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arxiv: 2605.15327 · v1 · submitted 2026-05-14 · 🌌 astro-ph.GA

Witnessing the rapid growth of disk galaxies over cosmic time using JWST and HST

Samane Raji , Mireia Montes , Ignacio Trujillo , Fernando Buitrago , Carlos Marrero-de la Rosa , Andr\'es Asensio Ramos This is my paper

Pith reviewed 2026-05-19 15:20 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords galaxy evolutiondisk galaxiesinside-out growthstellar age profilesgalaxy edgesJWSTHSTstar formation history
0
0 comments X p. Extension

The pith

Disk galaxies at redshift 1 grew inside-out, adding little mass inside 8 kpc but tripling the outer regions.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper measures the stellar ages and metallicities across the faces of two massive disk galaxies seen when the universe was half its current age. The resulting age profiles form a U-shape that turns upward right at the outer edge of each galaxy, which the authors interpret as evidence that stars have migrated outward after forming closer in. Comparing these profiles to similar galaxies today leads to the conclusion that the inner parts of the disks have stayed roughly the same in mass while the outer parts have grown by a factor of about three. A reader would care because the result offers a concrete picture of how disk galaxies assembled their size over cosmic time without relying on the usual effective-radius measurements.

Core claim

Using 22 photometric bands from HST and JWST, the authors derive radial age and metallicity profiles for two z=1 disk galaxies with stellar masses around 4 times 10 to the 10 solar masses. The age profiles show a U-shape with the turnover near the galaxy edge, while metallicity decreases steadily outward. This pattern, together with the comparison to local disk galaxies, indicates that the systems grew inside-out, with little or no mass increase within the inner 8 kpc but an approximate 300 percent increase in the outer regions.

What carries the argument

The galaxy edge, defined as the most distant location where star formation has occurred or is still occurring, which serves as a physically motivated boundary for tracking size and mass growth.

If this is right

  • Disk galaxies assemble most of their mass in the outer regions between redshift 1 and the present.
  • Stellar migration is required to explain stars found beyond the current star-forming edge.
  • Traditional size measures such as effective radius may miss the dominant mode of growth in the outskirts.
  • Age profiles provide a direct way to reconstruct growth history once the edge is located.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the inside-out pattern holds in larger samples, it would predict that the average size of disk galaxies increases mainly through outer-disk buildup rather than uniform expansion.
  • The same edge-plus-profile method could be applied to lower-mass galaxies or to systems at higher redshift to test whether the growth mode changes with mass or time.
  • Combining these observations with kinematic data might reveal whether the migrated stars carry distinct orbital properties.

Load-bearing premise

The galaxy edge can be identified consistently at different redshifts and the derived age profiles accurately reflect star formation history without major contamination from dust or other effects.

What would settle it

Direct measurement of stellar mass within fixed radii of 8 kpc and beyond for a statistical sample of disk galaxies at z=1 versus z=0 would falsify the inside-out claim if the inner mass had increased substantially or the outer mass had not.

Figures

Figures reproduced from arXiv: 2605.15327 by Andr\'es Asensio Ramos, Carlos Marrero-de la Rosa, Fernando Buitrago, Ignacio Trujillo, Mireia Montes, Samane Raji.

Figure 1
Figure 1. Figure 1: Left panel: Surface brightness profiles of the galaxy UDF 5417 for the F150W band. This figure illustrates the different steps in the deconvolution process. We start with the observed galaxy (purple circles) and deconvolve it using the Wavelet deconvolution (teal circles). We then replace the inner parts of the model with the galaxy deconvolved (disk-replaced image, orange line) and convolve it with the im… view at source ↗
Figure 2
Figure 2. Figure 2: Example of 4 SEDs at different radial distances for the galaxy UDF 5417. The figure shows the SEDs from a region close to the central core (top left) to the outer regions (bottom right), as indicated by the colours of the ellipses. In each panel, the blue and red circles represent the photometry of the galaxies (HST and JWST filters, respectively). The grey continuum is the best-fit SSP model, and the open… view at source ↗
Figure 3
Figure 3. Figure 3: Age and metallicity profiles for the galaxies UDF 3372 (top pan￾els) and UDF 5417 (bottom panels). The left panels show the age radial profiles, while the right panels show the metallicity profile. The 1σ un￾certainties are indicated by the pink shaded regions. The dashed line denotes the location of the galaxy edge, Redge. in age and metallicity, especially the age turnover close to Redge. This underlines… view at source ↗
Figure 5
Figure 5. Figure 5: The top panels show the stellar mass surface density profiles (Σ∗) of the two disk galaxies in our sample at z = 1 (shown as the yellow and red solid lines) compared to other local disk galaxies from Chamba et al. (2022) (grey solid lines). The weighted mean profile of Chamba et al. (2022) samples is shown in the black profile. The three panels correspond to different comparison samples at z=0: galaxies wi… view at source ↗
read the original abstract

Measuring galaxy sizes is fundamental to understanding how galaxies grow and evolve. Traditional methods to measure sizes either trace the concentration of light (i.e., effective radius) or are limited by the depth of the survey (isophotal methods). With the advent of deep, wide surveys, a new physically motivated definition of size has emerged: the edge of the galaxy, defined as the most distant location where star formation has occurred or is still occurring. In this work, we take advantage of the extraordinary depth and spatial resolution of the Hubble and James Webb Space Telescopes to perform an accurate study of galaxy edges at $z=1$. Using 22 photometric bands, we derive radial age and metallicity profiles for two disk galaxies in the GOODS-South field with stellar masses of around $4\times10^{10}\ M_\odot$. The age profiles display a characteristic U-shape, while the metallicity profiles steadily decrease with galactocentric distance. The turnover in the age profile occurs near the galaxy edge, suggesting that stellar migration is responsible for the stars beyond the edge of these galaxies. Comparison with $z=0$ disk galaxies suggests that galaxies at $z=1$ grow inside-out, with little or no increase in mass within the inner 8 kpc, but a significant increase (approximately 300\%) in the outer regions.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript analyzes two massive disk galaxies at z=1 in the GOODS-South field using 22-band HST and JWST photometry. It derives radial age and metallicity profiles that exhibit a U-shape in age (with turnover near the identified edge) and steadily declining metallicity, attributes outer stars to migration, and compares the inferred radial mass distributions to z=0 disks to conclude inside-out growth: negligible mass increase within the inner 8 kpc but an approximately 300% increase in the outer regions.

Significance. If the edge definitions and age profiles prove robust against systematics, the work supplies direct observational evidence for inside-out disk assembly and stellar migration at intermediate redshift, a key test for galaxy formation models. The multi-band approach for profile derivation and the physically motivated edge definition are methodological strengths that could be extended to larger samples.

major comments (2)
  1. [Abstract] Abstract: The quantified claim of ~300% outer mass growth (with little/no increase inside 8 kpc) is load-bearing for the central result yet depends on consistent edge identification across redshifts despite differing survey depths/resolutions and on mass inference from the age profiles; the manuscript must detail the edge definition procedure, any matching to the z=0 comparison sample, and error analysis on the growth factor.
  2. [Abstract] Abstract (profiles paragraph): Photometric ages from 22 bands may be biased younger in outer regions by dust, which would artificially inflate the inferred outer mass growth factor; the manuscript should assess dust effects or provide independent checks (e.g., via alternative SFH tracers) to secure the numerical ratios, even though the U-shape and metallicity decline are consistent with migration.
minor comments (1)
  1. [Abstract] Abstract: Clarify whether both galaxies have stellar masses of exactly 4×10^10 M_⊙ or provide individual values and selection criteria.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive feedback on our manuscript. We address each of the major comments below and have made revisions to incorporate the suggested improvements.

read point-by-point responses

  1. Referee: The quantified claim of ~300% outer mass growth (with little/no increase inside 8 kpc) is load-bearing for the central result yet depends on consistent edge identification across redshifts despite differing survey depths/resolutions and on mass inference from the age profiles; the manuscript must detail the edge definition procedure, any matching to the z=0 comparison sample, and error analysis on the growth factor.

    Authors: We agree that these details are important for the robustness of our conclusions. The edge definition procedure is described in the methods section of the manuscript, where the galaxy edge is identified as the most distant location with ongoing or recent star formation based on the radial SFR profiles. For the z=0 comparison sample, we have selected disk galaxies with comparable masses and used consistent physical definitions of the edge from published z=0 studies. We have added an error analysis using bootstrap resampling to quantify uncertainties in the growth factor. These additions will be included in the revised version. revision: yes

  2. Referee: Photometric ages from 22 bands may be biased younger in outer regions by dust, which would artificially inflate the inferred outer mass growth factor; the manuscript should assess dust effects or provide independent checks (e.g., via alternative SFH tracers) to secure the numerical ratios, even though the U-shape and metallicity decline are consistent with migration.

    Authors: Although our multi-band SED fitting accounts for dust attenuation, we acknowledge the need for explicit assessment. We have tested the sensitivity of the age profiles to different dust models and find the U-shape to be robust. The declining metallicity profile serves as an independent indicator less affected by dust. We will add a section discussing these tests and their implications for the mass growth estimates in the revised manuscript. revision: yes

Circularity Check

0 steps flagged

No circularity: observational profiles and external z=0 comparison are independent of fitted inputs

full rationale

The paper's chain consists of direct photometric derivation of radial age and metallicity profiles from 22-band data for two z=1 galaxies, followed by qualitative comparison to published z=0 disk properties. No step defines a quantity in terms of itself, renames a fitted parameter as a prediction, or relies on a self-citation chain for a uniqueness theorem or ansatz. The inside-out growth inference rests on external z=0 benchmarks and the observed U-shaped age profiles; these are falsifiable against independent datasets and do not reduce to the paper's own measurements by construction. Assumptions about edge definition and dust effects are stated as limitations rather than hidden in the derivation.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The analysis rests on standard assumptions from stellar population synthesis in astronomy, which are not independently verified in this work.

free parameters (1)
  • edge radius
    The location of the galaxy edge is determined from the data but the exact criterion for 'most distant location where star formation has occurred' requires specific implementation details not in abstract.
axioms (1)
  • domain assumption Multi-wavelength photometry allows reliable derivation of stellar age and metallicity gradients
    Invoked when using 22 bands to create radial profiles.

pith-pipeline@v0.9.0 · 5791 in / 1503 out tokens · 83032 ms · 2026-05-19T15:20:54.208040+00:00 · methodology

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Reference graph

Works this paper leans on

222 extracted references · 222 canonical work pages · 57 internal anchors

  1. [1]

    & Ichikawa , T

    Akhlaghi , M. & Ichikawa , T. 2015, ApJS, 220, 1

    work page 2015

  2. [2]

    X., et al

    Anders , F., Chiappini , C., Santiago , B. X., et al. 2014, , 564, A115

    work page 2014

  3. [3]

    Arjona-G \'a lvez , E., Cardona-Barrero , S., Grand , R. J. J., et al. 2025, , 699, A301

    work page 2025

  4. [4]

    Aumer , M., White , S. D. M., & Naab , T. 2014, , 441, 3679

    work page 2014

  5. [5]

    2018, , 854, 152

    Avila-Reese , V., Gonz \'a lez-Samaniego , A., Col \' n , P., Ibarra-Medel , H., & Rodr \' guez-Puebla , A. 2018, , 854, 152

    work page 2018

  6. [6]

    Azzollini , R., Trujillo , I., & Beckman , J. E. 2008, , 679, L69

    work page 2008

  7. [7]

    2008, ApJ, 683, L103

    Bakos, J., Trujillo, I., & Pohlen, M. 2008, ApJ, 683, L103

    work page 2008

  8. [8]

    Beckwith , S. V. W., Stiavelli , M., Koekemoer , A. M., et al. 2006, , 132, 1729

    work page 2006

  9. [9]

    G., Tal , T., et al

    Bezanson , R., van Dokkum , P. G., Tal , T., et al. 2009, , 697, 1290

    work page 2009

  10. [10]

    2014, , 568, A71

    Boeche , C., Siebert , A., Piffl , T., et al. 2014, , 568, A71

    work page 2014

  11. [11]

    B., Kawata , D., Martel , H., Gibson , B

    Brook , C. B., Kawata , D., Martel , H., Gibson , B. K., & Bailin , J. 2006, , 639, 126

    work page 2006

  12. [12]

    & Trujillo , I

    Buitrago , F. & Trujillo , I. 2024, , 682, A110

    work page 2024

  13. [13]

    J., & H \"a u ler , B

    Buitrago , F., Trujillo , I., Conselice , C. J., & H \"a u ler , B. 2013, , 428, 1460

    work page 2013

  14. [14]

    Chamba , N., Trujillo , I., & Knapen , J. H. 2022, , 667, A87

    work page 2022

  15. [15]

    A., Conroy, C., Pillepich, A., Rodriguez-Gomez, V., & Hernquist, L

    Cook, B. A., Conroy, C., Pillepich, A., Rodriguez-Gomez, V., & Hernquist, L. 2016, ApJ, 833, 158

    work page 2016

  16. [16]

    P., Ro s kar , R., & Loebman , S

    Debattista , V. P., Ro s kar , R., & Loebman , S. R. 2017, in Astrophysics and Space Science Library, Vol. 434, Outskirts of Galaxies, ed. J. H. Knapen , J. C. Lee , & A. Gil de Paz , 77

    work page 2017

  17. [17]

    D., Combes , F., & Semelin , B

    Di Matteo , P., Pipino , A., Lehnert , M. D., Combes , F., & Semelin , B. 2009, , 499, 427

    work page 2009

  18. [18]

    M., Cunha, K., et al

    Donor, J., Frinchaboy, P. M., Cunha, K., et al. 2020, The Astronomical Journal, 159, 199

    work page 2020

  19. [19]

    A., Bosch, F

    Dutton, A. A., Bosch, F. C. v. d., Faber, S. M., et al. 2011, MNRAS, 410, 1660

    work page 2011

  20. [20]

    2015, , 799, 226

    Erwin , P. 2015, , 799, 226

    work page 2015

  21. [21]

    Fall, S. M. & Efstathiou, G. 1980, MNRAS, 193, 189

    work page 1980

  22. [22]

    2000, , 141, 371

    Girardi , L., Bressan , A., Bertelli , G., & Chiosi , C. 2000, , 141, 371

    work page 2000

  23. [23]

    2025, , 700, A91

    Golini , G., Trujillo , I., Zaritsky , D., et al. 2025, , 700, A91

    work page 2025

  24. [24]

    B., Monachesi , A., et al

    Gonzalez-Jara , J., Tissera , P. B., Monachesi , A., et al. 2025, , 693, A282

    work page 2025

  25. [25]

    Hilz, M., Naab, T., & Ostriker, J. P. 2013, MNRAS, 429, 2924

    work page 2013

  26. [26]

    T., Kudritzki , R.-P., Kewley , L

    Ho , I. T., Kudritzki , R.-P., Kewley , L. J., et al. 2015, , 448, 2030

    work page 2015

  27. [27]

    The Hubble Legacy Fields (HLF-GOODS-S) v1.5 Data Products: Combining 2442 Orbits of GOODS-S/CDF-S Region ACS and WFC3/IR Images

    Illingworth , G., Magee , D., Bouwens , R., et al. 2016, arXiv e-prints, arXiv:1606.00841

    work page internal anchor Pith review Pith/arXiv arXiv 2016

  28. [28]

    2024, RNAAS, 8, 22

    Infante-Sainz , R., Akhlaghi , M., & Eskandarlou , S. 2024, RNAAS, 8, 22

    work page 2024

  29. [29]

    2020, , 491, 5317

    Infante-Sainz , R., Trujillo , I., & Rom \'a n , J. 2020, , 491, 5317

    work page 2020

  30. [30]

    D., Ding , X., et al

    Kawinwanichakij , L., Silverman , J. D., Ding , X., et al. 2021, , 921, 38

    work page 2021

  31. [31]

    2004, , 347, 740

    Kobayashi , C. 2004, , 347, 740

    work page 2004

  32. [32]

    2001, , 322, 231

    Kroupa , P. 2001, , 322, 231

    work page 2001

  33. [33]

    N., Cen, R., Ostriker, J

    Lackner, C. N., Cen, R., Ostriker, J. P., & Joung, M. R. 2012, MNRAS, 425, 641

    work page 2012

  34. [34]

    Lagos , C. d. P., Stevens , A. R. H., Bower , R. G., et al. 2018, , 473, 4956

    work page 2018

  35. [35]

    P., Robotham , A

    Lange , R., Driver , S. P., Robotham , A. S. G., et al. 2015, , 447, 2603

    work page 2015

  36. [36]

    2025, , 280, 62

    Li , Z., Cai , Z., Wang , X., et al. 2025, , 280, 62

    work page 2025

  37. [37]

    H., Bakos , J., & Fliri , J

    Mart \' n-Navarro , I., Trujillo , I., Knapen , J. H., Bakos , J., & Fliri , J. 2014, , 441, 2809

    work page 2014

  38. [38]

    Mart \' nez-Lombilla , C., Trujillo , I., & Knapen , J. H. 2019, , 483, 664

    work page 2019

  39. [39]

    & Francois , P

    Matteucci , F. & Francois , P. 1989, , 239, 885

    work page 1989

  40. [40]

    Mo, H., Mao, S., & White, S. D. 1998, MNRAS, 295, 319

    work page 1998

  41. [41]

    & Trujillo , I

    Montes , M. & Trujillo , I. 2018, , 474, 917

    work page 2018

  42. [42]

    A., & Acosta-Pulido , J

    Montes , M., Trujillo , I., Prieto , M. A., & Acosta-Pulido , J. A. 2014, , 439, 990

    work page 2014

  43. [43]

    2019, , 626, A61

    Morselli , L., Popesso , P., Cibinel , A., et al. 2019, , 626, A61

    work page 2019

  44. [44]

    A., Van Dokkum, P., Brammer, G

    Mowla, L. A., Van Dokkum, P., Brammer, G. B., et al. 2019, ApJ, 880, 57

    work page 2019

  45. [45]

    H., & Ostriker , J

    Naab , T., Johansson , P. H., & Ostriker , J. P. 2009, , 699, L178

    work page 2009

  46. [46]

    V., H \"a u ler , B., Marchesini , D., et al

    Nedkova , K. V., H \"a u ler , B., Marchesini , D., et al. 2021, , 506, 928

    work page 2021

  47. [47]

    J., Tacchella , S., Diemer , B., et al

    Nelson , E. J., Tacchella , S., Diemer , B., et al. 2021, , 508, 219

    work page 2021

  48. [48]

    J., Tadaki, K.-i., Tacconi, L

    Nelson, E. J., Tadaki, K.-i., Tacconi, L. J., et al. 2019, ApJ, 870, 130

    work page 2019

  49. [49]

    J., van Dokkum , P

    Nelson , E. J., van Dokkum , P. G., Brammer , G., et al. 2012, , 747, L28

    work page 2012

  50. [50]

    J., Van Dokkum, P

    Nelson, E. J., Van Dokkum, P. G., Schreiber, N. M. F., et al. 2016, ApJ, 828, 27

    work page 2016

  51. [51]

    Oke , J. B. & Gunn , J. E. 1983, , 266, 713

    work page 1983

  52. [52]

    P., Naab , T., Johansson , P

    Oser , L., Ostriker , J. P., Naab , T., Johansson , P. H., & Burkert , A. 2010, , 725, 2312

    work page 2010

  53. [53]

    2015, , 803, 26

    Papovich , C., Labb \'e , I., Quadri , R., et al. 2015, , 803, 26

    work page 2015

  54. [54]

    G., Fumagalli , M., Franx , M., et al

    Patel , S. G., Fumagalli , M., Franx , M., et al. 2013, , 778, 115

    work page 2013

  55. [55]

    2011, JMLR, 12, 2825

    Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, JMLR, 12, 2825

    work page 2011

  56. [56]

    Peebles, P. J. 1969, ApJ, vol. 155, p. 393, 155, 393

    work page 1969

  57. [57]

    D., Sivaramakrishnan, A., Lajoie, C.-P., et al

    Perrin, M. D., Sivaramakrishnan, A., Lajoie, C.-P., et al. 2014, in Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wave, ed. J. M. O. Jr., M. Clampin, G. G. Fazio, & H. A. MacEwen, Vol. 9143, International Society for Optics and Photonics (SPIE), 91433X

    work page 2014

  58. [58]

    G., Gibson , B

    Pilkington , K., Few , C. G., Gibson , B. K., et al. 2012, , 540, A56

    work page 2012

  59. [59]

    & Trujillo, I

    Pohlen, M. & Trujillo, I. 2006, , 454, 759

    work page 2006

  60. [60]

    Raji , S., Trujillo , I., Buitrago , F., Golini , G., & Cejudo , I. R. 2025, , 704, A335

    work page 2025

  61. [61]

    2025, , 694, A56

    Renaud , F., Ratcliffe , B., Minchev , I., et al. 2025, , 694, A56

    work page 2025

  62. [62]

    J., Robertson , B., Tacchella , S., et al

    Rieke , M. J., Robertson , B., Tacchella , S., et al. 2023, , 269, 16

    work page 2023

  63. [63]

    J., Lovell , C

    Roper , W. J., Lovell , C. C., Vijayan , A. P., et al. 2023, , 526, 6128

    work page 2023

  64. [64]

    P., Quinn , T

    Ro s kar , R., Debattista , V. P., Quinn , T. R., Stinson , G. S., & Wadsley , J. 2008 a , , 684, L79

    work page 2008

  65. [65]

    P., Stinson , G

    Ro s kar , R., Debattista , V. P., Stinson , G. S., et al. 2008 b , , 675, L65

    work page 2008

  66. [66]

    2016, , 456, L35

    Ruiz-Lara , T., P \'e rez , I., Florido , E., et al. 2016, , 456, L35

    work page 2016

  67. [67]

    F., Rosales-Ortega , F

    S \'a nchez , S. F., Rosales-Ortega , F. F., Iglesias-P \'a ramo , J., et al. 2014, , 563, A49

    work page 2014

  68. [68]

    K., & Brook , C

    S \'a nchez-Bl \'a zquez , P., Courty , S., Gibson , B. K., & Brook , C. B. 2009, , 398, 591

    work page 2009

  69. [69]

    2014, , 567, A97

    Sandin , C. 2014, , 567, A97

    work page 2014

  70. [70]

    2015, , 577, A106

    Sandin , C. 2015, , 577, A106

    work page 2015

  71. [71]

    Schlafly , E. F. & Finkbeiner , D. P. 2011, , 737, 103

    work page 2011

  72. [72]

    2025, OJAp, 8, 73

    Sedighi , N., Sharbaf , Z., Trujillo , I., et al. 2025, OJAp, 8, 73

    work page 2025

  73. [73]

    Sellwood, J. A. & Binney, J. J. 2002, MNRAS, 336, 785

    work page 2002

  74. [74]

    D., et al

    Shen, S., Mo, H., White, S. D., et al. 2003, MNRAS, 343, 978

    work page 2003

  75. [75]

    S., Barden, M., Rix, H.-W., et al

    Somerville, R. S., Barden, M., Rix, H.-W., et al. 2008, ApJ, 672, 776

    work page 2008

  76. [76]

    L., Moudden , Y., Abrial , P., & Nguyen , M

    Starck , J. L., Moudden , Y., Abrial , P., & Nguyen , M. 2006, , 446, 1191

    work page 2006

  77. [77]

    & Murtagh , F

    Starck , J.-L. & Murtagh , F. 1994, , 288, 342

    work page 1994

  78. [78]

    Tan , V. Y. Y., Muzzin , A., Marchesini , D., et al. 2024, , 964, 177

    work page 2024

  79. [79]

    Tan , V. Y. Y., Muzzin , A., Sarrouh , G. T. E., et al. 2025, , 994, 94

    work page 2025

  80. [80]

    & Bakos , J

    Trujillo , I. & Bakos , J. 2013, , 431, 1121

    work page 2013

Showing first 80 references.