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REVIEW 3 major objections 4 minor 41 references

Radial velocities and stellar populations for a sample of MATLAS survey dwarfs

T0 review · 3 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

Pith's one-line read Using Keck/KCWI spectra of 12 MATLAS dwarf galaxies, this paper shows that MATLAS-1494 is not an ultra-diffuse galaxy in the NGC 4690 group but a smaller, isolated dwarf at about 18 Mpc that appears old and passive.

desk verdict Useful new spectroscopy for a dozen MATLAS dwarfs, but the headline claim about MATLAS-1494 being an old, passive, isolated dwarf rests on an SED refit and an unsearched environment, not on the measured velocity. read the letter →

arxiv 2507.01362 v1 pith:FOE336GI submitted 2025-07-02 astro-ph.GA

classification astro-ph.GA
keywords dwarfgalaxiesultra-diffuseradialvelocitiesstellarpopulationsKCWIspectroscopyMATLASsurveygalaxyquenchingmass-metallicityrelation
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

On the strength of Keck/KCWI spectra of 12 dwarf galaxies from the MATLAS survey, the paper argues that a single redshift can overturn a galaxy's classification: MATLAS-1494, previously a candidate ultra-diffuse galaxy assumed to belong to the NGC 4690 group, has a velocity of 1315 km/s, placing it at about 18 Mpc in the field and shrinking its effective radius to 1.16 kpc, below the UDG threshold. The authors then re-fit its spectral energy distribution at the new distance and find it old and passive, which they read as a challenge to models that require tidal interactions to quench dwarf galaxies. The paper also measures stellar populations for seven galaxies, reporting a mixture of quenched and star-forming dwarfs, with ages and metallicities that are generally younger and more metal-rich than earlier MUSE-based or SED-based studies. If right, some 'ultra-diffuse galaxies' in low-density environments are really ordinary dwarfs whose status depends on an assumed distance, and dwarf quenching does not need a host galaxy.

What carries the argument

The load-bearing tool is the combination of Keck/KCWI spectroscopy and the spectral-fitting code pPXF, used with the MILES stellar library and BaSTI isochrones over 3700--5510 Angstroms with 10,000 bootstrap iterations, which yields recession velocities and, for seven galaxies, age and metallicity estimates. Host associations are judged by a $\pm$500 km/s velocity threshold motivated by group velocity dispersions. For MATLAS-1494, the decisive step is an SED re-fit following the method of Buzzo et al. (2024) at the new 18 Mpc distance, which shrinks the physical size below the UDG threshold and supplies the old, passive stellar-population estimate.

What would settle it

Measure the distance to MATLAS-1494 directly, for instance by resolving the tip of the red giant branch with HST or JWST; if the galaxy is actually near the original 40 Mpc group distance, its effective radius grows back above 1.5 kpc and the UDG label stands. Deeper spectroscopy or 21-cm mapping could also test the quenching claim by looking for residual star formation, ionised gas, or tidal debris that would contradict an old, passive, isolated dwarf.

Watch

Extended reading notes

Core claim

The central discovery is that spectroscopic redshifts change what the MATLAS dwarfs are. Nine of twelve velocities confirm the literature host associations, but three do not: MATLAS-631 is reassigned to PGC1422425 at about 145 Mpc, MATLAS-1938 to the NGC 5846 group at about 25 Mpc, and MATLAS-1494 to no host at all. For MATLAS-1494, the measured velocity of 1315 $\pm$ 22 km/s implies a distance of about 18 Mpc, which turns the angular size of 13.09 arcsec into a physical effective radius of 1.16 kpc, so the galaxy no longer satisfies the $R_e \ge 1.5$ kpc UDG criterion. Although the KCWI spectrum of MATLAS-1494 is not good enough for reliable stellar-population parameters, a new SED fit at this closer distance gives $\log M_* = 7.33$ $M_\odot$, an age of 8.11 Gyr, and [M/H] of $-0.99$ dex, leading the authors to describe it as an old, passive, relatively isolated dwarf and to argue that its quenching cannot be attributed to tidal interactions.

Load-bearing premise

The load-bearing premise is that the new distance for MATLAS-1494 is right and that an SED fit at that distance, rather than the low-quality spectrum, can be trusted to show it is old and passive.

Editorial extensions

If this is right

  • MATLAS-1494 should be treated as a normal, isolated dwarf with $R_e = 1.16$ kpc, not as an ultra-diffuse galaxy or a member of the NGC 4690 group.
  • If it is truly old and passive, tidal interactions with a host are not necessary to quench dwarfs near a stellar mass of $10^{7.3}$ $M_\odot$, so other quenching channels must exist.
  • The proposed host associations of MATLAS-631 and MATLAS-1938 shift, placing MATLAS-1938 in the NGC 5846 group at about 25 Mpc where it still meets the UDG size definition.
  • Higher metallicities measured from blue-region absorption lines, if they hold for larger samples, would reduce the apparent offset of MATLAS dwarfs from the dwarf-galaxy mass-metallicity relation.
  • The roughly 80% rate of confirmed host associations for MATLAS dwarfs supports statistical association methods but shows that individual redshift checks are needed before classifying individual galaxies.

Reading between the lines

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

  • If redshift-based reclassification is common, the true abundance of ultra-diffuse galaxies in low-density environments may be lower than photometric samples suggest, because angular-size-based UDG status depends on distance.
  • The young, low-metallicity light-weighted ages derived for star-forming dwarfs such as MATLAS-585 suggest that SED-based ages for actively star-forming dwarfs can be biased, which detailed star-formation histories could test.
  • A systematic spectroscopic campaign using blue coverage that includes the Balmer lines and Ca H+K could test whether the lower metallicities from redder MUSE spectra reflect a real population difference or a measurement bias.
  • The existence of an isolated old passive dwarf at this mass would argue that internal feedback or early reionisation, rather than environmental tides alone, can quench low-mass galaxies.
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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 / 4 minor

Summary. The paper presents Keck/KCWI spectroscopy for 12 MATLAS low-surface-brightness dwarfs, measuring recession velocities for all 12 and stellar population parameters for 7. Nine galaxies are found to be consistent with their literature-assumed host associations, while revised associations are proposed for MATLAS-631, 1494, and 1938. The headline result is MATLAS-1494: its measured velocity of 1315 ± 22 km/s implies a distance of ~18 Mpc instead of the assumed 40.2 Mpc, shrinking its effective radius to 1.16 kpc and reclassifying it from a UDG candidate to a smaller dwarf; an SED refit at the new distance suggests an old, passive stellar population. The paper also compares its age and metallicity measurements with previous studies, finding generally younger ages and higher metallicities, and suggests this may help reconcile the MATLAS dwarfs with the universal stellar mass–metallicity relation.

Significance. If the velocity measurements are correct, this is a useful contribution to the sparse census of spectroscopic redshifts and stellar populations in low-density-environment dwarfs. The internal consistency checks (agreement with Heesters et al. 2023 for the three overlapping galaxies, and with the SDSS velocity for MATLAS-1938) strengthen confidence in the measurements. The bootstrap-based uncertainties and the explicit discussion of light- versus mass-weighted values are commendable. The most scientifically loaded claim, however—that MATLAS-1494 is an isolated, old, passive dwarf that challenges tidal quenching models—rests on inferences that are not fully established by the data, as detailed in the major comments. The paper's core velocity measurements are likely to be of lasting value even if the interpretive claims are tempered.

major comments (3)
  1. [Section 3.1.7 and Conclusions] The claim that MATLAS-1494 'places it in the field' and is 'relatively isolated' is supported only by its velocity being inconsistent with the assumed host NGC 4690. At v = 1315 ± 22 km/s and H0 = 72, the Hubble distance is ~18 Mpc, but with plausible peculiar velocities of ±300 km/s the galaxy could lie at 14–23 Mpc. No check for other potential host galaxies, group members, or large-scale structure in this volume is presented. Because the 'challenge to tidal quenching' relies on this environmental classification, the field claim is load-bearing and needs either a genuine environment search (e.g., a NED or catalog search for galaxies within a projected radius and velocity window) or a clearly stated caveat that the environment is unknown beyond the single rejected host.
  2. [Section 3.1.7] The 'old and passive' classification of MATLAS-1494 is not based on the KCWI spectrum—the authors state explicitly that they are 'unable to derive reliable stellar population parameters from our KCWI spectrum'—but on an SED refit following Buzzo et al. (2024) with the new distance. The quoted age of 8.11+3.12−2.34 Gyr is thus distance-dependent and model-dependent. Moreover, the conclusion that this 'challenge[s] theories that invoke tidal interactions' implicitly assumes that the current lack of an obvious host implies that the galaxy has never experienced significant tidal processing. This is a nontrivial assumption. Please rephrase the abstract and conclusions to say the galaxy is 'consistent with being old and passive' and that its environment is currently uncertain, or provide additional evidence (e.g., deep imaging for tidal features, a wider environment search).
  3. [Section 3.2 and Abstract] The suggestion that the measured ages and metallicities 'may help reconcile the observed offset of MATLAS survey dwarf galaxies from the universal stellar mass–metallicity relationship' is based on only seven galaxies, with large error bars, a mix of light-weighted and mass-weighted values, and a systematic offset from the literature that the authors themselves describe as 'sometimes with large uncertainties.' As stated, this is more speculative than the data support. A quantitative assessment (e.g., how much the offset would shift under the new values) would be needed to make this claim persuasive; absent that, it should be clearly flagged as a preliminary possibility rather than a reconciliation.
minor comments (4)
  1. [Title (arXiv metadata)] The title contains a typo: 'MA TLAS' should read 'MATLAS'.
  2. [Section 3.1.7] The sentence 'This would suggest that it is not quenched by any tidal interaction process' is stronger than the evidence; consider replacing with 'consistent with no recent tidal quenching' and adding the qualification that past interactions cannot be excluded.
  3. [Section 3.1.9] The sentence 'The closer distance used by Marleau et al. (2024) will result in a brighter assumed apparent magnitude of the universal GC luminosity function peak, than it would be at further distances' is grammatically awkward and would be clearer as 'A closer assumed distance makes the adopted GC luminosity function peak brighter in apparent terms than it would be at a larger distance.'
  4. [Section 3.1.10] The discussion of MATLAS-2019, which is not part of the observed sample, feels like a digression in the Results section. It could be moved to a footnote or to Section 3.2 where the comparison with literature stellar populations is discussed.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: velocities are direct spectral fits, and the MATLAS-1494 reclassification follows from the measured redshift and standard size definition.

full rationale

The paper's primary measurements are recession velocities obtained by fitting KCWI spectra with pPXF; these are direct spectral fits, not outputs of a model that assumes the result. Host associations are checked against a stated +/-500 km/s threshold from Osmond and Ponman (2004); the three reassignments are consequences of the measured velocity differences. For MATLAS-1494, the new distance (about 18 Mpc from v=1315 plus/minus 22 km/s with H0=72) is used with the UDG definition Re >= 1.5 kpc to reclassify it as a dwarf of Re=1.16 kpc; this is an application of the definition, not a circular derivation. The 'old and passive' characterization comes from a photometric SED re-fit at the new distance following Buzzo et al. (2024), with the paper explicitly stating that reliable stellar population parameters could not be derived from the KCWI spectrum; this is a data-quality and model-dependence caveat, not an equation that reduces to its input. Comparisons with Heesters et al. (2023) and Buzzo et al. (2024, 2025) are external checks; although Buzzo et al. shares authors with the current paper, its SED products are used as input photometry and methodology, not as authority for the central claim. No fitted parameter is renamed as a prediction, and no uniqueness theorem or ansatz is imported from the authors' prior work. The 'challenge to tidal quenching' is an astrophysical interpretation with acknowledged environmental uncertainties, but that is a scientific inference risk, not circularity.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

The paper's central conclusions rest less on derived equations than on observational assumptions: template library fidelity, the association velocity threshold, the validity of a re-fitted SED at a new distance for MATLAS-1494, and the interpretation of current isolation as evidence against tidal processing. No new physical entities are introduced. Free parameters are limited to the adopted Hubble constant and the velocity association threshold; stellar ages, metallicities, and velocities are fitted outputs, not ad hoc inputs.

free parameters (2)
  • Host-association velocity threshold = ±500 km/s
    Chosen by the authors from Osmond & Ponman (2004) group velocity dispersions to decide which dwarfs are associated with assumed hosts. It is load-bearing for the revised associations of MATLAS-631, 1494, and 1938 and for retaining MATLAS-951 and 1957.
  • Hubble constant H0 = 72 km/s/Mpc
    Assumed in converting recession velocities to distances and physical sizes. It affects MATLAS-1494's reclassification and MATLAS-1938's status as a UDG, though the qualitative conclusions are robust to plausible H0 variations.
assumptions (4)
  • domain assumption The MILES synthetic stellar library with BaSTI isochrones provides adequate templates for fitting these dwarf galaxy spectra.
    Invoked in Section 2.2; systematic differences between template libraries could shift ages and metallicities and may explain part of the offset from Heesters et al. (2023).
  • domain assumption The SED fitting method of Buzzo et al. (2024) is valid for MATLAS-1494 when applied at the newly adopted distance.
    Section 3.1.7; the old and passive classification is derived from this photometric fit, not from the KCWI spectrum, from which the authors say they cannot derive reliable stellar population parameters.
  • ad hoc to paper Current spatial isolation of MATLAS-1494 implies that it has not been tidally processed by a former host.
    This interpretive premise underlies the challenge to tidal quenching models; no orbital history or complete group membership analysis is given.
  • domain assumption The KCWI BL/4550 spectra are sufficient for stellar population parameters in the seven galaxies where they are quoted.
    Section 2.2 restricts fits to 3700-5510 Å and the authors note the MATLAS-585 posterior is skewed toward the grid boundary, indicating template or model limitations that are not fully captured by random uncertainties.

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Cite this review

Pith. "Pith review of Radial velocities and stellar populations for a sample of MATLAS survey dwarfs." pith.science (2026). https://pith.science/paper/FOE336GI

@misc{pith2026250701362,
  author       = {Pith},
  title        = {Pith review of: Radial velocities and stellar populations for a sample of MATLAS survey dwarfs},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FOE336GI}},
  note         = {Machine review of arXiv:2507.01362}
}
read the original abstract

Spectroscopic observations are essential for confirming associations, measuring kinematics, and determining stellar populations in dwarf galaxies. Here, we present Keck Cosmic Web Imager (KCWI) spectra for 12 MATLAS survey dwarfs. For 9, we confirm recession velocities consistent with their literature-assumed host galaxies. We propose revisions of the host galaxy associations for MATLAS-631, 1494, and 1938. For MATLAS-1494, our measured redshift reclassifies it from an ultra-diffuse galaxy candidate to a dwarf galaxy that is of smaller physical size and places it in the field. It also appears old and passive, providing a challenge to models that invoke quenching by tidal effects. Additionally, we measure stellar population estimates for 7 of the 12 galaxies, finding a 'mixed bag' of old quenched galaxies and those that are currently forming stars. Compared to the literature we find generally younger ages and higher metallicities. This result may help reconcile the observed offset of MATLAS survey dwarf galaxies from the universal stellar mass-metallicity relationship reported by Heesters et al. (2023).

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Works this paper leans on

41 extracted references · 4 canonical work pages

  1. [1]

    Osmond J. P. F., Ponman T. J., 2004, MNRAS, 350, 1511. doi:10.1111/j.1365-2966.2004.07742.x

  2. [2]

    doi:10.3847/1538-4365/aaefe9

    Zaritsky D., Donnerstein R., Dey A., Kadowaki J., Zhang H., Karunakaran A., Mart \' nez-Delgado D., et al., 2019, ApJS, 240, 1. doi:10.3847/1538-4365/aaefe9

  3. [3]

    J., Zhang H.-X., Cao T., Puzia T

    Rong Y., Zhu K., Johnston E. J., Zhang H.-X., Cao T., Puzia T. H., Galaz G., 2020, ApJL, 899, L12. doi:10.3847/2041-8213/aba8aa

  4. [4]

    J., Abraham R., Merritt A., Zhang J., et al., 2018, ApJ, 868, 96

    Cohen Y., van Dokkum P., Danieli S., Romanowsky A. J., Abraham R., Merritt A., Zhang J., et al., 2018, ApJ, 868, 96. doi:10.3847/1538-4357/aae7c8

  5. [5]

    W., Liu C., Mihos J

    Wang K., Peng E. W., Liu C., Mihos J. C., C \^o t \'e P., Ferrarese L., Taylor M. A., et al., 2023, Nature, 623, 296. doi:10.1038/s41586-023-06650-z

  6. [6]

    G., Romanowsky A

    Jennings Z. G., Romanowsky A. J., Brodie J. P., Janz J., Norris M. A., Forbes D. A., Martinez-Delgado D., et al., 2015, ApJL, 812, L10. doi:10.1088/2041-8205/812/1/L10

  7. [7]

    N., Kumar Bachchan R., Aryal B., et al., 2023, ApJS, 265, 57

    Paudel S., Yoon S.-J., Yoo J., Smith R., Chhatkuli D. N., Kumar Bachchan R., Aryal B., et al., 2023, ApJS, 265, 57. doi:10.3847/1538-4365/acbfa7

  8. [8]

    J., Spekkens K., et al., 2023, ApJS, 267, 27

    Zaritsky D., Donnerstein R., Dey A., Karunakaran A., Kadowaki J., Khim D. J., Spekkens K., et al., 2023, ApJS, 267, 27. doi:10.3847/1538-4365/acdd71

Show all 41 references
  1. [9]

    J., Lang D., Blum R., Burleigh K., Fan X., Findlay J

    Dey A., Schlegel D. J., Lang D., Blum R., Burleigh K., Fan X., Findlay J. R., Finkbeiner D., Herrera D., Juneau S., et al., 2019, AJ, 157, 168. doi:10.3847/1538-3881/ab089d

  2. [10]

    L., 2017, ApJL, 838, L21

    Kadowaki J., Zaritsky D., Donnerstein R. L., 2017, ApJL, 838, L21. doi:10.3847/2041-8213/aa653d

  3. [11]

    L., Dressler A., Blakeslee J

    Tonry J. L., Dressler A., Blakeslee J. P., Ajhar E. A., Fletcher A. B., Luppino G. A., Metzger M. R., Moore C. B., 2001, ApJ, 546, 681. doi:10.1086/318301

  4. [12]

    J., van der Burg R

    Prole D. J., van der Burg R. F. J., Hilker M., Davies J. I., 2019, MNRAS, 488, 2143. doi:10.1093/mnras/stz1843

  5. [13]

    A., Rejkuba M., Hilker M., Arnaboldi M., Greggio L., Spiniello C., Mieske S., et al., 2022, A&A, 665, A105

    La Marca A., Iodice E., Cantiello M., Forbes D. A., Rejkuba M., Hilker M., Arnaboldi M., Greggio L., Spiniello C., Mieske S., et al., 2022, A&A, 665, A105. doi:10.1051/0004-6361/202142367

  6. [14]

    G., Abraham R., Merritt A., Zhang J., Geha M., Conroy C., 2015, ApJL, 798, L45

    van Dokkum P. G., Abraham R., Merritt A., Zhang J., Geha M., Conroy C., 2015, ApJL, 798, L45. doi:10.1088/2041-8205/798/2/L45

  7. [15]

    A., Alabi A., Romanowsky A

    Forbes D. A., Alabi A., Romanowsky A. J., Brodie J. P., Arimoto N., 2020, MNRAS, 492, 4874. doi:10.1093/mnras/staa180

  8. [16]

    L., Forbes D

    Buzzo M. L., Forbes D. A., Jarrett T. H., Marleau F. R., Duc P.-A., Brodie J. P., Romanowsky A. J., Ferré-Mateu A., Hilker M., Gannon J. S., Pfeffer J., Haacke L., 2025, MNRAS, 536, 2536. doi:10.1093/mnras/stae2700

  9. [17]

    L., Forbes D

    Buzzo M. L., Forbes D. A., Jarrett T. H., Marleau F. R., Duc P.-A., Brodie J. P., Romanowsky A. J., Gannon J. S., Janssens S. R., Pfeffer J., Ferré-Mateu A., Haacke L., Couch W. J., Lim S., Sánchez-Janssen R., 2024, MNRAS, 529, 3210. doi:10.1093/mnras/stae564

  10. [18]

    R., Duc P.-A., Habas R., Fensch J., Emsellem E., Poulain M., Lim S., Agnello A., Durrell P., Paudel S., Sánchez-Janssen R., van der Burg R

    Müller O., Marleau F. R., Duc P.-A., Habas R., Fensch J., Emsellem E., Poulain M., Lim S., Agnello A., Durrell P., Paudel S., Sánchez-Janssen R., van der Burg R. F. J., 2020, A&A, 640, A106. doi:10.1051/0004-6361/202038351

  11. [19]

    Danieli S., van Dokkum P., Trujillo-Gomez S., Kruijssen J. M. D., Romanowsky A. J., Carlsten S., Shen Z., Li J., Abraham R., Brodie J., Conroy C., Gannon J. S., Greco J., 2022, ApJL, 927, L28. doi:10.3847/2041-8213/ac590a

  12. [20]

    A., Buzzo M

    Forbes D. A., Buzzo M. L., Ferre-Mateu A., Romanowsky A. J., Gannon J., Brodie J. P., Collins M. L. M., 2025, MNRAS, 536, 1217. doi:10.1093/mnras/stae2675

  13. [21]

    S., Forbes D

    Gannon J. S., Forbes D. A., Romanowsky A. J., Brodie J. P., Haacke L., Ferr \'e -Mateu A., Danieli S., van Dokkum P., Buzzo M. L., Couch W. J., Shen Z., 2024, MNRAS, 531, 1789. doi:10.1093/mnras/stae1274

  14. [22]

    N., Cohen J

    Kirby E. N., Cohen J. G., Guhathakurta P., Cheng L., Bullock J. S., Gallazzi A., 2013, ApJ, 779, 102. doi:10.1088/0004-637X/779/2/102

  15. [23]

    S., Ferr \'e -Mateu A., Forbes D

    Gannon J. S., Ferr \'e -Mateu A., Forbes D. A., Brodie J. P., Buzzo M. L., Romanowsky A. J., 2024, MNRAS, 531, 1856. doi:10.1093/mnras/stae1287

  16. [24]

    J., Zaritsky D., Donnerstein R., 2024, AJ, 167, 61

    Lambert M., Khim D. J., Zaritsky D., Donnerstein R., 2024, AJ, 167, 61. doi:10.3847/1538-3881/ad0f25

  17. [25]

    A., Gannon J

    Haacke L., Forbes D. A., Gannon J. S., Danieli S., Brodie J. P., Pfeffer J., Romanowsky A. J., van Dokkum P., Janssens S. R., Buzzo M. L., Shen Z., 2025, MNRAS, 539, 674. doi:10.1093/mnras/staf559

  18. [26]

    S., Forbes D

    Ferr \'e -Mateu A., Gannon J. S., Forbes D. A., Buzzo M. L., Romanowsky A. J., Brodie J. P., 2023, MNRAS, 526, 4735. doi:10.1093/mnras/stad3102

  19. [27]

    R., Duc P.-A., Poulain M., M \"u ller O., Lim S., Durrell P

    Marleau F. R., Duc P.-A., Poulain M., M \"u ller O., Lim S., Durrell P. R., Habas R., S \'a nchez-Janssen R., Paudel S., Fensch J., 2024, A&A, 690, A339. doi:10.1051/0004-6361/202449617

  20. [28]

    R., Habas R., Poulain M., Duc P.-A., Müller O., Lim S., Durrell P

    Marleau F. R., Habas R., Poulain M., Duc P.-A., Müller O., Lim S., Durrell P. R., Sánchez-Janssen R., Paudel S., Ahad S. L., Chougule A., Bílek M., Fensch J., 2021, AAP, 654, A105. doi:10.1051/0004-6361/202141432

  21. [29]

    R., Duc P.-A., Sánchez-Janssen R., Poulain M., Habas R., Lim S., Durrell P

    Heesters N., Müller O., Marleau F. R., Duc P.-A., Sánchez-Janssen R., Poulain M., Habas R., Lim S., Durrell P. R., 2023, AAP, 676, A33. doi:10.1051/0004-6361/202346441

  22. [30]

    C., Neill J

    Morrissey P., Matuszewski M., Martin D. C., Neill J. D., Epps H., Fucik J., Weber B., Darvish B., Adkins S., Allen S., Bartos R., Belicki J., Cabak J., Callahan S., Cowley D., Crabill M., Deich W., Delecroix A., Doppman G., Hilyard D., James E., Kaye S., Kokorowski M., Kwok S....

  23. [31]

    R., Abraham R., Brodie J., Forbes D

    Janssens S. R., Abraham R., Brodie J., Forbes D. A., Romanowsky A. J., 2019, ApJ, 887, 92. doi:10.3847/1538-4357/ab536c

  24. [32]

    R., Paudel S., Mueller O., Lim S., Bilek M., Fensch J., 2021, VizieR On-line Data Catalog: J/A+A/659/A14

    Poulain M., Marleau F., Habas R., Duc P.-A., Sanchez-Janssen R., Durrell P. R., Paudel S., Mueller O., Lim S., Bilek M., Fensch J., 2021, VizieR On-line Data Catalog: J/A+A/659/A14. doi:10.26093/cds/vizier.36590014

  25. [33]

    M., Scott N., Verdoes Kleijn G

    Cappellari M., Emsellem E., Krajnović D., McDermid R. M., Scott N., Verdoes Kleijn G. A., Young L. M., Alatalo K., Bacon R., Blitz L., Bois M., Bournaud F., Bureau M., Davies R. L., Davis T. A., de Zeeuw P. T., Duc P.-A., Khochfar S., Kuntschner H., Lablanche P.-Y., Morganti R...

  26. [34]

    doi:10.1093/mnras/stw3020

    Cappellari M., 2017, MNRAS, 466, 798. doi:10.1093/mnras/stw3020

  27. [35]

    D., 2019, ARA&A, 57, 375

    Simon J. D., 2019, ARA&A, 57, 375. doi:10.1146/annurev-astro-091918-104453

  28. [36]

    Ott T., 2012, Astrophysics Source Code Library, record ascl:1210.019

  29. [37]

    C., Katz D

    Jacob J. C., Katz D. S., Berriman G. B., Good J., Laity A. C., Deelman E., Kesselman C., Singh G., Su M.-H., Prince T. A., Williams R., 2010, arXiv e-prints, arXiv:1005.4454. doi:10.48550/arXiv.1005.4454

  30. [38]

    F., Knapen J

    Saifollahi T., Zaritsky D., Trujillo I., Peletier R. F., Knapen J. H., Amorisco N., Beasley M. A., Donnerstein R., 2022, MNRAS, 511, 4633. doi:10.1093/mnras/stac328

  31. [39]

    R., Duc P.-A., Durrell P

    Habas R., Marleau F. R., Duc P.-A., Durrell P. R., Paudel S., Poulain M., Sánchez-Janssen R., Sreejith S., Ramasawmy J., Stemock B., Leach C., Cuillandre J.-C., Gwyn S., Agnello A., Bílek M., Fensch J., Müller O., Peng E. W., van der Burg R. F. J., 2020, MNRAS, 491, 1901. doi:...

  32. [40]

    B., Dutton A

    Di Cintio A., Brook C. B., Dutton A. A., Macciò A. V., Obreja A., Dekel A., 2017, MNRAS, 466, L1. doi:10.1093/mnrasl/slw210

  33. [41]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry add.period write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence '...

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.