/1/10 , https://ui.adsabs.harvard.edu/abs/2013AJ....145...10D 145, 10
-
[51]
Deg N., Blyth S. L., Hank N., Kruger S., Carignan C., 2020, @doi [ ] 10.1093/mnras/staa1368 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.495.1984D 495, 1984
-
[52]
Dekel A., Birnboim Y., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10145.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.368....2D 368, 2
arXiv 2006
-
[53]
D \'e nes H., Kilborn V. A., Koribalski B. S., 2014, @doi [ ] 10.1093/mnras/stu1337 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444..667D 444, 667
-
[54]
Dewdney P. E., Hall P. J., Schilizzi R. T., Lazio T. J. L. W., 2009, @doi [IEEE Proceedings] 10.1109/JPROC.2009.2021005 , https://ui.adsabs.harvard.edu/abs/2009IEEEP..97.1482D 97, 1482
arXiv 2009
-
[55]
Dey A., et al., 2019, @doi [ ] 10.3847/1538-3881/ab089d , https://ui.adsabs.harvard.edu/abs/2019AJ....157..168D 157, 168
-
[56]
Di Matteo P., Combes F., Melchior A. L., Semelin B., 2007, @doi [ ] 10.1051/0004-6361:20066959 , https://ui.adsabs.harvard.edu/abs/2007A&A...468...61D 468, 61
-
[57]
Dom \' nguez S \'a nchez H., Margalef B., Bernardi M., Huertas-Company M., 2022, @doi [ ] 10.1093/mnras/stab3089 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.4024D 509, 4024
-
[58]
Driver S. P., Popescu C. C., Tuffs R. J., Liske J., Graham A. W., Allen P. D., de Propris R., 2007, @doi [ ] 10.1111/j.1365-2966.2007.11862.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.379.1022D 379, 1022
arXiv 2007
-
[59]
Durbala A., Finn R. A., Crone Odekon M., Haynes M. P., Koopmann R. A., O'Donoghue A. A., 2020, @doi [ ] 10.3847/1538-3881/abc018 , https://ui.adsabs.harvard.edu/abs/2020AJ....160..271D 160, 271
-
[60]
Dutta R., et al., 2022, @doi [Journal of Astrophysics and Astronomy] 10.1007/s12036-022-09875-y , https://ui.adsabs.harvard.edu/abs/2022JApA...43..103D 43, 103
-
[61]
Ellison S. L., Patton D. R., Simard L., McConnachie A. W., 2008, @doi [ ] 10.1088/0004-6256/135/5/1877 , https://ui.adsabs.harvard.edu/abs/2008AJ....135.1877E 135, 1877
-
[62]
Ellison S. L., Mendel J. T., Patton D. R., Scudder J. M., 2013, @doi [ ] 10.1093/mnras/stt1562 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.435.3627E 435, 3627
-
[63]
Ellison S. L., Catinella B., Cortese L., 2018, @doi [ ] 10.1093/mnras/sty1247 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.3447E 478, 3447
-
[64]
Erwin P., 2018, @doi [ ] 10.1093/mnras/stx3117 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.474.5372E 474, 5372
-
[65]
Espada D., Verdes-Montenegro L., Huchtmeier W. K., Sulentic J., Verley S., Leon S., Sabater J., 2011, @doi [ ] 10.1051/0004-6361/201016117 , https://ui.adsabs.harvard.edu/abs/2011A&A...532A.117E 532, A117
-
[66]
Euclid Collaboration et al., 2025, @doi [ ] 10.1051/0004-6361/202450810 , https://ui.adsabs.harvard.edu/abs/2025A&A...697A...1E 697, A1
-
[67]
Ewen H. I., Purcell E. M., 1951, @doi [ ] 10.1038/168356a0 , https://ui.adsabs.harvard.edu/abs/1951Natur.168..356E 168, 356
doi:10.1038/168356a0 1951
-
[68]
Fanali R., Dotti M., Fiacconi D., Haardt F., 2015, @doi [ ] 10.1093/mnras/stv2247 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.454.3641F 454, 3641
-
[70]
Fern \'a ndez Lorenzo M., Sulentic J., Verdes-Montenegro L., Ruiz J. E., Sabater J., S \'a nchez S., 2012b, @doi [ ] 10.1051/0004-6361/201118660 , https://ui.adsabs.harvard.edu/abs/2012A&A...540A..47F 540, A47
-
[71]
Fern \'a ndez Lorenzo M., Sulentic J., Verdes-Montenegro L., Argudo-Fern \'a ndez M., 2013, @doi [ ] 10.1093/mnras/stt1020 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.434..325F 434, 325
-
[72]
Firmani C., Avila-Reese V., 2000, @doi [ ] 10.1046/j.1365-8711.2000.03338.x , https://ui.adsabs.harvard.edu/abs/2000MNRAS.315..457F 315, 457
arXiv 2000
-
[73]
Flores Vel \'a zquez J. A., et al., 2021, @doi [ ] 10.1093/mnras/staa3893 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.501.4812F 501, 4812
-
[74]
Forbes J. C., et al., 2023, @doi [ ] 10.3847/1538-4357/acb53e , https://ui.adsabs.harvard.edu/abs/2023ApJ...948..107F 948, 107
-
[75]
Fragkoudi F., Grand R. J. J., Pakmor R., G \'o mez F., Marinacci F., Springel V., 2025, @doi [ ] 10.1093/mnras/staf389 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.538.1587F 538, 1587
-
[76]
Frosst M., Obreschkow D., Ludlow A., Fraser-McKelvie A., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2508.14626 , https://ui.adsabs.harvard.edu/abs/2025arXiv250814626F p. arXiv:2508.14626
-
[77]
Ghosh S., Saha K., Jog C. J., Combes F., Di Matteo P., 2022, @doi [ ] 10.1093/mnras/stac461 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.511.5878G 511, 5878
-
[78]
Glowacki M., Deg N., Blyth S. L., Hank N., Dav \'e R., Elson E., Spekkens K., 2022, @doi [ ] 10.1093/mnras/stac2684 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.1282G 517, 1282
-
[79]
Grossi M., et al., 2016, @doi [ ] 10.1051/0004-6361/201628123 , https://ui.adsabs.harvard.edu/abs/2016A&A...590A..27G 590, A27
-
[80]
P., Giovanelli R., Chincarini G
Haynes M. P., Giovanelli R., Chincarini G. L., 1984, @doi [ ] 10.1146/annurev.aa.22.090184.002305 , https://ui.adsabs.harvard.edu/abs/1984ARA&A..22..445H 22, 445
arXiv 1984
-
[81]
Haynes M. P., Hogg D. E., Maddalena R. J., Roberts M. S., van Zee L., 1998, @doi [ ] 10.1086/300166 , https://ui.adsabs.harvard.edu/abs/1998AJ....115...62H 115, 62
doi:10.1086/300166 1998
-
[82]
Haynes M. P., et al., 2018, @doi [ ] 10.3847/1538-4357/aac956 , https://ui.adsabs.harvard.edu/abs/2018ApJ...861...49H 861, 49
-
[83]
Heald G., et al., 2011, @doi [ ] 10.1051/0004-6361/201015938 , https://ui.adsabs.harvard.edu/abs/2011A&A...526A.118H 526, A118
-
[84]
Hern \'a ndez-Toledo H. M., V \'a zquez-Mata J. A., Mart \' nez-V \'a zquez L. A., Avila Reese V., M \'e ndez-Hern \'a ndez H., Ortega-Esbr \' S., N \'u \ n ez J. P. M., 2008, @doi [ ] 10.1088/0004-6256/136/5/2115 , https://ui.adsabs.harvard.edu/abs/2008AJ....136.2115H 136, 2115
-
[85]
Hern \'a ndez-Toledo H. M., V \'a zquez-Mata J. A., Mart \' nez-V \'a zquez L. A., Choi Y.-Y., Park C., 2010, @doi [ ] 10.1088/0004-6256/139/6/2525 , https://ui.adsabs.harvard.edu/abs/2010AJ....139.2525H 139, 2525
-
[86]
Hern \'a ndez-Toledo H. M., M \'e ndez-Hern \'a ndez H., Aceves H., Olgu \' n L., 2011, @doi [ ] 10.1088/0004-6256/141/3/74 , https://ui.adsabs.harvard.edu/abs/2011AJ....141...74H 141, 74
This paper was first reviewed by deepseek-v4-flash on August 1, 2026.
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