pith. machine review for the scientific record. sign in

arxiv: 2605.01000 · v2 · submitted 2026-05-01 · 🌌 astro-ph.GA

Recognition: unknown

Prospects for Observing Galaxy Spectral Energy Distribution from the Radio to the far-Infrared in the Era of Next-Generation Radio Telescopes

Ilsang Yoon , Jonathan Letai , Hansung B. Gim , Eric F. Jim\'enez-Andrade , Intae Jung , Caitlin Casey , Eric J. Murphy , Min S. Yun
Authors on Pith no claims yet

Pith reviewed 2026-05-09 18:32 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords galaxy spectral energy distributionradio-infrared correlationhigh-redshift galaxiesstar-forming galaxiesSKAngVLAepoch of reionizationradio continuum
0
0 comments X

The pith

Next-generation radio telescopes can detect radio to far-infrared SEDs of galaxies with stellar masses above 10^9 solar masses at any redshift up to 20.

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

The paper explores how the sensitivity and frequency range of telescopes such as the SKA and ngVLA will sample the radio and far-infrared continuum emission from galaxies out to redshift 20. Simulations of energy-balanced SEDs for UV star-forming galaxies and dusty star-forming galaxies incorporate the radio-infrared correlation and the cosmic microwave background to predict flux densities at relevant observing frequencies. These predictions indicate that current and planned facilities will make massive galaxies detectable across wide redshift ranges where optical observations face limitations. A sympathetic reader would care because this approach offers a way to study galaxy properties during the epoch of reionization using wavelengths less affected by dust obscuration.

Core claim

The central claim is that simulated flux density evolution shows massive galaxies with stellar mass at least 10^10 solar masses remain detectable at any redshift in frequencies above 90 GHz, the ngVLA high-frequency band near 100 GHz can detect galaxies with stellar mass at least 10^9 solar masses almost independently of redshift, and the SKA low-frequency window below 1 GHz can detect dusty star-forming galaxies with stellar mass at least 10^10 solar masses up to redshifts 5 to 7. The anomalous microwave emission component is insignificant in the SEDs of galaxies beyond the local universe at redshifts greater than 0.1.

What carries the argument

Energy-balanced panchromatic SED models extended from UV to radio wavelengths, combined with the radio-IR correlation and CMB corrections, to compute observable flux densities at telescope frequencies for different galaxy populations.

If this is right

  • Massive galaxies above 10^10 solar masses are detectable at any redshift in high-frequency bands above 90 GHz with facilities like ALMA and ngVLA.
  • The ngVLA at approximately 100 GHz can detect galaxies down to 10^9 solar masses with little dependence on redshift.
  • The SKA low-frequency band below 1 GHz reaches dusty star-forming galaxies with stellar masses above 10^10 solar masses up to the epoch of reionization.
  • Anomalous microwave emission contributes negligibly to the SED for galaxies at redshifts greater than 0.1.
  • Full radio-FIR SED sampling will support studies of galaxy formation and evolution at high redshift.

Where Pith is reading between the lines

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

  • Radio observations could supply dust-independent star formation rate estimates for early galaxies that complement infrared data.
  • Combining these detections with multi-wavelength surveys might test whether SED models calibrated locally apply at high redshift.
  • Large radio surveys could build statistical samples of high-redshift galaxies selected by their radio continuum rather than optical brightness.
  • This capability extends the reach of ALMA by covering lower frequencies where synchrotron emission dominates.

Load-bearing premise

The radio-infrared correlation and energy-balanced SED models remain valid for high-redshift galaxies whose magnetic fields, cosmic ray densities, and dust properties may differ from local calibrators.

What would settle it

A ngVLA survey at 100 GHz that detects no galaxies with stellar masses near 10^9 solar masses at redshifts 5 to 10, or measures radio flux densities that systematically fall below predictions scaled from their infrared luminosities.

Figures

Figures reproduced from arXiv: 2605.01000 by Caitlin Casey, Eric F. Jim\'enez-Andrade, Eric J. Murphy, Hansung B. Gim, Ilsang Yoon, Intae Jung, Jonathan Letai, Min S. Yun.

Figure 1
Figure 1. Figure 1: Model galaxy spectral energy distribution illus￾trating four major radiation processes: synchrotron emission, free-free emission, anomalous microwave emission, and ther￾mal dust emission the radio emission in the intermediate-frequency (1–100 GHz) is set by a mixture of the four radiation processes. The model spectrum in view at source ↗
Figure 2
Figure 2. Figure 2: Synchrotron dimming factor, fs in Equation 3 as a function of redshift (z) for different gas surface density Σg, without the consideration of turbulent magnetic field enhancement (i.e., UB(z) = UB(0)) Yoon (2024) expresses each energy loss rate in Equa￾tion 3 as a function of gas surface density2 (Σg) in￾ferred from star formation rate surface density using the Kennicutt-Schmidt relation (Kennicutt & Evans… view at source ↗
Figure 3
Figure 3. Figure 3: The peak frequency and the corresponding flux density at the peak frequency for AME at different redshift. The flux density values scale with l 2 and NH. JWST discovered high-z galaxies which are the rest￾frame UV-bright star-forming galaxies with star for￾mation rate of 1–10 M⊙ yr−1 (e.g., Atek et al. 2023b; Roberts-Borsani et al. 2023; Franco et al. 2024; Robert￾son et al. 2023; Castellano et al. 2024; W… view at source ↗
Figure 4
Figure 4. Figure 4: Panel A illustrates the variation with the redshift of 14 SEDs without including the CMB heating and contrast, for models with all other parameters the same: tau main = 100 Myr, age main = 100 Myr, metallicity = 0.02, Av ISM = 4, and Td,∗ = 30 K (note that Td does vary with redshift). Panels B-I, B-II, and B-III show the effect of the CMB for three of the same models at different redshifts: z = 1.057, 7.73… view at source ↗
Figure 5
Figure 5. Figure 5: Panels A-I, A-II, and A-III illustrate how SEDs vary with temperature at three redshifts z = 1.057, 7.739, 20.823. All physical parameters, except for temperature, are the same as for the SEDs in view at source ↗
Figure 6
Figure 6. Figure 6: The radio flux density variation as a function of redshift for a given observing frequency, for galaxies sampled from the JAGUAR catalog. Each row corresponds to a different mass bin — from top to bottom: Mchar(z), 6 ≤ M < 7, 7 ≤ M < 8, 8 ≤ M < 9, 9 ≤ M < 10, and 10 ≤ M < 11. The 11 ≤ M is not plotted because it appears to be unreliable due to small sample sizes. For a given mass bin, the flux density of a… view at source ↗
Figure 7
Figure 7. Figure 7: Same as view at source ↗
Figure 8
Figure 8. Figure 8: In the top row, the flux density of a DSFG with M∗ = 1011M⊙ is plotted as a function of redshift and compared to the 3σ RMS of the SKA and/or ngVLA ( view at source ↗
Figure 9
Figure 9. Figure 9: Same as view at source ↗
Figure 10
Figure 10. Figure 10: Each group of four panels shows a 2-D histogram overlaid with the fits to the four physical parameters of the galaxies in each mass bin of the JAGUAR catalog. The orange lines indicate the median values at each redshift bin, while the red lines show the fit to these median values as a function of time. Note that the x-axis is re-scaled to redshift. Also note the changes in axes’ limits and scale view at source ↗
read the original abstract

The superb sensitivity and angular resolution of the next-generation radio telescopes with combined frequency coverage of approximately over three orders of magnitude (100 MHz--100 GHz) will sample the radio and far-infrared (FIR) spectral energy distribution (SED) of galaxies and revolutionize the galaxy formation study at the epoch of re-ionization and beyond. We present a prospect of observing the radio--FIR continuum SEDs of galaxies in the redshift of up to $z\approx 20$ based on an ensemble of the simulated `energy balanced' panchromatic SED (from UV to FIR) extended to the radio. For `realistic' populations of UV star-forming galaxies and dusty star-forming galaxies, we simulate their SEDs by accounting for the CMB effect and the radio--IR correlation. The flux density evolution of the UV-bright star-forming galaxies and the dusty star-forming galaxies at the selected observing frequencies covered by the current (ALMA) and next generation (SKA and ngVLA) radio-millimeter telescopes, suggest that massive galaxies (M$_* \gtrsim 10^{10}$M$_{\odot}$) are detectable at any redshift ($0<z<20$) in high frequency ($\nu>90$GHz). In particular, when operating, the ngVLA high-frequency ($\approx 100$ GHz) band is capable of detecting galaxies with M$_* \gtrsim 10^{9}$M$_{\odot}$ almost independently from redshift and the SKA low-frequency observing window ($\lesssim1$ GHz) has sufficient sensitivity to detect M$_* \gtrsim 10^{10}$M$_{\odot}$ dusty star-forming galaxies up to the epoch of reionization ($z=5\sim7$). We also show that the brightness of anomalous microwave emission (AME) in the galaxy SED is insignificant if the galaxies are beyond the local Universe (e.g., $z\gtrsim 0.1$).

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 / 2 minor

Summary. The paper claims that next-generation radio telescopes (SKA and ngVLA) with frequency coverage from ~100 MHz to 100 GHz will enable detailed sampling of galaxy radio-FIR SEDs up to z≈20. Using ensembles of simulated energy-balanced panchromatic SEDs (UV to FIR) extended to radio wavelengths, the authors incorporate CMB effects and the radio-IR correlation to model flux-density evolution for UV star-forming galaxies and dusty star-forming galaxies. They conclude that massive galaxies (M* ≳ 10^10 M⊙) are detectable at any redshift (0<z<20) in high-frequency bands (ν>90 GHz); specifically, ngVLA at ≈100 GHz can detect M* ≳ 10^9 M⊙ galaxies nearly independently of redshift, while SKA at ≲1 GHz has sufficient sensitivity to detect M* ≳ 10^10 M⊙ dusty star-forming galaxies up to z=5–7. The work also finds anomalous microwave emission (AME) to be insignificant for z≳0.1.

Significance. If the underlying extrapolations hold, the forecasts provide useful guidance for survey design with SKA and ngVLA, highlighting how their combined frequency coverage can probe galaxy populations during the epoch of reionization. The approach of extending energy-balanced SED templates with CMB corrections follows standard techniques in the field and offers a broad view across UV-bright and dusty galaxy populations. The explicit statement that AME becomes negligible at modest redshifts is a clear, falsifiable prediction that could be tested with early ngVLA data.

major comments (2)
  1. [Abstract and flux-density evolution results] The central detection thresholds (ngVLA ~100 GHz for M* ≳ 10^9 M⊙ independent of z; SKA ≲1 GHz for M* ≳ 10^10 M⊙ dusty galaxies to z~7) are computed by extending local radio-IR correlations to high redshift while applying only CMB corrections. No sensitivity runs are shown for plausible high-z variations in q_IR, magnetic-field strength, cosmic-ray density, or dust emissivity that would rescale the radio continuum relative to the FIR. Because flux densities are derived directly from these fixed models, even modest deviations at z>5 would shift the minimum detectable stellar mass by factors of several and remove the claimed redshift independence (see abstract and the flux-density evolution results).
  2. [Simulation methodology and results sections] The manuscript states that the radio-IR correlation and energy-balanced SED models are used to generate the predictions, yet it provides no quantitative validation of these templates against existing high-z radio or sub-mm data, nor error propagation on the assumed correlation parameters. This omission is load-bearing for the claimed detection prospects at z=5–7 and beyond.
minor comments (2)
  1. [Abstract] The abstract refers to 'realistic' populations of UV star-forming and dusty star-forming galaxies without specifying the exact stellar-mass functions, star-formation histories, or dust attenuation parameters adopted in the simulations.
  2. [Throughout] Notation for frequency bands is occasionally inconsistent (e.g., 'high frequency (ν>90 GHz)' versus '≈100 GHz'); a single table summarizing the exact frequency windows for ALMA, SKA, and ngVLA would improve clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have prompted us to strengthen the robustness of our forecasts. We agree that the original manuscript would benefit from explicit sensitivity tests and quantitative validation against observations. We have revised the paper accordingly by adding these elements, as explained in the point-by-point responses below.

read point-by-point responses

  1. Referee: [Abstract and flux-density evolution results] The central detection thresholds (ngVLA ~100 GHz for M* ≳ 10^9 M⊙ independent of z; SKA ≲1 GHz for M* ≳ 10^10 M⊙ dusty galaxies to z~7) are computed by extending local radio-IR correlations to high redshift while applying only CMB corrections. No sensitivity runs are shown for plausible high-z variations in q_IR, magnetic-field strength, cosmic-ray density, or dust emissivity that would rescale the radio continuum relative to the FIR. Because flux densities are derived directly from these fixed models, even modest deviations at z>5 would shift the minimum detectable stellar mass by factors of several and remove the claimed redshift independence (see abstract and the flux-density evolution results).

    Authors: We agree that the lack of sensitivity runs to high-redshift variations in the radio-IR correlation parameters is a limitation of the submitted version. In the revised manuscript we have added a dedicated subsection (now Section 4.3) that explores variations in q_IR (±0.2 dex around the local value, consistent with the observed scatter), magnetic-field strength (factor of 2), and cosmic-ray density (factor of 2). These are motivated by theoretical expectations for high-z galaxies. The new analysis shows that while the precise stellar-mass threshold can shift by up to a factor of ~3, the core result—that ngVLA at ~100 GHz detects M* ≳ 10^9 M⊙ galaxies with little redshift dependence—remains valid within the explored range. We have updated the abstract and the flux-density evolution figures to include shaded uncertainty bands reflecting these variations, and we have tempered the language to emphasize that the redshift independence holds under standard assumptions. revision: yes

  2. Referee: [Simulation methodology and results sections] The manuscript states that the radio-IR correlation and energy-balanced SED models are used to generate the predictions, yet it provides no quantitative validation of these templates against existing high-z radio or sub-mm data, nor error propagation on the assumed correlation parameters. This omission is load-bearing for the claimed detection prospects at z=5–7 and beyond.

    Authors: We acknowledge that the original submission lacked direct quantitative validation and error propagation. We have now added a validation subsection (Section 3.2) that compares our simulated radio and sub-mm fluxes against published ALMA and VLA measurements for UV-selected and dusty star-forming galaxies at 2 < z < 6. The models reproduce the observed continuum levels within the 0.2–0.3 dex scatter of the radio-IR correlation. In addition, we have implemented Monte Carlo error propagation by drawing the correlation parameters from their observed distributions and re-running the SED library; the resulting 1σ uncertainty envelopes are now shown as shaded regions in all flux-density evolution plots. These additions directly address the robustness of the z = 5–7 detection forecasts. revision: yes

Circularity Check

0 steps flagged

No significant circularity; detection forecasts follow directly from external radio-IR correlation and SED templates

full rationale

The paper constructs simulated panchromatic SEDs by extending literature energy-balanced models to radio frequencies using the established radio-IR correlation (plus CMB correction), then computes flux densities at SKA/ngVLA bands for given galaxy populations. No equation or step within the manuscript reduces a claimed detection threshold to a parameter fitted inside the paper, nor does any load-bearing premise rest on a self-citation whose validity is defined by the present work. The redshift-independent detectability statements are straightforward numerical consequences of applying fixed external scalings; they are not tautological with the inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central forecasts rest on two standard domain assumptions drawn from local galaxy observations rather than new derivations or data.

axioms (2)
  • domain assumption The radio-IR correlation holds at high redshifts with the same normalization and scatter as locally
    Used to extend the panchromatic SED into the radio regime for all simulated galaxies.
  • domain assumption Energy-balanced UV-to-FIR SED templates remain applicable to galaxies at z up to 20
    Basis for generating the input SEDs before radio extension and CMB correction.

pith-pipeline@v0.9.0 · 5702 in / 1426 out tokens · 44020 ms · 2026-05-09T18:32:51.838284+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

118 extracted references · 114 canonical work pages · 1 internal anchor

  1. [1]

    J., Conselice, C

    Adams, N. J., Conselice, C. J., Ferreira, L., et al. 2023, MNRAS, 518, 4755, doi: 10.1093/mnras/stac3347 Ali-Ha¨ ımoud, Y., Hirata, C. M., & Dickinson, C. 2009, MNRAS, 395, 1055, doi: 10.1111/j.1365-2966.2009.14599.x

    work page doi:10.1093/mnras/stac3347 2023

  2. [2]

    N., et al

    An, F., Vaccari, M., Best, P. N., et al. 2024, MNRAS, 528, 5346, doi: 10.1093/mnras/stae364 Arrabal Haro, P., Dickinson, M., Finkelstein, S. L., et al. 2023, arXiv e-prints, arXiv:2303.15431, doi: 10.48550/arXiv.2303.15431

    work page doi:10.1093/mnras/stae364 2024

  3. [3]

    , keywords =

    Atek, H., Shuntov, M., Furtak, L. J., et al. 2023a, MNRAS, 519, 1201, doi: 10.1093/mnras/stac3144

    work page doi:10.1093/mnras/stac3144

  4. [4]

    2023, MNRAS, 524, 5486, doi: 10.1093/mnras/stad1998

    Atek, H., Chemerynska, I., Wang, B., et al. 2023b, MNRAS, 524, 5486, doi: 10.1093/mnras/stad1998

    work page doi:10.1093/mnras/stad1998

  5. [5]

    Bakx, T. J. L. C., Zavala, J. A., Mitsuhashi, I., et al. 2023, MNRAS, 519, 5076, doi: 10.1093/mnras/stac3723

    work page doi:10.1093/mnras/stac3723 2023

  6. [6]

    Bakx, T. J. L. C., Algera, H. S. B., Jolly, J.-B., et al. 2026, MNRAS, 546, staf2284, doi: 10.1093/mnras/staf2284

    work page doi:10.1093/mnras/staf2284 2026

  7. [7]

    S., Fatigoni, S., Murgia, M., et al

    Battistelli, E. S., Fatigoni, S., Murgia, M., et al. 2019, ApJL, 877, L31, doi: 10.3847/2041-8213/ab21de

    work page doi:10.3847/2041-8213/ab21de 2019

  8. [8]

    2018, MNRAS, 477, 552, doi: 10.1093/mnras/sty552

    Vallini, L. 2018, MNRAS, 477, 552, doi: 10.1093/mnras/sty552

    work page doi:10.1093/mnras/sty552 2018

  9. [9]

    Bell, E. F. 2003, ApJ, 586, 794, doi: 10.1086/367829

    work page doi:10.1086/367829 2003

  10. [10]

    W., & Longair, M

    Blain, A. W., & Longair, M. S. 1993, MNRAS, 264, 509, doi: 10.1093/mnras/264.2.509

    work page doi:10.1093/mnras/264.2.509 1993

  11. [11]

    Frayer, D. T. 2002, PhR, 369, 111, doi: 10.1016/S0370-1573(02)00134-5

    work page doi:10.1016/s0370-1573(02)00134-5 2002

  12. [12]

    2025, A&A, 698, A275, doi: 10.1051/0004-6361/202554194

    Bondi, M., Prandoni, I., Magliocchetti, M., et al. 2025, A&A, 698, A275, doi: 10.1051/0004-6361/202554194

    work page doi:10.1051/0004-6361/202554194 2025

  13. [13]

    CIGALE: a python Code Investigating GALaxy Emission

    Boquien, M., Burgarella, D., Roehlly, Y., et al. 2019, A&A, 622, A103, doi: 10.1051/0004-6361/201834156

    work page Pith review doi:10.1051/0004-6361/201834156 2019

  14. [14]

    Dust attenuation curves at z = 4.4-5.5

    Boquien, M., Buat, V., Burgarella, D., et al. 2022, A&A, 663, A50, doi: 10.1051/0004-6361/202142537

    work page doi:10.1051/0004-6361/202142537 2022

  15. [15]

    2005 , issn =

    Brandenburg, A., & Subramanian, K. 2005, PhR, 417, 1, doi: 10.1016/j.physrep.2005.06.005 22Yoon et al. Mchar(z) 6≤ M<7 7≤ M<8 8≤ M<9 9≤ M<10 10≤ M<11 Figure 10.Each group of four panels shows a 2-D histogram overlaid with the fits to the four physical parameters of the galaxies in each mass bin of the JAGUAR catalog. The orange lines indicate the median v...

    work page doi:10.1016/j.physrep.2005.06.005 2005

  16. [16]

    and Bonaldi, A

    Braun, R., Bonaldi, A., Bourke, T., Keane, E., & Wagg, J. 2019, arXiv e-prints, arXiv:1912.12699, doi: 10.48550/arXiv.1912.12699

    work page doi:10.48550/arxiv.1912.12699 2019

  17. [17]

    and Copin, Y

    Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000, doi: 10.1046/j.1365-8711.2003.06897.x

    work page doi:10.1046/j.1365-8711.2003.06897.x 2003

  18. [18]

    A&A677, 88 (2023) https://doi.org/10.1051/ 0004-6361/202346159 arXiv:2302.07256 [astro-ph.GA]

    Bunker, A. J., Saxena, A., Cameron, A. J., et al. 2023, arXiv e-prints, arXiv:2302.07256, doi: 10.48550/arXiv.2302.07256

    work page doi:10.48550/arxiv.2302.07256 2023

  19. [19]

    Casey, C. M. 2012, MNRAS, 425, 3094, doi: 10.1111/j.1365-2966.2012.21455.x

    work page doi:10.1111/j.1365-2966.2012.21455.x 2012

  20. [20]

    M., Akins, H

    Casey, C. M., Akins, H. B., Shuntov, M., et al. 2023, arXiv e-prints, arXiv:2308.10932, doi: 10.48550/arXiv.2308.10932

    work page doi:10.48550/arxiv.2308.10932 2023

  21. [21]

    2022, ApJL, 938, L15, doi: 10.3847/2041-8213/ac94d0

    Castellano, M., Fontana, A., Treu, T., et al. 2022, ApJL, 938, L15, doi: 10.3847/2041-8213/ac94d0

    work page doi:10.3847/2041-8213/ac94d0 2022

  22. [22]

    2024, ApJ, 972, 143, doi: 10.3847/1538-4357/ad5f88

    Castellano, M., Napolitano, L., Fontana, A., et al. 2024, ApJ, 972, 143, doi: 10.3847/1538-4357/ad5f88

    work page doi:10.3847/1538-4357/ad5f88 2024

  23. [23]

    Galactic

    Chabrier, G. 2003, PASP, 115, 763, doi: 10.1086/376392

    work page Pith review doi:10.1086/376392 2003

  24. [24]

    Charlot, S., & Fall, S. M. 2000, ApJ, 539, 718, doi: 10.1086/309250

    work page Pith review doi:10.1086/309250 2000

  25. [25]

    Sandstrom, K. M. 2025, MNRAS, 537, 1518, doi: 10.1093/mnras/staf118

    work page doi:10.1093/mnras/staf118 2025

  26. [26]

    K., Kondapally, R., Best, P

    Cochrane, R. K., Kondapally, R., Best, P. N., et al. 2023, MNRAS, 523, 6082, doi: 10.1093/mnras/stad1602

    work page doi:10.1093/mnras/stad1602 2023

  27. [27]

    Condon, J. J. 1992, ARA&A, 30, 575, doi: 10.1146/annurev.aa.30.090192.003043

    work page doi:10.1146/annurev.aa.30.090192.003043 1992

  28. [28]

    J., & Yin, Q

    Condon, J. J., & Yin, Q. F. 1990, ApJ, 357, 97, doi: 10.1086/168894

    work page doi:10.1086/168894 1990

  29. [29]

    2026, A&A, 705, A258, doi: 10.1051/0004-6361/202557211 da Cunha, E., Charlot, S., & Elbaz, D

    Correia, L., Bot, C., Chastenet, J., et al. 2026, A&A, 705, A258, doi: 10.1051/0004-6361/202557211 da Cunha, E., Charlot, S., & Elbaz, D. 2008, MNRAS, 388, 1595, doi: 10.1111/j.1365-2966.2008.13535.x da Cunha, E., Groves, B., Walter, F., et al. 2013, ApJ, 766, 13, doi: 10.1088/0004-637X/766/1/13

    work page doi:10.1051/0004-6361/202557211 2026

  30. [30]

    T., et al

    Delvecchio, I., Daddi, E., Sargent, M. T., et al. 2021, A&A, 647, A123, doi: 10.1051/0004-6361/202039647

    work page doi:10.1051/0004-6361/202039647 2021

  31. [31]

    2018, NewAR, 80, 1, doi: 10.1016/j.newar.2018.02.001

    Dickinson, C., Ali-Ha¨ ımoud, Y., Barr, A., et al. 2018, NewAR, 80, 1, doi: 10.1016/j.newar.2018.02.001

    work page doi:10.1016/j.newar.2018.02.001 2018

  32. [32]

    , keywords =

    Donnan, C. T., McLeod, D. J., McLure, R. J., et al. 2023, MNRAS, 520, 4554, doi: 10.1093/mnras/stad471

    work page doi:10.1093/mnras/stad471 2023

  33. [33]

    Draine, B. T. 2011, Physics of the Interstellar and Intergalactic Medium

    2011

  34. [34]

    T., & Lazarian, A

    Draine, B. T., & Lazarian, A. 1998, ApJ, 508, 157, doi: 10.1086/306387

    work page doi:10.1086/306387 1998

  35. [35]

    J., Willott, C., Alberts, S., et al

    Eisenstein, D. J., Willott, C., Alberts, S., et al. 2023, arXiv e-prints, arXiv:2306.02465, doi: 10.48550/arXiv.2306.02465

    work page doi:10.48550/arxiv.2306.02465 2023

  36. [36]

    2025a, A&A, 694, A215, doi: 10.1051/0004-6361/202452368

    Ferrara, A., Carniani, S., di Mascia, F., et al. 2025a, A&A, 694, A215, doi: 10.1051/0004-6361/202452368

    work page doi:10.1051/0004-6361/202452368

  37. [37]

    2025b, A&A, 694, A286, doi: 10.1051/0004-6361/202452707

    Ferrara, A., Pallottini, A., & Sommovigo, L. 2025b, A&A, 694, A286, doi: 10.1051/0004-6361/202452707

    work page doi:10.1051/0004-6361/202452707

  38. [38]

    , keywords =

    Finkelstein, S. L., Bagley, M. B., Arrabal Haro, P., et al. 2022, ApJL, 940, L55, doi: 10.3847/2041-8213/ac966e

    work page doi:10.3847/2041-8213/ac966e 2022

  39. [39]

    , keywords =

    Franco, M., Akins, H. B., Casey, C. M., et al. 2024, ApJ, 973, 23, doi: 10.3847/1538-4357/ad5e6a

    work page doi:10.3847/1538-4357/ad5e6a 2024

  40. [40]

    L., Burgarella, D., et al

    Fujimoto, S., Finkelstein, S. L., Burgarella, D., et al. 2023, ApJ, 955, 130, doi: 10.3847/1538-4357/aceb67

    work page doi:10.3847/1538-4357/aceb67 2023

  41. [41]

    J., Shuntov, M., Atek, H., et al

    Furtak, L. J., Shuntov, M., Atek, H., et al. 2023, MNRAS, 519, 3064, doi: 10.1093/mnras/stac3717

    work page doi:10.1093/mnras/stac3717 2023

  42. [42]

    A., Mac Low, M.-M., Korpi-Lagg, M

    Gent, F. A., Mac Low, M.-M., Korpi-Lagg, M. J., & Singh, N. K. 2023, ApJ, 943, 176, doi: 10.3847/1538-4357/acac20

    work page doi:10.3847/1538-4357/acac20 2023

  43. [43]

    2024, ApJ, 962, 26, doi: 10.3847/1538-4357/ad1519

    Gentile, F., Talia, M., Behiri, M., et al. 2024, ApJ, 962, 26, doi: 10.3847/1538-4357/ad1519

    work page doi:10.3847/1538-4357/ad1519 2024

  44. [44]

    B., Yun, M

    Gim, H. B., Yun, M. S., Owen, F. N., et al. 2019, ApJ, 875, 80, doi: 10.3847/1538-4357/ab1011 Gonz´ alez-L´ opez, J., Novak, M., Decarli, R., et al. 2020, ApJ, 897, 91, doi: 10.3847/1538-4357/ab765b

    work page doi:10.3847/1538-4357/ab1011 2019

  45. [45]

    L., Heywood, I., Jarvis, M

    Hale, C. L., Heywood, I., Jarvis, M. J., et al. 2025, MNRAS, 536, 2187, doi: 10.1093/mnras/stae2528

    work page doi:10.1093/mnras/stae2528 2025

  46. [46]

    Harikane, K

    Harikane, Y., Nakajima, K., Ouchi, M., et al. 2023, arXiv e-prints, arXiv:2304.06658, doi: 10.48550/arXiv.2304.06658

    work page doi:10.48550/arxiv.2304.06658 2023

  47. [47]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

    work page doi:10.1038/s41586-020-2649-2 2020

  48. [48]

    Haskell, P., Smith, D. J. B., Cochrane, R. K., Hayward, C. C., & Angl´ es-Alc´ azar, D. 2023, MNRAS, 525, 1535, doi: 10.1093/mnras/stad2315

    work page doi:10.1093/mnras/stad2315 2023

  49. [49]

    E., Watson, D., Valentino, F., et al

    Heintz, K. E., Watson, D., Valentino, F., et al. 2025, arXiv e-prints, arXiv:2510.07936, doi: 10.48550/arXiv.2510.07936

    work page doi:10.48550/arxiv.2510.07936 2025

  50. [50]

    T., & Rowan-Robinson, M

    Helou, G., Soifer, B. T., & Rowan-Robinson, M. 1985, ApJL, 298, L7, doi: 10.1086/184556

    work page doi:10.1086/184556 1985

  51. [51]

    2015, MNRAS, 449, 809, doi: 10.1093/mnras/stv287

    Hensley, B., Murphy, E., & Staguhn, J. 2015, MNRAS, 449, 809, doi: 10.1093/mnras/stv287

    work page doi:10.1093/mnras/stv287 2015

  52. [52]

    J., Jim´ enez-Andrade, E

    Heywood, I., Murphy, E. J., Jim´ enez-Andrade, E. F., et al. 2021, ApJ, 910, 105, doi: 10.3847/1538-4357/abdf61

    work page doi:10.3847/1538-4357/abdf61 2021

  53. [53]

    Hoang, T., & Tram, L. N. 2019, ApJ, 877, 36, doi: 10.3847/1538-4357/ab1845

    work page doi:10.3847/1538-4357/ab1845 2019

  54. [54]

    N., Lee, H., & Ahn, S.-H

    Hoang, T., Tram, L. N., Lee, H., & Ahn, S.-H. 2019, Nature Astronomy, 3, 766, doi: 10.1038/s41550-019-0763-6

    work page doi:10.1038/s41550-019-0763-6 2019

  55. [55]

    2025, PASA, 42, e071, doi: 10.1017/pasa.2025.10042

    Hopkins, A., Kapinska, A., Marvil, J., et al. 2025, PASA, 42, e071, doi: 10.1017/pasa.2025.10042

    work page doi:10.1017/pasa.2025.10042 2025

  56. [56]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

    work page doi:10.1109/mcse.2007.55 2007

  57. [57]

    Inami, H., Algera, H. S. B., Schouws, S., et al. 2022, MNRAS, 515, 3126, doi: 10.1093/mnras/stac1779

    work page doi:10.1093/mnras/stac1779 2022

  58. [58]

    F., Capozziello, S., & Dainotti, M

    Ivison, R. J., Alexander, D. M., Biggs, A. D., et al. 2010, MNRAS, 402, 245, doi: 10.1111/j.1365-2966.2009.15918.x 24Yoon et al

    work page doi:10.1111/j.1365-2966.2009.15918.x 2010

  59. [59]

    2018, ApJ, 866, 120, doi: 10.3847/1538-4357/aae0fa Jim´ enez-Andrade, E

    Iyer, K., Gawiser, E., Dav´ e, R., et al. 2018, ApJ, 866, 120, doi: 10.3847/1538-4357/aae0fa Jim´ enez-Andrade, E. F., Murphy, E. J., Momjian, E., et al. 2024, ApJ, 972, 89, doi: 10.3847/1538-4357/ad5b5c Jim´ enez-Andrade, E. F., Murphy, E. J., Heywood, I., et al. 2021, ApJ, 910, 106, doi: 10.3847/1538-4357/abe876

    work page doi:10.3847/1538-4357/aae0fa 2018

  60. [60]

    Kazantsev, A. P. 1968, Soviet Journal of Experimental and Theoretical Physics, 26, 1031

    1968

  61. [61]

    and Evans, Neal J

    Kennicutt, R. C., & Evans, N. J. 2012, ARA&A, 50, 531, doi: 10.1146/annurev-astro-081811-125610

    work page internal anchor Pith review doi:10.1146/annurev-astro-081811-125610 2012

  62. [62]

    M., & Anderson, S

    Kulsrud, R. M., & Anderson, S. W. 1992, ApJ, 396, 606, doi: 10.1086/171743

    work page doi:10.1086/171743 1992

  63. [63]

    C., & Thompson, T

    Lacki, B. C., & Thompson, T. A. 2010, ApJ, 717, 196, doi: 10.1088/0004-637X/717/1/196

    work page doi:10.1088/0004-637x/717/1/196 2010

  64. [64]

    A., Aftab, A., Whalen, D

    Latif, M. A., Aftab, A., Whalen, D. J., & Mezcua, M. 2025, A&A, 694, L14, doi: 10.1051/0004-6361/202453194

    work page doi:10.1051/0004-6361/202453194 2025

  65. [65]

    A., & Whalen, D

    Latif, M. A., & Whalen, D. J. 2025, MNRAS, 537, 3448, doi: 10.1093/mnras/staf242

    work page doi:10.1093/mnras/staf242 2025

  66. [66]

    , keywords =

    Leslie, S. K., Schinnerer, E., Liu, D., et al. 2020, ApJ, 899, 58, doi: 10.3847/1538-4357/aba044

    work page doi:10.3847/1538-4357/aba044 2020

  67. [67]

    , keywords =

    Liang, L., Feldmann, R., Kereˇ s, D., et al. 2019, Monthly Notices of the Royal Astronomical Society, 489, 1397, doi: 10.1093/mnras/stz2134

    work page doi:10.1093/mnras/stz2134 2019

  68. [68]

    2019, The Astrophysical Journal Supplement Series, 244, 30, doi: 10.3847/1538-4365/ab4194

    Ma, J., Cooray, A., Nayyeri, H., et al. 2019, The Astrophysical Journal Supplement Series, 244, 30, doi: 10.3847/1538-4365/ab4194

    work page doi:10.3847/1538-4365/ab4194 2019

  69. [69]

    , keywords =

    Markov, V., Gallerani, S., Pallottini, A., et al. 2023, A&A, 679, A12, doi: 10.1051/0004-6361/202346723

    work page doi:10.1051/0004-6361/202346723 2023

  70. [70]

    , keywords =

    Mauch, T., Cotton, W. D., Condon, J. J., et al. 2020, ApJ, 888, 61, doi: 10.3847/1538-4357/ab5d2d

    work page doi:10.3847/1538-4357/ab5d2d 2020

  71. [71]

    & Dayal, P.\ 2023, , 526, 2196

    Mauerhofer, V., & Dayal, P. 2023, MNRAS, 526, 2196, doi: 10.1093/mnras/stad2734

    work page doi:10.1093/mnras/stad2734 2023

  72. [72]

    M., Long, A

    McKinney, J., Casey, C. M., Long, A. S., et al. 2025, ApJ, 979, 229, doi: 10.3847/1538-4357/ada357

    work page doi:10.3847/1538-4357/ada357 2025

  73. [73]

    J., Dunlop, J

    McLure, R. J., Dunlop, J. S., Cullen, F., et al. 2018, MNRAS, 476, 3991, doi: 10.1093/mnras/sty522

    work page doi:10.1093/mnras/sty522 2018

  74. [74]

    E., et al

    Mitsuhashi, I., Harikane, Y., Bauer, F. E., et al. 2024a, ApJ, 971, 161, doi: 10.3847/1538-4357/ad5675

    work page doi:10.3847/1538-4357/ad5675

  75. [75]

    2024b, A&A, 690, A197, doi: 10.1051/0004-6361/202348782

    Mitsuhashi, I., Tadaki, K.-i., Ikeda, R., et al. 2024b, A&A, 690, A197, doi: 10.1051/0004-6361/202348782

    work page doi:10.1051/0004-6361/202348782

  76. [76]

    2024, ApJ, 963, 9, doi: 10.3847/1538-4357/ad1404

    Morishita, T., Stiavelli, M., Chary, R.-R., et al. 2024, ApJ, 963, 9, doi: 10.3847/1538-4357/ad1404

    work page doi:10.3847/1538-4357/ad1404 2024

  77. [77]

    Murphy, E. J. 2009, ApJ, 706, 482, doi: 10.1088/0004-637X/706/1/482

    work page doi:10.1088/0004-637x/706/1/482 2009

  78. [78]

    J., Dong, D., Momjian, E., et al

    Murphy, E. J., Dong, D., Momjian, E., et al. 2018a, ApJS, 234, 24, doi: 10.3847/1538-4365/aa99d7

    work page doi:10.3847/1538-4365/aa99d7

  79. [79]

    J., Linden, S

    Murphy, E. J., Linden, S. T., Dong, D., et al. 2018b, ApJ, 862, 20, doi: 10.3847/1538-4357/aac5f5

    work page doi:10.3847/1538-4357/aac5f5

  80. [80]

    J., Helou, G., Condon, J

    Murphy, E. J., Helou, G., Condon, J. J., et al. 2010, ApJL, 709, L108, doi: 10.1088/2041-8205/709/2/L108

    work page doi:10.1088/2041-8205/709/2/l108 2010

Showing first 80 references.