Pith. sign in

REVIEW 3 major objections 6 minor 67 references

Moderate Influence of Halo Spin on Stellar Mass Distributions in Dwarf and Massive Galaxies

T0 review · 3 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

Pith's one-line read Halo spin is inversely tied to stellar surface density in both dwarf and massive galaxies, pointing to a universal spin-driven galaxy formation scenario.

desk verdict The spin estimator's built-in dependence on HI mass likely manufactures the claimed anti-correlation, so treat the result as an instructive cautionary tale rather than evidence for spin shaping stellar mass distributions. read the letter →

arxiv 2411.12210 v2 pith:FUFGM2UH submitted 2024-11-19 astro-ph.GA

classification astro-ph.GA
keywords halospinstellarsurfacedensitygalaxyevolutionALFALFAsurveyHIgalaxiesangularmomentumdwarfformation
open problems Dark Matter
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 halo spin leaves a measurable imprint on where stars end up inside a galaxy, from dwarfs to massive disks. Using 6,680 HI-rich galaxies from the ALFALFA survey and a semi-analytic estimator that converts HI rotation widths and scale lengths into halo spin, the paper finds that stellar surface density decreases as halo spin increases, with correlation coefficients of -0.21 (low mass) and -0.31 (massive), and -0.18/-0.30 for isolated galaxies. The paper interprets this as a universal formation scenario: high-spin halos pull in high-angular-momentum gas, slow its condensation at the center, suppress star formation and feedback, and let stars drift outward in a shallower potential, producing diffuse stellar structures. If correct, halo spin becomes a basic parameter for predicting galaxy structure, not a detail confined to massive disk galaxies.

What carries the argument

The load-bearing object is the semi-analytic spin estimator of Eq. (1), $\lambda_h \simeq 21.8\,(R_{\mathrm{HI,d}}/\mathrm{kpc})\,/\,(V_{\mathrm{rot}}/(\mathrm{km\,s^{-1}}))^{3/2}$, which returns a halo spin parameter from the HI disk scale length $R_{\mathrm{HI,d}}$ and rotation velocity $V_{\mathrm{rot}}$. The scale length is derived by assuming an exponential, centrifugal-balance HI disk with the same specific angular momentum as the halo (Mo et al. 1998) and anchoring the disk edge with the empirical HI mass-radius relation (Wang et al. 2016). Rotation velocities come from ALFALFA $W_{50}$ line widths corrected for inclination, with single-horned, dispersion-dominated profiles excluded. This estimator carries the argument by converting a large, HI-selected sample into halo spins that can be compared directly with stellar surface density.

What would settle it

Run the same spin estimator on simulated galaxy observations in which true halo spin is uncorrelated with stellar surface density; if the estimator still returns an anti-correlation, the method creates the signal. Alternatively, measure spins from resolved HI kinematics for a sample spanning the same stellar surface density range and check whether the anti-correlation survives.

Watch

Extended reading notes

Core claim

The central claim is that halo spin is inversely related to stellar surface density across the full mass range of the sample. For low-mass galaxies ($M_{\star} < 10^9\,M_\odot$) the correlation coefficient is $-0.21$, and for massive galaxies ($M_{\star} > 10^9\,M_\odot$) it is $-0.31$; restricting to isolated galaxies gives $-0.18$ and $-0.30$. The linear fits to binned medians are $\log\lambda_h = (-0.09 \pm 0.09)\log S_{\star} - (0.16 \pm 0.59)$ for low-mass and $\log\lambda_h = (-0.11 \pm 0.09)\log S_{\star} + (0.04 \pm 0.73)$ for massive galaxies. The paper interprets these trends as a universal formation scenario: high-spin halos accrete high-spin gas that retains its angular momentum, preventing efficient condensation and star formation in the center; weak feedback then redistributes gas outward, and the shallower central potential drives outward stellar migration, yielding more extended galaxies with lower stellar surface density.

Load-bearing premise

The spin estimate assumes the HI gas disk and the dark matter halo have the same specific angular momentum and that a universal baryonic Tully-Fisher relation with slope 3.5 holds, so a systematic difference in gas angular momentum between dense and diffuse galaxies would masquerade as the reported anti-correlation.

Editorial extensions

If this is right

  • High-spin halos should systematically host galaxies with lower central stellar surface densities and more extended stellar distributions across the whole mass range studied.
  • Environment is not the driver: the anti-correlation persists in isolated galaxies at nearly the same strength.
  • Stellar structure is shaped by halo spin together with other processes, since the correlation is weaker than the halo-spin versus HI-to-stellar-mass-ratio relation.
  • HI-selected samples can probe halo-spin physics without the stellar-selection biases that affect higher-surface-brightness samples.

Reading between the lines

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

  • A direct test: galaxies in high-spin halos should also show higher specific angular momentum in their stellar component, measurable with integral-field spectroscopy.
  • Applying the same estimator to CO- or H-alpha-selected galaxies would show whether the anti-correlation is a general property of gas-rich star-forming galaxies or specific to HI-selected systems.
  • If high spin suppresses central star formation, low-surface-density galaxies at fixed stellar mass should show weaker metal enrichment and older stellar populations, a checkable prediction.
  • Resolved HI kinematics from interferometers can replace the assumed exponential-disk geometry and test whether the estimator's assumptions, rather than astrophysics, create the anti-correlation.
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 / 6 minor

Summary. The paper estimates halo spin parameters for ~6,680 HI-rich galaxies from the ALFALFA survey using a semi-analytic formula (Eq. 1) that combines a disk scale length derived from an empirical r_HI--M_HI calibration with rotation velocities inferred from W50 and inclination. It then fits log lambda_h versus log S_star separately for low- and high-mass samples, including isolated subsamples, and reports inverse correlations with slopes of -0.09 +/- 0.09 and -0.11 +/- 0.09 and correlation coefficients of -0.21 and -0.31. The authors interpret these correlations as evidence that high-spin halos suppress central star formation and produce extended stellar distributions.

Significance. If the result holds, it would provide a large observational sample supporting a universal role of halo spin in setting galaxy structure, extending earlier work on massive galaxies to dwarfs. The paper's strengths are its use of a large homogeneous HI-selected sample, the separation into low-mass and massive subsamples, the environmental control through an isolated-galaxy sample, and the transparent listing of the semi-analytic method's assumptions in Section 4. However, the quantitative support is weak: the fitted slopes are consistent with zero at about the 1-sigma level, and the spin estimator is closely tied to M_HI and Vrot, raising a degeneracy with gas-fraction scaling that the current analysis does not rule out.

major comments (3)
  1. [§2.3 and §4, Eqs. (1)–(4)] Solving Eqs. (3) and (4) with the adopted empirical relation log r_HI = 0.51 log M_HI - 3.59 makes R_HI,d a monotonically increasing function of M_HI (approximately R_HI,d ~ M_HI^0.5), so Eq. (1) assigns higher lambda_h to more HI-rich galaxies at fixed Vrot; through the baryonic Tully-Fisher slope of 3.5, the same holds at fixed stellar mass. Because low-S_star galaxies at fixed M_star are systematically HI-rich and have larger R_e, the reported anti-correlation may restate the known gas-fraction--stellar-density scaling rather than measure an independent halo-spin effect. The final paragraph of Section 4 argues only that a constant multiplicative overestimate of lambda_h cannot create the correlation; it does not exclude a bias that grows systematically with M_HI. Please add partial correlations controlling for M_HI or gas fraction, or otherwise demonstrate that the result is not driven by this calibration.
  2. [§3] The headline fits, log lambda_h = (-0.09 +/- 0.09) log S_star + c and log lambda_h = (-0.11 +/- 0.09) log S_star + c, have slopes within 1.0--1.2 sigma of zero, and the correlation coefficients are only -0.21 and -0.31. With 6,680 galaxies these coefficients could still be statistically significant, but no p-values or confidence intervals are reported, so the reader cannot assess whether the claimed inverse correlation is more than marginal. Please report significance levels and, ideally, partial correlations that control for M_HI, M_star, and R_e.
  3. [§4] The physical interpretation (high-spin halos retain angular momentum, suppress central star formation, and promote outward migration) assumes that the estimator in Eq. (1) faithfully traces the true halo spin parameter. Given the explicit dependence of lambda_h on M_HI and Vrot, and the unverified assumption of equal specific angular momenta of cool gas and halo, the current analysis cannot distinguish this causal scenario from a selection or gas-fraction effect. A consistency check with simulations—for example, comparing estimated spins against true halo spins at fixed observational inputs—or with resolved HI kinematics would be needed to support the interpretive claim.
minor comments (6)
  1. [§2.1] The statement that ALFALFA selection is unbiased because it is based on HI column densities rather than stellar characteristics is overstated; ALFALFA is HI-flux limited and will miss HI-poor or low-column-density galaxies, which could affect the S_star--lambda_h relation.
  2. [§2.2] The three stellar-mass estimation methods are said to have negligible discrepancies, but no scatter or validation statistic is quoted; please quantify the agreement.
  3. [§2.3] The assumed intrinsic thickness q0 differs by mass (0.2 vs. 0.4) with no uncertainty propagation; since q0 affects Vrot and hence lambda_h, a sensitivity test would strengthen the results.
  4. [Fig. 1] The caption should explicitly state that panels (a) and (c) are low-mass and panels (b) and (d) are high-mass, and it should define the blue/red error bars beyond saying they are '1 sigma uncertainties'.
  5. [§4] The text alternates between calling the correlation 'weak' and 'moderate' for Pearson coefficients of -0.21 and -0.31; please use consistent terminology aligned with the reported values.
  6. [References] The reference list contains formatting artifacts such as 'V oort' and 'Kere ˇs'; please proofread the bibliography.
Assumptions & free parameters 3 free parameters · 6 assumptions · 0 invented entities

The central correlation rests entirely on the semi-analytic spin estimator; the paper adds no new physics but applies a published estimator to a large sample. The main load is carried by assumptions about gas-halo angular momentum coupling and the empirical r_HI-M_HI calibration, both taken from external literature or the authors' own prior papers.

free parameters (3)
  • intrinsic disk thickness q0 = 0.2 (massive), 0.4 (low-mass M_star < 10^9.5)
    Used to convert optical axis ratio b/a into HI disk inclination and thus V_rot; choice is taken from the literature and applied by hand, affecting all spin values.
  • HI radius relation coefficients = log r_HI = 0.51 log M_HI - 3.59 (Wang et al. 2016)
    The empirical r_HI-M_HI relation sets the HI disk scale length R_HI,d via Eq. (3)-(4); its slope and zero-point are fitted constants from another survey and are not re-calibrated here, so systematic errors propagate into every lambda_h.
  • spin estimator constant = 21.8 in Eq. (1) (Hernandez et al. 2007)
    Calibration constant for the semi-analytic lambda_h estimator; not fitted here, but it absorbs assumptions about halo structure and the baryonic Tully-Fisher relation.
assumptions (6)
  • domain assumption Spherically symmetric dark matter halo in the spin estimator
    Eq. (1) is derived assuming spherical symmetry; galaxies are triaxial, so lambda_h is approximate. Acknowledged in Section 4.
  • ad hoc to paper Same specific angular momentum of cool gas and halo
    The estimator maps the gas disk scale length to halo spin; this is the key assumption that could make the spin proxy correlate with gas extent by construction. Stated in Section 4.
  • domain assumption Universal baryonic Tully-Fisher relation with slope 3.5
    The calibration of Eq. (1) assumes all galaxies follow the same V_rot-mass relation; variations with mass or environment would bias lambda_h. Stated in Section 4.
  • domain assumption Exponential thin gas disk in centrifugal balance
    Eq. (2) and (4) assume a thin exponential HI disk; real HI disks have warps, clumps, and pressure support. Section 2.3.
  • domain assumption Kurtosis k4 > -1.0 identifies dispersion-dominated single-horned profiles
    The sample excludes single-horned galaxies based on this threshold from Hua et al. (2024); if misclassified, the low-mass sample is biased. Section 2.3.
  • domain assumption Isolation criterion (distance > 3 virial radii) removes environmental effects
    Section 3 uses this threshold to define isolated galaxies; residual effects of tidal or ram-pressure stripping may remain.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Moderate Influence of Halo Spin on Stellar Mass Distributions in Dwarf and Massive Galaxies." pith.science (2026). https://pith.science/paper/FUFGM2UH

@misc{pith2026241112210,
  author       = {Pith},
  title        = {Pith review of: Moderate Influence of Halo Spin on Stellar Mass Distributions in Dwarf and Massive Galaxies},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FUFGM2UH}},
  note         = {Machine review of arXiv:2411.12210}
}
read the original abstract

We estimate halo spins for HI-rich galaxies in the Arecibo Legacy Fast Alfa Survey using a semi-analytic approach, examining the relationship between halo spin and stellar surface density. Our findings reveal an inverse correlation in both low- and high-mass galaxy samples, with stellar surface density decreasing as halo spin increases. This trend highlights the pivotal role of halo spin in galaxy evolution and suggests a universal formation scenario: high-spin halos, accompanied by high-spin accreted gas, retain angular momentum, preventing gas from efficiently condensing in the galactic center and thus suppressing star formation. Consequently, weak feedback redistributes gas to the halo outskirts without significant expulsion. The shallower central gravitational potential in high-spin halos promotes outward stellar migration, leading to more extended stellar distributions and lower stellar surface densities.

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

67 extracted references · 47 canonical work pages

  1. [1]

    Alam, M. P. et al. 2015, ApJS, 219, 12 2, 3

  2. [2]

    Amorisco, N. C. & Loeb, A. 2016, MNRAS, 459, L51 1

  3. [3]

    S., Conroy, C., Wechsler, R

    Behroozi, P. S., Conroy, C., Wechsler, R. H. 2010,ApJ, 717, 379-403 (2010) 1

  4. [4]

    A., Sales, L

    Benavides, J. A., Sales, L. V ., Abadi, M. G., Marinacci, F., V ogelsberger, M., Hernquist, L. 2023, MNRAS, 522, 1033 1

  5. [5]

    & Arnouts, S

    Bertin, E. & Arnouts, S. 1996, A&AS 117, 393-404 2

  6. [6]

    2007, MNRAS, 376, 215 3

    Navarro, J. 2007, MNRAS, 376, 215 3

  7. [7]

    2006, MNRAS, 366, 1126 1

    Cappellari, Michele; Bacon, R.; Bureau, M., et al. 2006, MNRAS, 366, 1126 1

  8. [8]

    M., Alatalo, K., et al.2013, MNRAS, 432, 1862 1

    Cappellari, M., McDermid, R. M., Alatalo, K., et al.2013, MNRAS, 432, 1862 1

Show all 67 references
  1. [9]

    H., Crain R

    Desmond, H., Mao Y .-Y ., Wechsler R. H., Crain R. A., Schaye J. 2017, MNRAS, 471, L11 1 Stellar surface density depends on halo spin 5 Di Cintio, A., Brook, C. B., Dutton, A. A., Macci `o, A. V .,

  2. [10]

    2017, MNRAS, 466L, 1 3 Di Cintio, A., Brook, C

    Obreja, A., Dekel, A. 2017, MNRAS, 466L, 1 3 Di Cintio, A., Brook, C. B., Macci `o, A. V ., Dutton, A. V .,

  3. [11]

    2019, MNRAS, 486, 2535 1

    Cardona-Barrero, S. 2019, MNRAS, 486, 2535 1

  4. [12]

    2005, MNRAS, 364, 367 1

    Diemand, J., Madau, P., Moore, B. 2005, MNRAS, 364, 367 1

  5. [13]

    2019, MNRAS, 483, 1754 2

    Du, W., Cheng, C., Wu, H., Zhu, M., Wang, Y . 2019, MNRAS, 483, 1754 2

  6. [14]

    I., Zhu, Y ., Lei, F., Zhou, Z

    Du, W., Wu, H., Lam, M. I., Zhu, Y ., Lei, F., Zhou, Z. 2015, AJ, 149, 199 2

  7. [15]

    A., Crone Odekon, M., Haynes, M

    Durbala, A., Finn, R. A., Crone Odekon, M., Haynes, M. P., Koopmann, R. A., O’Donoghue, A. A. 2020, AJ, 160, 271 2

  8. [16]

    ElBadry, K. et al. 2018, MNRAS, 473, 1930 2

  9. [17]

    A., Katz, N., Gardner, J

    Fardal, M. A., Katz, N., Gardner, J. P., et al. 2001, ApJ, 562, 605 1

  10. [18]

    Gault, L. et al. 2021, AJ, 909, 19 2

  11. [19]

    Gill, S. P. D., Knebe, A., Gibson, B. K. 2005, MNRAS, 356, 1327-1332 3

  12. [20]

    Giovanelli, R. et al. 2005, AJ, 130, 6 2

  13. [21]

    Giovanelli, R. et al. 1997, AJ, 113, 22 2

  14. [22]

    2020, A&A, 634, A135-A157 1

    Marulli, F., Baldi, M. 2020, A&A, 634, A135-A157 1

  15. [23]

    2011, MNRAS, 413, 101 1

    Guo, Q., et al. 2011, MNRAS, 413, 101 1

  16. [24]

    2022, MNRAS, 514, 5056 1

    Hafen, Z., Stern, J., Bullock, J., et al. 2022, MNRAS, 514, 5056 1

  17. [25]

    Haynes, M. P. et al. 2018, ApJ, 861, 49 2

  18. [26]

    2007, MNRAS, 375, 163 2

    Hernandez, X., Park, C., Cervantes-Sodi, B., & Choi, Y .-Y . 2007, MNRAS, 375, 163 2

  19. [27]

    F., Quataert, E., Murray, N

    Hopkins, P. F., Quataert, E., Murray, N. 2012, MNRAS, 421, 3488 1

  20. [28]

    2024, eprint arXiv:2403.16754 2

    Hua, Z., Rong, Y ., Hu, H.-J. 2024, eprint arXiv:2403.16754 2

  21. [29]

    Huchra, J. P. et al. 2012, ApJS, 199, 26 3

  22. [30]

    A., et al

    Hunter, D. A., et al. 2012, AJ, 144, 134

  23. [31]

    S., Daddi, E., Bournaud, F., et al

    Kalita, B. S., Daddi, E., Bournaud, F., et al. 2022, A&A, 666A, 44 1

  24. [32]

    2011, ApJ, 726, 98 3 Kereˇs, D., Katz, N., Weinberg, D

    Moustakas, L. 2011, ApJ, 726, 98 3 Kereˇs, D., Katz, N., Weinberg, D. H., Dav ´e, R. 2005, MNRAS, 363, 2 1

  25. [33]

    & Lee, J

    Kim, J.-h. & Lee, J. 2013, MNRAS, 432, 1701 1

  26. [34]

    M., Fox, A

    Lehner, N., O’Meara, J. M., Fox, A. J., et al. 2014, ApJ, 788, 119 1

  27. [35]

    2022, MNRAS, 516, 4220 2

    Gu, Q., Li, S. 2022, MNRAS, 516, 4220 2

  28. [36]

    2024, arXiv:2411.11446 3

    Liu, S., Rong, Y ., Hua, Z., Hu, H. 2024, arXiv:2411.11446 3

  29. [37]

    A., Sanchis, T., Salvador-Sol ´e, E., Solanes, J

    Mamon, G. A., Sanchis, T., Salvador-Sol ´e, E., Solanes, J. M. 2004, A&A, 414, 445 3

  30. [38]

    2005, MNRAS, 364, 607 3

    Piffaretti, R., Stadel, J. 2005, MNRAS, 364, 607 3

  31. [39]

    2001, ApJ, 547, L123 3

    Wadsley, J., Stadel, J., Lake, G. 2001, ApJ, 547, L123 3

  32. [40]

    2007, Nature, 445, 738

    Mayer, L., Kazantzidis, S., Mastropietro, C., Wadsley, J. 2007, Nature, 445, 738

  33. [41]

    J., Mao, S

    Mo, H. J., Mao, S. D. & White, S. D. M. 1998, MNRAS, 295, 319 1, 2

  34. [42]

    1996, Nature, 379, 613 3

    Moore, B., Katz, N., Lake, G., et al. 1996, Nature, 379, 613 3

  35. [43]

    2013, MNRAS, 429, 3353 1

    Nelson, D., V ogelsberger, M., Genel, S., et al. 2013, MNRAS, 429, 3353 1

  36. [44]

    2018, Nature, 559, 585 1

    Noguchi, M. 2018, Nature, 559, 585 1

  37. [45]

    2022, MNRAS, 510, 1772 1

    Noguchi, M. 2022, MNRAS, 510, 1772 1

  38. [46]

    2023, MNRAS, 522, 4691 1

    Noguchi, M. 2023, MNRAS, 522, 4691 1

  39. [47]

    A., Hudson, M

    Oman, K. A., Hudson, M. J., Behroozi, P. S. 2013, MNRAS, 431, 2307-2316 3

  40. [48]

    2020, MNRAS, 491L, 51 3

    Peng, Y .-J., Renzini, A. 2020, MNRAS, 491L, 51 3

  41. [49]

    2017, MNRAS, 470, 4231 1

    Sun, S., Pan, J. 2017, MNRAS, 470, 4231 1

  42. [50]

    2018, MNRAS, 477, 230 1

    Rong, Y ., et al. 2018, MNRAS, 477, 230 1

  43. [51]

    2024a, arXiv:2404.00555 3

    Zhang, H.-X., Mo, H. 2024a, arXiv:2404.00555 3

  44. [52]

    2024b, arXiv:2409.00944 2

    Rong, Y ., He, M., Hu, H., Zhang, H.-X., Wang, H.-Y . 2024b, arXiv:2409.00944 2

  45. [53]

    Weiner, B. J. 2010, ApJ, 712, 574 1

  46. [54]

    H., Hennawi, J

    Rubin, K. H., Hennawi, J. F., Prochaska, J. X., et al. 2015, ApJ, 808, 38 1

  47. [55]

    V ., Wetzel, A., Fattahi, A

    Sales, L. V ., Wetzel, A., Fattahi, A. 2022, Nature Astronomy, 6, 897 1

  48. [56]

    V ., Mikske, S., Zeilinger, W

    Saulder, C., van Kampen, E., Chilingarian, I. V ., Mikske, S., Zeilinger, W. W. 2016, A&A, 596, A14 3

  49. [57]

    2015, MNRAS, 448, 2941 1

    Sawala, T., et al. 2015, MNRAS, 448, 2941 1

  50. [58]

    On the fragmentation of cosmic gas clouds

    Silk, J. On the fragmentation of cosmic gas clouds. I. 1977, ApJ, 211, 638-648 1

  51. [59]

    McConnachie, A. W. 2011, ApJS, 196, 11 2

  52. [60]

    A., et al

    Smith, R., S´anchez-Janssen, R., Beasley, M. A., et al. 2015, MNRAS, 454, 2502 3

  53. [61]

    I., Jacobs, B

    Makarov, D. I., Jacobs, B. A. 2009, AJ, 138, 323 2 van de V oort, F., Schaye, J., Altay, G., Theuns, T. 2012, MNRAS, 421, 2809 1 van den Bosch, F. C. 1998, ApJ, 507, 601 1

  54. [62]

    S., Serra, P., van der Hulst, T., Roychowdhury, S., Kamphuis, P., Chengalur, J

    Wang, J., Koribalski, B. S., Serra, P., van der Hulst, T., Roychowdhury, S., Kamphuis, P., Chengalur, J. N. 2016, MNRAS, 460, 2143 2

  55. [63]

    2020, MNRAS, 495, 1958 1

    Wang, B., Cappellari, M., Peng, Y ., Graham, M. 2020, MNRAS, 495, 1958 1

  56. [64]

    2023, MNRAS, 518, 5253 1 6 Rong et al

    Liao, S., Shao, S. 2023, MNRAS, 518, 5253 1 6 Rong et al

  57. [65]

    S., Gao, L., Guo, Q., Shao, S., Wang, L., Wright, R

    Yang, H., Liao, S., Fattahi, A., Frenk, C. S., Gao, L., Guo, Q., Shao, S., Wang, L., Wright, R. J., Zeng, G. 2024, MNRAS, 535, 1394 3

  58. [66]

    J., van den Bosch, F

    Yang, X., Mo, H. J., van den Bosch, F. C., Zhang, Y ., Han, J. 2012, ApJ, 752, 41-73 1

  59. [67]

    V ., Nagai, D

    Zinger, E., Dekel, A., Kravtsov, A. V ., Nagai, D. 2018, MNRAS, 475, 3654–3681 3

Pith tools

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