Pith. sign in

REVIEW 3 major objections 5 minor 85 references

Alignment of Blue/Green and Red Early-type Galaxies with Large-scale Filaments Reveals Distinct Evolutionary Pathways

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

Pith's one-line read Red early-type galaxies point along cosmic filaments; blue and green early-type galaxies do not, suggesting they formed by different routes.

desk verdict A carefully controlled new null result for blue/green ETG alignment, worth a serious referee, but the 'distinct pathways' title overshoots the data. read the letter →

arxiv 2411.14885 v3 pith:3VUCE3ZN submitted 2024-11-22 astro-ph.GA

classification astro-ph.GA
keywords galaxyalignmentearly-typegalaxiescosmicfilamentsevolutionbluegreenvalleylarge-scalestructure
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 asks whether the well-known tendency of early-type galaxies to align with large-scale filaments is shared by blue and green early-type galaxies, which have younger stars and more star formation than their red counterparts. Using a spectroscopic sample of central galaxies and a filament catalog, it measures the angle between each galaxy's major axis and the nearest filament spine, then compares the red and non-red populations. It finds that red early-type galaxies show a clear alignment signal ($I(\theta)=1.30 \pm 0.05$, about $6\sigma$), while non-red early-type galaxies show no significant alignment ($I(\theta)=1.07 \pm 0.08$, $p=0.13$), and the two populations differ at about the $0.003$ level. The authors conclude that red and non-red early-type galaxies probably formed through different pathways, with filament-synchronized mergers shaping red galaxies and less ordered assembly producing the blue and green ones.

What carries the argument

The central object is the alignment statistic $I(\theta)=N_{0-45}/N_{45-90}$, the ratio of early-type galaxies whose major axis lies within $45^\circ$ of the filament spine to those lying farther away; a uniform distribution gives $I(\theta)\simeq 1$, and values above $1$ signal alignment. To make the comparison fair, the paper builds a mass-weighting control that resamples red early-type galaxies to match the stellar-mass distribution of the non-red sample, then repeats the comparison with equal sample sizes. It also checks that stellar mass, distance to the filament, and redshift are statistically indistinguishable between the two samples, and it tests the angle distributions against uniformity and against each other with Kolmogorov--Smirnov tests. This machinery is what supports the claim that the alignment difference is intrinsic to the color division rather than an artifact of sample properties.

What would settle it

Re-measuring the major axes of the same non-red early-type galaxies from higher-resolution imaging, then recomputing the alignment statistic with the same filament catalog, would settle the claim: a significant excess of angles below $45^\circ$ would overturn the null result, while a distribution consistent with $I(\theta)=1$ at high significance would confirm it.

Watch

Extended reading notes

Core claim

The central discovery is a statistically distinct alignment behavior between red and non-red early-type galaxies. For red galaxies the ratio statistic $I(\theta)=N_{0-45}/N_{45-90}$ is $1.30 \pm 0.05$, meaning substantially more galaxies lie within $0^\circ$--$45^\circ$ of the filament direction than within $45^\circ$--$90^\circ$, with a Kolmogorov--Smirnov $p \sim 10^{-8}$ against a uniform distribution. Non-red galaxies give $I(\theta)=1.07 \pm 0.08$, consistent with a uniform distribution ($p=0.13$). A two-sample test comparing the two angle distributions gives $p \simeq 0.003$. The difference persists after weighting the red sample to match the non-red sample's stellar-mass distribution and after matching the two sample sizes, so it is not attributable to differences in mass, distance to the filament spine, redshift, or sampling size. The paper therefore claims that the filament-alignment signal previously attributed to early-type galaxies as a class is carried almost entirely by red, quiescent galaxies, while non-red early-type galaxies appear essentially unaligned.

Load-bearing premise

The whole comparison assumes the survey's fitted position angle reliably captures the true direction of each non-red early-type galaxy; if those galaxies are too irregular for the fit, noise could wash out a real alignment.

Editorial extensions

If this is right

  • Any future alignment study of early-type galaxies in filaments must treat red and non-red galaxies separately, because the known filament-alignment signal is driven almost entirely by the red population.
  • Non-red early-type galaxies cannot simply be red galaxies caught before they turn red; if they were, they would have inherited the same aligned orientations.
  • The preferred formation route for red early-type galaxies is merger-driven assembly along the filament spine, while non-red early-type galaxies likely formed through disk instability, gas-rich random mergers, or recent transformations that reset their orientation.
  • If expanded samples confirm that non-red early-type galaxies are unaligned, current models for how these galaxies form and evolve will need revision.

Reading between the lines

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

  • An untested gradient may exist: if green-valley galaxies in the sample are closer to the red sequence, they might show an intermediate alignment strength that the current sample size cannot resolve.
  • Alignment statistics could be used as a rough clock for morphological reset: a galaxy's orientation memory may encode how recently its last major merger or quenching event occurred.
  • The same color-selected comparison could be applied to star-forming disk galaxies, where blue disks might show a different spin-alignment pattern than red spheroids; finding an opposite pattern would sharpen the evolutionary interpretation.
Share X Bluesky LinkedIn Reddit HN

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. The paper uses SDSS data and the Tempel et al. (2014) filament catalog to measure the alignment of the major axes of red and non-red early-type galaxies (ETGs) with their host filaments. Selecting central ETGs with M*>1e9.5 Msun and distances dgf<=1 Mpc/h, the authors report that red ETGs show significant alignment (I(theta)=1.30+/-0.05, K-S p~1e-8 in the mass-weighted sample), while non-red (blue/green) ETGs show no significant alignment (I(theta)=1.07+/-0.08, p=0.13), with a two-sample K-S p~0.003. They interpret this difference as evidence for distinct evolutionary pathways for red and non-red ETGs.

Significance. If the differential alignment signal is robust, this is a valuable empirical constraint on galaxy formation: it extends filament-alignment studies to blue/green ETGs and suggests that their recent assembly histories differ from those of quiescent red ETGs. The analysis is carefully controlled in several respects: the authors apply mass weighting, match sample sizes, use K-S tests to quantify both the alignment and the null result, and report bootstrap uncertainties. However, the central conclusion rests on the assumption that the SDSS photoObj.deVPhi_r parameter reliably traces the intrinsic major axis for non-red ETGs, a population that is plausibly less regular than red ETGs. That assumption is not validated in the manuscript, and the overstatement of the null result in the abstract and discussion further weakens the interpretation.

major comments (3)
  1. [Section 2] The claim that nETGs show no alignment is load-bearing for the paper, but the only justification for the position-angle estimator is the statement that photoObj.deVPhi_r is 'a reliable metric for elliptical galaxies with de Vaucouleurs R1/4 surface brightness profile'. Non-red ETGs are, by construction, bluer and are expected to be less regular (disky, patchy, or recently disturbed); for such galaxies a forced single de Vaucouleurs fit can produce noisy or biased position angles. If PA scatter is larger for nETGs than for rETGs, the measured I(theta) will be compressed toward unity, producing exactly the observed null. The authors should provide an independent validation of deVPhi_r for nETGs: for example, compare it with alternative position-angle measurements (isophotal ellipse fits, 2D light-profile models such as GALFIT, or visual classifications) on matched subsamples, and show that the PA uncertainty distribution is comparable between nETGs and rETGs. Without this, the differential result is not secure.
  2. [Abstract and Section 4] The wording 'no significant alignment signal' in the abstract and 'absence of alignment' in Section 4 overstates the evidence. A K-S p-value of 0.13 against uniform means the nETG data are consistent with no alignment, but they cannot establish that alignment is absent; the current I(theta)=1.07+/-0.08 is also consistent with a weak alignment of roughly 1.2 or lower. The authors themselves acknowledge this in Section 4 ('does not entirely rule out the possibility of a weak alignment'). The abstract and summary should be rephrased to 'no significant alignment detected' and, ideally, an upper limit or confidence interval on I(theta) for nETGs should be reported.
  3. [Section 4] The robustness checks are asserted but not presented. The text claims that the alignment patterns remain unchanged when selecting with photoObj.deV ABr>0.7, ABr>0.6, M*>1e10 Msun, or M*>1e10.5 Msun, but no I(theta) values, K-S p-values, or two-sample p-values are given for these cases. Since these checks are part of the evidence that the rETG/nETG difference is not an artifact of sample-selection thresholds, the corresponding numerical results should be provided in a table or appendix.
minor comments (5)
  1. [Section 2, Eq. (2)] The quantity n'_rETG,i defined in Eq. (2) is generally non-integer (since w and max(w) are real numbers), but the text says galaxies are 'randomly selected' according to this number. Please clarify how fractional selection is implemented (e.g., rounding, Poisson sampling, or weighted resampling), because this affects the effective sample size and the interpretation of the reported N=3225.
  2. [Figure 3 and Section 3] The two-sample K-S p-value of 0.003 is not extremely small, and the paper tests multiple thresholds and sample constructions. Please state whether the reported p-values are raw or corrected for multiple comparisons, and if corrected, describe the procedure.
  3. [Section 2] The 'non-red' category combines blue and green galaxies. If green ETGs behave differently from blue ETGs (e.g., green ETGs may be transitional), the combined sample could dilute a real alignment signal. A split into blue and green subsamples, or at least a comment on their relative alignment strengths, would strengthen the interpretation.
  4. [Title page] The received/revised line 'Revised tomorrow; Accepted the day after tomorrow' is not appropriate for a journal submission and should be removed. There are also typos: 'classfied' in the Introduction, 'Acedemy' in the affiliation, 'wavelengh' in the Acknowledgments, and 'W A VES' spacing for WAVES.
  5. [References] The Troxel & Ishak (2014) reference is cited as arXiv:1047.6990; the correct identifier is arXiv:1407.6990. Please check all arXiv identifiers and journal page numbers for consistency.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the alignment statistic is measured directly from observed position angles and filament orientations, with no fitted parameter or self-citation chain producing the central result.

full rationale

The central measurement is direct: galaxy position angles come from SDSS photoObj.deVPhi_r, filament spine orientations come from the Tempel et al. (2014) catalog, the angle theta is defined geometrically in the plane of the sky, and I(theta) is computed as a ratio of counts in two angle bins. No parameter is fitted to the alignment data. The color division uses the Papastergis et al. (2013) boundary, the stellar mass estimates use Bell et al. (2003), and the mass-weighting procedure is an explicit control that does not alter the qualitative result. The only self-citations, Rong et al. (2019, 2024), are used to define I(theta), which is a standard count-ratio statistic rather than a prior alignment claim imported as evidence. The rETG alignment is also compared with external results, such as Tempel et al. (2013). The interpretation of distinct evolutionary pathways is speculative discussion rather than a derived, falsifiable prediction of the measurement pipeline. The concern that photoObj.deVPhi_r may be less reliable for blue/green early-type galaxies is a possible data-quality limitation that could affect the physical conclusion, but it is not circular reasoning: the analysis does not assume the nETG null result at any step. The paper is therefore self-contained as a measurement and contains no circular derivation.

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

The measurement rests on external catalogs and empirical calibrations, but the paper fits no parameters to the alignment signal itself. The listed thresholds are standard selection cuts with robustness checks.

free parameters (4)
  • Stellar mass threshold = M* > 10^9.5 Msun
    Selected to ensure reliable alignment signal based on prior work; authors test robustness to higher thresholds (10^10 and 10^10.5 Msun).
  • Filament distance threshold = dgf <= 1.0 Mpc/h
    Approximate filament boundary used in prior studies (Wang et al. 2024).
  • Axis ratio threshold = deV ABr > 0.8 galaxies removed
    Removes galaxies with uncertain position angles; robustness tested with 0.7 and 0.6 thresholds.
  • Color boundary = g-i = -0.0571(Mr+24)+1.25
    Taken from Papastergis et al. (2013) to split red and non-red samples; not fitted in this paper.
assumptions (5)
  • domain assumption The Tempel et al. (2014) filament catalog correctly identifies large-scale filaments and their spine orientations.
    The alignment analysis depends entirely on these filament orientations.
  • domain assumption The SDSS photoObj.deVPhi_r parameter reliably measures the position angle of the major axis for ETGs.
    Used directly to compute theta; this is the weakest load-bearing assumption, especially for non-red ETGs.
  • domain assumption The Bell et al. (2003) mass-to-light relation provides accurate stellar masses.
    Used to impose the stellar mass threshold.
  • domain assumption The Papastergis et al. (2013) color boundary separates red and non-red ETGs in a physically meaningful way.
    Defines the two samples being compared.
  • domain assumption Projected alignment angles statistically represent 3D alignments without sample-dependent bias.
    The comparison of rETG and nETG distributions is done in projection; any population-dependent projection bias would affect the conclusion.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Alignment of Blue/Green and Red Early-type Galaxies with Large-scale Filaments Reveals Distinct Evolutionary Pathways." pith.science (2026). https://pith.science/paper/3VUCE3ZN

@misc{pith2026241114885,
  author       = {Pith},
  title        = {Pith review of: Alignment of Blue/Green and Red Early-type Galaxies with Large-scale Filaments Reveals Distinct Evolutionary Pathways},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/3VUCE3ZN}},
  note         = {Machine review of arXiv:2411.14885}
}
read the original abstract

We investigate the alignment of non-red early-type galaxies (ETGs) with blue or green colors within large-scale filaments and compare this alignment pattern with that of red ETGs. Our analysis reveals a significant alignment of the major axes of red ETGs with the orientations of their host cosmic filaments, consistent with prior research. In contrast, non-red ETGs show no significant alignment signal. This divergence in alignment behavior between non-red and red ETGs plausibly suggests distinct evolutionary pathways for non-red and red ETGs.

Figures

Figures reproduced from arXiv: 2411.14885 by the authors.

Figure 1
Figure 1. The color-magnitude diagram, showing g − i optical colors versus r-band absolute magnitudes Mr, for SDSS galaxies (black dots) and ETGs (cyan dots). The red boundary line separat￾ing rETGs and nETGs is defined by g − i = −0.0571(Mr + 24) + 1.25 (Papastergis et al. 2013). panels of [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Comparison of the stellar mass distributions (left), dgf distributions (middle), and (CMB-corrected) redshift distributions (right) between the nETGs (blue histograms) and rETGs (red histograms). The upper, middle, and lower panels correspond to the results obtained from the original rETG sample, mass-weighted rETG sample, and mass-weighted sample matched in size to the nETG sample, respectively. Each panel displays… view at source ↗
Figure 3
Figure 3. Comparison of the θ distributions of rETGs (red his￾tograms) and nETGs (blue histograms). The upper, middle, and lower panels display the results from the original rETG sample, mass-weighted sample, and mass-weighted sample with the same size as the nETG sample, respectively. The 1σ uncertainties, de￾rived from bootstrap resampling while maintaining the sample size (the standard deviation of the distribution functio… view at source ↗

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

85 extracted references · 77 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month note number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.co...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.doi doi empty "" "doi:" doi * if FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix ":" * if eprint field.or.null * if FUNCTION format.pid eprint empty format.doi format.eprint if FUNCTION n.dashify 't := "" t...

  3. [3]

    acknowledgments ... acknowledgments

    thebibliography [1] 20pt to REFERENCES 6pt =0pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command Each re...

  4. [4]

    0O> ?ܹsndz 5 's :_ 讻j|

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

  5. [5]

    2011, ApJS, 193, 29

    Aihara, H., Allende Prieto, C., An, D., et al. 2011, ApJS, 193, 29

  6. [6]

    2015, A&A, 578A, 110

    Argudo-Fern\'andez, M., et al. 2015, A&A, 578A, 110

  7. [7]

    P., Nichol, R

    Bamford, S. P., Nichol, R. C., Baldry, I. K., et al. 2009, MNRAS, 393, 1324

  8. [8]

    2022, MNRAS, 516, 3569

    Barsanti, S., et al. 2022, MNRAS, 516, 3569

Show all 85 references
  1. [9]

    F., McIntosh, D

    Bell, E. F., McIntosh, D. H., Katz, N., Weinberg, M. D. 2003, , 149, 289

  2. [10]

    Brinchmann, J., Charlot, S., White, S. D. M., Tremonti, C., Kauffmann, G., Heckman, T., Brinkmann, J. 2004, , 351, 1151

  3. [11]

    Carleton, T., Errani, R., Cooper, M., Kaplinghat, M., Pe\ narrubia, J. Guo, Y. 2019, , 485, 382

  4. [12]

    2019, MNRAS, 485, 2492

    Chen, Y.-C., Ho, S., Blazek, J., He, S., Mandelbaum, R., Melchior, P., Singh, S. 2019, MNRAS, 485, 2492

  5. [13]

    D., Dolgachev, V

    Chernin, A. D., Dolgachev, V. P., Domozhilova, L. M. 2000, MNRAS, 319,851

  6. [14]

    Codis, S., Pichon, C., Devriendt, J., Slyz, A., Pogosyan, D., Dubois, Y., Sousbie, T., 2012, MNRAS, 427, 3320

  7. [15]

    V., O'Mill, A

    Costa-Duarte, M. V., O'Mill, A. L., Duplancic, F., Sodr\'e, L., Lambas, D. G. 2016, MNRAS, 459, 2539

  8. [16]

    Coutts A., 1996, MNRAS, 278, 87

  9. [17]

    1948, Ann

    de Vaucouleurs, G. 1948, Ann. d'Ap., 11, 247

  10. [18]

    2009, , 699, 948

    Deng, X.-F., He, J.-Z., Wu, P., Ding, Y.-P. 2009, , 699, 948

  11. [19]

    Donoso, E., O'Mill, A., & Lambas, D. G. 2006, MNRAS, 369, 479

  12. [20]

    P., Liske, J., Davies, L

    Driver, S. P., Liske, J., Davies, L. J. M., et al. 2019, The Messenger, 175, 46

  13. [21]

    2014, MNRAS, 444, 1453

    Dubois, Y., Pichon, C., Welker, C., et al. 2014, MNRAS, 444, 1453

  14. [22]

    Duplancic, F., D\'avila-Kurb\'an, F., Coldwell, G. V. 2020, MNRAS, 493. 1818

  15. [23]

    G., O'Mill, A

    Duplancic, F., Alonso, S., Lambas, D. G., O'Mill, A. L., 2015, MNRAS, 447, 1399

  16. [24]

    L., Lambas, D

    Duplancic, F., O'Mill, A. L., Lambas, D. G., Sodr\'e, L., Alonso, S., 2013, MNRAS, 433, 354

  17. [25]

    Faltenbacher, A., Li, C., Simon, W. D. M., Jing, Y.-P., Mao, S.-D., Wang, J. 2009, Research in Astron. Astrophys., 9, 41

  18. [26]

    Feng, S., Shao, Z.-Y., Shen, S.-Y., Argudo-Fern\'andez, M., Wu, H., Lam, M.-I., Yang, M., Yuan, F.-T 2015, Research in Astronomy and Astrophysics, 16, 72

  19. [27]

    Ganeshaiah Veena, P., Cautun, M., Tempel, E., van de Weygaert, R., Frenk, C. S. 2019, MNRAS, 487, 1607

  20. [28]

    2017, A&, 598A, 45

    George, K. 2017, A&, 598A, 45

  21. [29]

    M., M\'endez-Hern\'andez, H., Aceves, H., Olgu\'in, L

    Hern\'andez-Toledo, H. M., M\'endez-Hern\'andez, H., Aceves, H., Olgu\'in, L. 2011, AJ, 141, 74

  22. [30]

    M., Seljak U., 2004, Phys

    Hirata C. M., Seljak U., 2004, Phys. Rev. D, 70, 063526

  23. [31]

    J., 2010, ApJ, 720, 1483

    Hung L.-W., Ba \ n ados E., De Propris R., West M. J., 2010, ApJ, 720, 1483

  24. [32]

    G., Saurer, W

    Kitzbichler, M. G., Saurer, W. 2003, ApJ, 590, L9

  25. [33]

    2013, Secular Evolution of Galaxies, by Jes\'us Falc\'on-Barroso, and Johan H

    Kormendy, J. 2013, Secular Evolution of Galaxies, by Jes\'us Falc\'on-Barroso, and Johan H. Knapen, Cambridge, UK: Cambridge University Press, 2013, p.1

  26. [34]

    Kang X., Wang P., 2015, ApJ, 813, 6

  27. [35]

    2021, MNRAS, 504, 4626

    Kraljic, K., et al. 2021, MNRAS, 504, 4626

  28. [36]

    2015, MNRAS, 446, 2744

    Laigle, C., et al. 2015, MNRAS, 446, 2744

  29. [37]

    2015, ApJ, 799, 212

    Lee, J., Choi, Y.-Y. 2015, ApJ, 799, 212

  30. [38]

    P., Faltenbacher, A., Wang, J

    Li, C., Jing, Y. P., Faltenbacher, A., Wang, J. 2013, ApJL, 770, L12

  31. [39]

    2024, , 974, 238

    Li, F., Wang, E., Zhu, M., et al. 2024, , 974, 238

  32. [40]

    I., Hoffman, Y., Steinmetz, M., Gottl\"ober, S., Knebe, A., Hess, S., 2013, ApJ, 766, L15

    Libeskind, N. I., Hoffman, Y., Steinmetz, M., Gottl\"ober, S., Knebe, A., Hess, S., 2013, ApJ, 766, L15

  33. [41]

    J., Tempel, E., Saar, E

    Liivam\"agi, L. J., Tempel, E., Saar, E. 2012, A&A, 539, A80

  34. [42]

    H., & Dekel, A

    Maller, A. H., & Dekel, A. 2002, MNRAS, 335, 487

  35. [43]

    Merluzzi, P. et al. 2015, , 446, 803

  36. [44]

    2019, Comput

    Nelson, D., Springel, V., Pillepich, A., et al. 2019, Comput. Astrophys. Cosmol., 6, 2

  37. [45]

    J., Kuchner, U., Gray, M

    O'Kane, C. J., Kuchner, U., Gray, M. E., Arag\'on-Salamanca, A. 2024, , 534, 1682

  38. [46]

    L., Duplancic, F., Garc\'ia Lambas, D., Valotto, C., Sodr\'e, L

    O'Mill, A. L., Duplancic, F., Garc\'ia Lambas, D., Valotto, C., Sodr\'e, L. 2012, MNRAS, 421, 1897

  39. [47]

    P., Rodr\'iguez-Puebla, A., Jones, M

    Papastergis, E., Giovanelli, R., Haynes, M. P., Rodr\'iguez-Puebla, A., Jones, M. G. 2013, , 776, 43

  40. [48]

    J., Kuhn, J

    Pereira, M. J., Kuhn, J. R. 2005, , 627L, 21

  41. [49]

    Plionis M., Basilakos S., 2002, MNRAS, 329, L47

  42. [50]

    J., Bryan, G

    Pereira, M. J., Bryan, G. L., Gill, S. P. D. 2008, , 672, 825

  43. [51]

    Plionis M., Benoist C., Maurogordato S., Ferrari, C., Basilakos, S., 2003, ApJ, 594, 144

  44. [52]

    Primack, J. R. 2024, Annual Review of Nuclear and Particle Science, 74, 173

  45. [53]

    2024, , 531L, 9

    Rong, Y., Shen, J., Hua, Z. 2024, , 531L, 9

  46. [54]

    2016, MNRAS, 455, 2267

    Rong, Y., Liu, Y., Zhang, S.-N. 2016, MNRAS, 455, 2267

  47. [55]

    E., Tempel, E., Puzia, T

    Rong, Y., Mancera Pi\ na, P. E., Tempel, E., Puzia, T. H., De Rijcke, S. 2020, MNRAS, 498, L72

  48. [56]

    H., et al

    Rong, Y., Puzia, T. H., et al. 2019, ApJ, 883, 56

  49. [57]

    2015a, MNRAS, 451, 2536

    Rong, Y., Yi, S.-X., Zhang, S.-N., Tu, H. 2015a, MNRAS, 451, 2536

  50. [58]

    2015b, MNRAS, 453, 1577

    Rong, Y., Zhang, S.-N., Liao, J.-Y. 2015b, MNRAS, 453, 1577

  51. [59]

    D., et al

    Schneider, M. D., et al. 2013, MNRAS, 433, 2727

  52. [60]

    S., Dubinski, J., Yee, H

    Taranu, D. S., Dubinski, J., Yee, H. K. C. 2013, ApJ, 778, 61

  53. [61]

    A., Ali, G

    Tawfeek, A. A., Ali, G. B., Takey, A., Awad, Z., Hayman, Z. M. 2019, MNRAS, 482, 2627

  54. [62]

    N., 2011, MNRAS, 418, 1587

    Taylor, E. N., 2011, MNRAS, 418, 1587

  55. [63]

    2023, The Messenger, 190, 46

    Taylor, E.N., et al. 2023, The Messenger, 190, 46

  56. [64]

    Tempel, E., Guo, Q., Kipper, R., Libeskind, N. I. 2015, MNRAS, 450, 2727

  57. [65]

    Tempel, E., Libeskind, N. I. 2013, ApJ, 775, L42

  58. [66]

    S., Mart\'inez, V

    Tempel, E., Stoica, R. S., Mart\'inez, V. J., Liivam\"agi, L. J., Castellan, G., Saar, E., 2014, MNRAS, 438, 3465

  59. [67]

    S., Saar, E

    Tempel, E., Stoica, R. S., Saar, E. 2013, MNRAS, 428, 1827

  60. [68]

    2015, A&A, 576, L5

    Tempel, E., Tamm, A. 2015, A&A, 576, L5

  61. [69]

    J., 2012, A&A, 540, A106

    Tempel, E., Tago, E., Liivam\"agi, L. J., 2012, A&A, 540, A106

  62. [70]

    Tempel, E., et al., 2014b, A&A, 566, A1

  63. [71]

    L., Richards, J

    Tojeiro, R., Masters, K. L., Richards, J. 2013, , 432, 359

  64. [72]

    V., Chernin, A

    Trofimov, A. V., Chernin, A. D. 1995, AZh, 72, 308

  65. [73]

    A., Ishak M., 2014, preprint arXiv:1047.6990

    Troxel M. A., Ishak M., 2014, preprint arXiv:1047.6990

  66. [74]

    C., 1998, ApJ, 507, 601

    van den Bosch, F. C., 1998, ApJ, 507, 601

  67. [75]

    2023, A&A, 670, A63

    V\'asquez-Bustos, P., Argudo-Fernandez, M., Grajales-Medina, D., Duarte Puertas, S., Verley, S. 2023, A&A, 670, A63

  68. [76]

    I., Tempel, E., Pawlowski, M

    Wang, P., Libeskind, N. I., Tempel, E., Pawlowski, M. S., Kang, X., Guo, Q. 2020, ApJ, 900, 129

  69. [77]

    2017, 468, L123

    Wang P., Kang X. 2017, 468, L123

  70. [78]

    I., 2018, ApJ, 866, 138

    Wang P., Guo Q., Kang X., Libeskind N. I., 2018, ApJ, 866, 138

  71. [79]

    Wang P., Kang X., 2018, MNRAS, 473, 1562

  72. [80]

    2024, , 532, 4604

    Wang, W., Wang, P., Guo, H., et al. 2024, , 532, 4604

  73. [81]

    S., 1984, A&A, 138, 253

    Wesson P. S., 1984, A&A, 138, 253

  74. [82]

    J., 1994, MNRAS, 268, 79

    West M. J., 1994, MNRAS, 268, 79

  75. [83]

    2016, ApJS, 225, 11

    Yagi, M., Koda, J., Komiyama, Y., Yamanoi, H. 2016, ApJS, 225, 11

  76. [84]

    2015, ApJ, 798, 17

    Zhang, Y., Yang, X., Wang, H., et al. 2015, ApJ, 798, 17

  77. [85]

    J., van den Bosch, F

    Zhang, Y., Yang, X., Wang, H., Wang, L., Mo, H. J., van den Bosch, F. C. 2013, ApJ, 779, 160

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.