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ALMA/SCUBA-2 COSMOS Survey: Properties of X-ray- and SED-selected AGNs in Bright Submillimeter Galaxies

T0 review · 3 major / 4 minor · reviewed 2026-08-11 · deepseek-v4-flash

Pith's one-line read Bright submillimeter galaxies that host active galactic nuclei are about twice as likely as non-AGN ones to be major mergers, implying mergers trigger black hole growth rather than the intense star formation itself.

desk verdict Careful, honest paper whose merger-fraction headline is a ~1.8 sigma trend the abstract overstates; the new AGN catalog and merger classifications still deserve peer review. read the letter →

arxiv 2412.09737 v2 pith:PUCDI7G2 submitted 2024-12-12 astro-ph.GA

classification astro-ph.GA
keywords activegalacticnucleisubmillimetergalaxiesgalaxymergersspectralenergydistributionfittingX-rayobservationsJWSTmorphologyAGNtriggeringCOSMOSfield
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

Using SED modeling of 260 bright submillimeter galaxies (SMGs) in the COSMOS field, supplemented by X-ray data, the paper assembles a sample of 40 AGN hosts and compares their morphologies to non-AGN SMGs. It finds that 47% of AGN hosts are major merger candidates, versus 25% of non-AGN SMGs, with the latter fraction consistent with the general z~2 galaxy population. The paper argues that major mergers are therefore not required for the enhanced star formation in SMGs but play a key role in triggering AGN activity. It also finds that the 17 X-ray-undetected SED-selected AGNs are likely nearly Compton-thick or have suppressed X-ray emission.

What carries the argument

The core method is multi-component SED fitting with CIGALE, using an extended dust-emission model (ethemis) and clumpy torus AGN templates (skirtor). AGN identification is done by comparing the Bayesian Information Criterion of fits with and without an AGN component (DeltaBIC > 10), supplemented by 23 X-ray-detected AGNs from Chandra and X-ray spectral decomposition. The merger classification uses visual inspection of JWST/NIRCam color-composite images, following the approach of Gillman et al. (2024), classifying sources into major/minor/non-mergers based on tidal features, disturbed morphology, and potential companions. The paper combines these results to compare merger fractions between AGN hosts and non-AGN SMGs.

What would settle it

Deep hard X-ray observations above rest-frame 10 keV of the 17 X-ray-undetected SED AGNs: if these sources turn out to be Compton-thin and intrinsically X-ray-weak, the hidden-AGN interpretation and the inferred high obscuration would be disproven, weakening the merger-fraction comparison by removing these sources from the AGN sample.

Watch

Extended reading notes

Core claim

The central claim is that the dichotomy in merger fraction between AGN hosts and non-AGN SMGs points to a specific evolutionary role for mergers. In a sample of 40 AGN-host galaxies drawn from 260 AS2COSMOS SMGs (24 SED-selected, 23 X-ray-selected, with seven overlap), the major-merger fraction is 47+16/-15%, about twice the 25+6/-5% seen in the 65 non-AGN SMGs with JWST coverage. Because the non-AGN fraction matches the general z~2 galaxy population, the paper concludes that major mergers are not the dominant driver of the intense star formation in SMGs, but that they preferentially trigger black hole growth. The authors further argue that the X-ray-undetected SED AGNs, which dominate the AGN sample at high redshift, are likely obscured (nearly Compton-thick) or unusually X-ray-weak, based on X-ray stacking and bolometric correction analysis.

Load-bearing premise

The load-bearing premise is that the SED-based AGN selection reliably identifies true AGNs, particularly the 17 X-ray-undetected SED AGNs, even though the paper itself cautions that five of these candidates show only limited evidence and that high-redshift indicators (24-micron excess or flat FIR SEDs) can be mimicked by starburst PAH or hot dust emission.

Editorial extensions

If this is right

  • If AGN activity in bright SMGs is preferentially triggered by major mergers, then the bright SMG population is not a single homogeneous phase but a mix of merger-driven and secularly star-forming galaxies.
  • The lack of enhancement in the non-AGN merger fraction indicates that intense star formation in SMGs can be sustained without major mergers, aligning with simulations like EAGLE.
  • The X-ray-undetected SED AGNs being near Compton-thick implies that X-ray surveys miss a substantial fraction of AGN activity in the most luminous dusty starbursts, biasing census studies.
  • The AGN number fraction of 16+3/-2% in this bright sample is a lower limit, implying an even higher true AGN fraction once obscured and X-ray-weak sources are included.

Reading between the lines

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

  • If the merger-AGN connection holds, AGN hosts in SMGs may be caught in a post-coalescence transition phase before feedback quenches star formation; a testable expectation is that their central black hole growth is elevated relative to host galaxy growth compared to X-ray-selected AGNs.
  • The 24 SED AGNs have fAGN > 0.3, sitting above the derived detection limit; a direct corollary is that deeper far-IR or mid-IR data at z > 3 should reveal more low-fAGN obscured AGNs, potentially shifting the merger fraction comparison.
  • The visual merger classification relies on apparent companions without redshift confirmation; spectroscopic follow-up of these companions will be decisive, as some may be foreground or background galaxies rather than true merging systems.
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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 studies the 260 bright submillimeter galaxies of the AS2COSMOS survey, combining optical-to-millimeter SED fitting with X-ray spectral analysis to identify AGNs. The authors identify 24 SED-selected AGNs, add 23 X-ray-detected AGNs, and form an overall sample of 40 AGN hosts, of which seven are common to both selections. They then use JWST/NIRCam images to visually classify major-merger candidates and compare the merger fractions of AGN hosts and non-AGN SMGs. The headline result is that about 47% of AGN hosts are major-merger candidates versus about 25% of non-AGN SMGs, which the authors interpret as evidence that major mergers play a key role in triggering AGN activity but are not necessarily required for the enhanced star formation in SMGs.

Significance. If the hidden AGN population and the merger excess are both real, this would be one of the first statistical demonstrations in bright SMGs that mergers preferentially trigger SMBH growth rather than the starburst itself. The paper has real strengths: a well-defined 870-um-selected sample, careful reanalysis of the Chandra data, an X-ray stacking analysis of X-ray-undetected sources, explicit checks against the Donley mid-IR AGN selection and the radio-IR correlation, and a mock-based check of the CIGALE host-galaxy parameters. The authors are also unusually candid about the model dependence of their SED AGN selection. However, the central merger-fraction claim is not currently supported at the quoted significance, and the SED-selected AGN sample is admitted to contain sources with only limited evidence. These issues make the main astrophysical conclusion fragile as it stands.

major comments (3)
  1. [Section 4.6.2, abstract, and Section 5] The quoted major-merger fractions are internally inconsistent and the headline difference is not shown to be statistically significant. Section 4.6.2 reports 50 +/- 15% for AGN hosts and 28 +6/-5% for non-AGN hosts, while the abstract and Section 5 report 47 +16/-15% and 25 +6/-5%. No explanation is given for the difference, and either pair of numbers has 68% confidence intervals that overlap: the AGN lower bound is roughly 32-35% and the non-AGN upper bound is roughly 31-34%. No significance test (Fisher exact test, two-proportion z-test, or bootstrap) is reported anywhere in Section 4.6.2. Given the sample sizes implied by the binomial uncertainties, the 47% versus 25% difference corresponds to p of order 0.05 or larger. I therefore do not think the data establish that major mergers are more common in AGN hosts than in non-AGN SMGs. The authors should either provide a formal significance test with one internally consistent set of numbers, or explicitly downgrade the abstract and summary claims to 'tentative' or 'potentially' throughout.
  2. [Sections 3.1.3, 3.1.5, and 4.6.2] The central merger comparison depends on the reliability of the SED-selected AGN sample, but the paper itself states that the selection is model-dependent and that five SED AGNs (AS2COS0025.1, AS2COS0084.1, AS2COS0099.1, AS2COS0108.2, AS2COS0330.3) have 'fairly limited' evidence. At z >= 3 the AGN indicators can be only a 24-um excess or a flat far-infrared SED, which the authors note can be confused with PAH or hot-dust emission from a starburst. Because the 17 X-ray-undetected SED AGNs are the main hidden-AGN population, contamination by starburst-dominated galaxies would directly change the AGN-host merger fraction and the stated factor-of-two excess. I request a quantitative robustness test: recompute the major-merger fraction after (i) removing the five low-confidence SED AGNs and (ii) using only the X-ray-confirmed AGNs, and state how many of the claimed major-merger hosts belong to each of these subsamples. The Donley-based cross-check in Section 4.6.2 gives 43 +13/-12%, which is reassuring but relies on the same mid-infrared features that are degenerate at z >= 3.
  3. [Section 3.3 and Section 4.6.2] The morphological classification is purely visual, and the paper does not report inter-rater reliability, quantitative morphology metrics, or a stability test with respect to the definition of a major merger. Section 3.3 shows that the full-sample merger fraction changes from 33/105 (31 +/- 5%) to 28/99 (28 +/- 5%) when close pairs are counted once, indicating sensitivity to a small number of objects. In addition, the possible companions are not spectroscopically confirmed, as the paper acknowledges. Since the central claim rests on the difference between the AGN-host and non-AGN-host major-merger fractions, the authors should state how many of the AGN and non-AGN major-merger candidates are in the six close-pair systems, and should show that the AGN/non-AGN difference is stable under alternative definitions (for example, excluding unconfirmed companions or requiring tidal features rather than brightness ratios).
minor comments (4)
  1. [Section 3.1.3] The definition of BIC states that k is the number of degrees of freedom, but in the standard Bayesian Information Criterion k is the number of free parameters in the model. This affects the sentence claiming that the DeltaBIC > 10 threshold corresponds to an improvement in reduced chi-squared of about 1, and should be corrected.
  2. [Sections 3.2.1, 3.2.2, 4.1, and 4.6.1] Several X-ray luminosities are quoted with units of erg s^-1 cm^-2, for example 'L2-10 keV = 2.6 x 10^44 erg s^-1 cm^-2' in Section 3.2.1 and '16 +3/-2 per cent' in Section 4.6.1. Luminosities should be in erg s^-1, while erg s^-1 cm^-2 is the unit of flux; the extraneous cm^-2 appears to be a typo that should be removed throughout.
  3. [Appendix C.2] The text refers to 'AS2COS00159.1' in the discussion of the misidentified counterpart of AS2COS0159.1; the source ID has one extra digit and should read AS2COS0159.1 for consistency with the rest of the paper.
  4. [Section 2.5 and Section 3.3] The paper states that 107/260 AS2COSMOS sources fall within the NIRCam coverage, but Section 3.3 analyzes 105/258 sources after excluding the lensed system AS2COS0005.1/0005.2. The relationship between these numbers is clear, but it would help to state explicitly in Section 3.3 that the sample is 105 sources rather than 107 because two strongly lensed components are excluded, and that the denominator for the merger fractions is therefore 105 (or 99 when pairs are counted once).

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation: the central merger-fraction claim compares independently measured observables (SED/X-ray AGN selection versus JWST visual morphology), so no prediction reduces to its own input by construction.

full rationale

No circular derivation is present. The paper is an observational analysis: AGN selection is made from X-ray spectral fitting and from optical-to-millimeter SED modeling with a BIC threshold, while merger morphology is visually classified from JWST images. These are independent data products, so the merger-fraction comparison does not reduce by construction to the AGN-selection inputs. The SED-derived quantities (fAGN and LSED_AGN,bol) are outputs of one CIGALE fit, but the paper does not use them to predict one another; the X-ray-to-bolometric comparison uses the external empirical relation of Duras et al. (2020), and the X-ray spectral analysis uses the independent xclumpy torus model. The dust-emission model EThemis is cited from the authors' prior work, but it is a model component used for fitting, not an unverified theorem invoked to forbid alternatives; the paper explicitly cautions about model degeneracies and identifies five SED AGNs with limited evidence. The possible overlap of the 68% confidence intervals for the 47% versus 25% major-merger fractions is a statistical-significance concern, not a circularity concern. Under the stated rules, no step can be quoted in which a prediction equals an input by construction, so the circularity score is 0.

Assumptions & free parameters 6 free parameters · 6 assumptions · 0 invented entities

The central claims rest on the SED-based AGN identification and the visual merger classification. The listed free parameters are per-source quantities fitted by CIGALE and XSPEC; they are not hand-tuned constants for a derivation. The axioms are the modeling and observational assumptions the paper relies on, most of which the authors explicitly flag. No new physical entities are introduced.

free parameters (6)
  • fAGN (AGN IR luminosity fraction) = per-source, 0.10-0.90 in Table 1
    Grid parameter in CIGALE; central to SED AGN identification and the fAGN>~0.3 detection limit in Section 3.1.5.
  • L_SED_AGN,bol (bolometric AGN luminosity) = per-source, log10 = 45.22-47.31 erg/s in Table 1
    Derived from SED fit; used to compute X-ray-to-bolometric ratios and infer Compton-thick absorption in Section 4.4.
  • photometric redshift (photo-z) = per-source, range 0.1-6.0, Table 1
    Fitted with CIGALE for sources without secure spectroscopic redshifts; fixed for X-ray spectral analysis and physical property comparisons (Section 3.1.2).
  • log M* (stellar mass) = per-source, Table 1
    Fitted by CIGALE; used to compare host properties and to split merger fractions by stellar mass in Section 4.6.2.
  • log SFR (star formation rate) = per-source, Table 1
    Fitted by CIGALE using 10 Myr averages; used in SFR vs AGN luminosity plot and sample comparisons.
  • N_LOS_H,X (line-of-sight hydrogen column density) = per-source, 21.9-23.9 log cm^-2 in Table 1
    Fitted from X-ray spectra with inclination as free parameter; central to Compton-thin/thick classification of X-ray AGNs in Section 3.2.1.
assumptions (6)
  • domain assumption CIGALE SED templates (BC03 stellar, EThemis dust, SKIRTOR AGN) and the chosen parameter grid represent SMG emission adequately.
    Section 3.1.1; AGN identification and all physical properties depend on these templates; paper acknowledges degeneracies between AGN and host-dust modules.
  • ad hoc to paper DeltaBIC > 10 indicates a real AGN; the number of photometric points and degrees of freedom make this equivalent to a reduced chi2 improvement of about 1.
    Section 3.1.3; threshold adopted from Toba et al. (2020), not independently calibrated; one source is overridden by visual inspection.
  • domain assumption The Duras et al. (2020) empirical LX-to-bolometric relation applies to these bright SMG AGNs, and X-ray undetected SED AGNs have typical AGN spectra with photon index 1.9.
    Section 4.4; used to conclude 14/17 SED AGNs are nearly Compton thick; paper notes the alternative that they are intrinsically X-ray weak.
  • domain assumption Visual classification of JWST NIRCam/F444W images identifies major mergers, with bright companions (within factor of four) being physically associated.
    Section 3.3; companions are not spectroscopically confirmed and the paper warns some may be foreground or background galaxies.
  • domain assumption The AS2COSMOS sample, despite 50% completeness at S850~7.2 mJy and partial NIRCam coverage, yields merger fractions comparable across AGN and non-AGN subsets.
    Sections 2.1 and 4.6.2; no correction for possible coverage or selection bias between subsamples is applied.
  • standard math Flat LCDM cosmology with H0=70.4 km/s/Mpc and Omega_M=0.272.
    Section 1; used to compute luminosities and distances.

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Cite this review

Pith. "Pith review of ALMA/SCUBA-2 COSMOS Survey: Properties of X-ray- and SED-selected AGNs in Bright Submillimeter Galaxies." pith.science (2026). https://pith.science/paper/PUCDI7G2

@misc{pith2026241209737,
  author       = {Pith},
  title        = {Pith review of: ALMA/SCUBA-2 COSMOS Survey: Properties of X-ray- and SED-selected AGNs in Bright Submillimeter Galaxies},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/PUCDI7G2}},
  note         = {Machine review of arXiv:2412.09737}
}
abstract

We investigate the properties of active galactic nuclei (AGNs) in the brightest submillimeter galaxies (SMGs) in the COSMOS field. We utilize the bright sample of ALMA/SCUBA-2 COSMOS Survey (AS2COSMOS), which consists of 260 SMGs with $S_{\mathrm{870}\, \mu \mathrm{m}}=0.7\text{--}19.2\,\mathrm{mJy}$ at $z=0\text{--}6$. We perform optical to millimeter spectral energy distribution (SED) modeling for the whole sample. We identify 24 AGN-host galaxies from the SEDs. Supplemented by 23 X-ray detected AGNs (X-ray AGNs), we construct an overall sample of 40 AGN-host galaxies. The X-ray luminosity upper bounds indicate that the X-ray undetected SED-identified AGNs are likely to be nearly Compton thick or have unusually suppressed X-ray emission. From visual classification, we identify $25^{+6}_{-5}$\% of the SMGs without AGNs as major merger candidates. This fraction is almost consistent with the general galaxy population at $z\sim2$, suggesting that major mergers are not necessarily required for the enhanced star formation in SMGs. We also identify $47^{+16}_{-15}$\% of the AGN hosts as major merger candidates, which is about twice as high as that in the SMGs without AGNs. This suggests that major mergers play a key role in triggering AGN activity in bright SMGs.

Figures

Figures reproduced from arXiv: 2412.09737 by the authors.

Figure 1
Figure 1. Positions of the AS2COSMOS sources. The cyan and red points correspond to the X-ray AGNs and SED AGNs, respectively (see Section 3.1.3 and Section 4.1). The background is the CFHT Ks-band image. The coverage of Hubble Space Telescope (HST)/ACS, JWST/NIRCam, and JWST/MIRI imaging are shown in yellow, orange, and magenta, respectively. sample”). In Section 3.1.1 and Appendix C.2, we show that the original optical coun… view at source ↗
Figure 2
Figure 2. 8 arcsec × 8 arcsec JWST images of the 105 AS2COSMOS sources in the coverage of NIRCam (AS2COS0005.1 and AS2COS0005.2 are excluded). The blue, green, and red colors correspond to the F115W+F150W, F277W, and F444W filters, respectively. We label the merger candidates, which have tidal features (T), disturbed morphology (D) or possible companions (C) (see Section 3.3). The major merger candidates are indicated by “M”.… view at source ↗
Figure 3
Figure 3. Example SEDs of a galaxy fitted (a) without and (b) with AGN templates. The black solid line represents the best-fit template SED solution. The yellow solid line illustrates the stellar emission attenuated by interstellar dust. The blue dashed line depicts the unattenuated stellar emission for reference. The orange line corresponds to the emission from the AGN. The red line shows the infrared emission from interstel… view at source ↗
Figures from the paper (18 more)
Figure 4
Figure 4. Figure 4: Distribution of ∆BIC of the X-ray detected AS2COSMOS sources (X-ray AGN; see Section 4.1), SED AGNs, and all the AS2COSMOS sources. The vertical or￾ange solid lines show the adopted threshold to identify an SED AGN (∆BIC = 10). Most of the X-ray detected sources (16 ou…
Figure 5
Figure 5. Figure 5: (a) Mid-infrared color-color diagram of the AS2COSMOS sources. The shaded area shows the AGN selection criteria by Donley et al. (2012). Note that only the sources that are detected in all the mid-infrared bands (Spitzer 3.6 µm, 4.5 µm, 5.8 µm, and 8.0 µm) are plotted …
Figure 6
Figure 6. Figure 6: Results of X-ray stacking analysis for (a) the X-ray undetected SED AGNs and (b) the other X-ray undetected AS2COSMOS sources. The left panels show the stacked X-ray images, while the right panels show the bootstrap histograms of the net count rates. The mean count rat…
Figure 7
Figure 7. Figure 7: Comparison between far-infrared luminosity (rest-frame 40–120 µm) and X-ray (rest-frame 0.5–8 keV) luminosity for X-ray detected (X-det) SMGs. For the AS2COSMOS sources, we apply a factor of 1/1.91 to convert total infrared luminosity to far-infrared luminosity (Magnel…
Figure 8
Figure 8. Figure 8: (a) Comparison of line-of-sight hydrogen column density measured by X-ray spectral analysis (N LOS H,X ) with that estimated from the dust properties (NH,dust). AS2COS0055.2 and AS2COS246.2 are not plotted in this panel because they are too faint to derive reliable siz…
Figure 9
Figure 9. Figure 9: Histograms of (a) stellar masses, (b) SFRs, (c) specific SFRs, (d) radio-IR correlation factors (qIR), and (e) the dust continuum sizes (Re) for the X-ray AGNs, SED AGNs, and the rest of the AS2COSMOS sources (non-AGNs). In the histogram of Re, the bins at Re = 0 kpc s…
Figure 10
Figure 10. Figure 10: Comparison of X-ray to bolometric correction factor (κ2–10) and bolometric AGN luminosity for (a) the X-ray AGNs and (b) the SED AGNs (the overlapped sources are plotted in panel (a)). The black solid line denotes the empirical relation at z = 0–4 (Duras et al. 2020).…
Figure 11
Figure 11. Figure 11: Comparison of SFR and bolometric AGN luminosity for the X-ray AGNs and the SED AGNs. The orange solid and dashed lines show the “simultaneous evolution” with A = 200 (bulge only) and A = 400 (bulge+disk), respectively. The black solid line shows the detection limit of…
Figure 12
Figure 12. Figure 12: (a) Comparison of the major merger fraction in the AS2COSMOS sample with the theoretical prediction from EAGLE (McAlpine et al. 2019). The errors on M∗ of AS2COSMOS sample indicate the 16–84% intervals of each stellar mass bin. (b) Dependencies of the major merger fra…
Figure 13
Figure 13. Figure 13: 8 arcsec × 8 arcsec JWST images of the 40 AS2COSMOS sources in the coverage of both NIRCam and MIRI imaging. The blue, green, and red colors correspond to the F115W+F150W, F277W+F444W, and F770W filters, respectively. We label the merger candidates, which have tidal f…
Figure 14
Figure 14. Figure 14: (a) Positional offsets between optical sources and X-ray sources used for the astrometry correction. The solid, dotted, and dashed circles encompass 68%, 90%, and 95% of the sources before (red) and after (blue) the correction, respectively. (b) Histogram of the separ…
Figure 15
Figure 15. Figure 15: Positions of the X-ray detected sources near AS2COS0353.1 and AS2COS0353.2 plotted over the Ultravista Ks￾band image. The red points show the X-ray source positions listed in the catalog by Civano et al. (2016), whereas the blue points show the positions derived in ou…
Figure 16
Figure 16. Figure 16: Histogram of the reduced χ 2 for the final fits. The median and the maximum reduced χ 2 are 1.8 and 6.5, respectively. D. CONSISTENCY CHECK OF SED MODELING [PITH_FULL_IMAGE:figures/full_fig_p028_16.png]
Figure 17
Figure 17. Figure 17: Comparison of the physical properties derived by the SED template fitting and the observational properties for the X-ray detected AS2COSMOS sources (X-ray AGN; see Section 4.1), SED AGNs, and the rest of the AS2COSMOS sources (non-AGNs). In panel (a) and (b), the larg…
Figure 18
Figure 18. Figure 18: Comparison of the stellar mass and SFR derived by the SED analysis with those derived from the mock catalog. Most of the sources align well, but AS2COS0285.2 shows a large discrepancy in stellar mass, and AS2COS0175.1 shows large discrepancies in both stellar mass and…
Figure 19
Figure 19. Figure 19: (AS2COS0014.1–AS2COS0353.1) The 0.5–10 keV spectra of the 23 X-ray AGNs. The black points and the black solid lines show the observed spectra and the best-fit models. The red points and the red solid lines show the background spectra and the best-fit models. The blue …
Figure 20
Figure 20. Figure 20: Plots of the goodness of fit as a function of the line-of-sight hydrogen column densities. The vertical axes show the statistical values of the C-statistic. The horizontal axes show the line-of-sight hydrogen column densities in units of 1022 cm−2 . The blue lines sho…
Figure 21
Figure 21. Figure 21: The SEDs and best-fit models of the SED AGNs. The black solid line represents the composite spectrum. The yellow solid line illustrates the stellar emission attenuated by interstellar dust. The blue dashed line depicts the unattenuated stellar emission for a reference…

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Works this paper leans on

140 extracted references · 7 canonical work pages

  1. [1]

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

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

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    /* <q6w]r>`Uː v;+7L FDB !_n 1Jɐ+QC^ B Al q(

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

  4. [4]

    2020, , 249, 3, 10.3847/1538-4365/ab929e

    Ahumada , R., Allende Prieto , C., Almeida , A., et al. 2020, , 249, 3, 10.3847/1538-4365/ab929e

  5. [5]

    2019, , 71, 114, 10.1093/pasj/psz103

    Aihara , H., AlSayyad , Y., Ando , M., et al. 2019, , 71, 114, 10.1093/pasj/psz103

  6. [6]

    2022, , 74, 247, 10.1093/pasj/psab122

    ---. 2022, , 74, 247, 10.1093/pasj/psab122

  7. [7]

    M., Bauer , F

    Alexander , D. M., Bauer , F. E., Chapman , S. C., et al. 2005, , 632, 736, 10.1086/444342

  8. [8]

    M., & Hickox , R

    Alexander , D. M., & Hickox , R. C. 2012, , 56, 93, 10.1016/j.newar.2011.11.003

Show all 140 references
  1. [9]

    Algera , H. S. B., Smail , I., Dudzevi c i \= u t \. e , U., et al. 2020, , 903, 138, 10.3847/1538-4357/abb77b

  2. [10]

    M., Rosario , D., et al

    Andonie , C., Alexander , D. M., Rosario , D., et al. 2022, , 517, 2577, 10.1093/mnras/stac2800

  3. [11]

    M., Greenwell , C., et al

    Andonie , C., Alexander , D. M., Greenwell , C., et al. 2024, , 527, L144, 10.1093/mnrasl/slad144

  4. [12]

    Arnaud , K. A. 1996, in Astronomical Society of the Pacific Conference Series, Vol. 101, Astronomical Data Analysis Software and Systems V, ed. G. H. Jacoby & J. Barnes , 17

  5. [13]

    P., Tollerud , E

    Astropy Collaboration , Robitaille , T. P., Tollerud , E. J., et al. 2013, , 558, A33, 10.1051/0004-6361/201322068

  6. [14]

    M., Sip o cz , B

    Astropy Collaboration , Price-Whelan , A. M., Sip o cz , B. M., et al. 2018, , 156, 123, 10.3847/1538-3881/aabc4f

  7. [15]

    J., Cowie , L

    Barger , A. J., Cowie , L. L., Bauer , F. E., & Gonz \'a lez-L \'o pez , J. 2019, , 887, 23, 10.3847/1538-4357/ab5116

  8. [16]

    J., Cowie , L

    Barger , A. J., Cowie , L. L., Blair , A. H., & Jones , L. H. 2022, , 934, 56, 10.3847/1538-4357/ac67e7

  9. [17]

    E., Weiss , A., Wardlow , J

    Birkin , J. E., Weiss , A., Wardlow , J. L., et al. 2021, , 501, 3926, 10.1093/mnras/staa3862

  10. [18]

    2019, , 622, A103, 10.1051/0004-6361/201834156

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

  11. [19]

    G., Benson , A

    Bower , R. G., Benson , A. J., Malbon , R., et al. 2006, , 370, 645, 10.1111/j.1365-2966.2006.10519.x

  12. [20]

    2003, , 344, 1000, 10.1046/j.1365-8711.2003.06897.x

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

  13. [21]

    C., et al

    Calzetti , D., Armus , L., Bohlin , R. C., et al. 2000, , 533, 682, 10.1086/308692

  14. [22]

    M., Kartaltepe , J

    Casey , C. M., Kartaltepe , J. S., Drakos , N. E., et al. 2023, , 954, 31, 10.3847/1538-4357/acc2bc

  15. [23]

    1979, , 228, 939, 10.1086/156922

    Cash , W. 1979, , 228, 939, 10.1086/156922

  16. [24]

    2003, , 115, 763, 10.1086/376392

    Chabrier , G. 2003, , 115, 763, 10.1086/376392

  17. [25]

    C., Blain , A

    Chapman , S. C., Blain , A. W., Smail , I., & Ivison , R. J. 2005, , 622, 772, 10.1086/428082

  18. [26]

    2022, , 929, 159, 10.3847/1538-4357/ac61df

    Chen , C.-C., Liao , C.-L., Smail , I., et al. 2022, , 929, 159, 10.3847/1538-4357/ac61df

  19. [27]

    Chien , T. C. C., Ling , C.-T., Goto , T., et al. 2024, , 532, 719, 10.1093/mnras/stae1550

  20. [28]

    2016, , 819, 62, 10.3847/0004-637X/819/1/62

    Civano , F., Marchesi , S., Comastri , A., et al. 2016, , 819, 62, 10.3847/0004-637X/819/1/62

  21. [29]

    L., Blanton , M

    Coil , A. L., Blanton , M. R., Burles , S. M., et al. 2011, , 741, 8, 10.1088/0004-637X/741/1/8

  22. [30]

    Condon , J. J. 1992, , 30, 575, 10.1146/annurev.aa.30.090192.003043

  23. [31]

    J., Moustakas , J., Blanton , M

    Cool , R. J., Moustakas , J., Blanton , M. R., et al. 2013, , 767, 118, 10.1088/0004-637X/767/2/118

  24. [32]

    L., Barger , A

    Cowie , L. L., Barger , A. J., Hsu , L. Y., et al. 2017, , 837, 139, 10.3847/1538-4357/aa60bb

  25. [33]

    L., Gonz \'a lez-L \'o pez , J., Barger , A

    Cowie , L. L., Gonz \'a lez-L \'o pez , J., Barger , A. J., et al. 2018, , 865, 106, 10.3847/1538-4357/aadc63

  26. [34]

    J., Geller , M

    Damjanov , I., Zahid , H. J., Geller , M. J., Fabricant , D. G., & Hwang , H. S. 2018, , 234, 21, 10.3847/1538-4365/aaa01c

  27. [35]

    T., et al

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

  28. [36]

    L., Koekemoer , A

    Donley , J. L., Koekemoer , A. M., Brusa , M., et al. 2012, , 748, 142, 10.1088/0004-637X/748/2/142

  29. [37]

    e , U., Smail , I., Swinbank , A

    Dudzevi c i \= u t \. e , U., Smail , I., Swinbank , A. M., et al. 2020, , 494, 3828, 10.1093/mnras/staa769

  30. [38]

    S., Abraham , R

    Dunlop , J. S., Abraham , R. G., Ashby , M. L. N., et al. 2021, PRIMER: Public Release IMaging for Extragalactic Research , JWST Proposal. Cycle 1, ID. \#1837

  31. [39]

    2020, , 636, A73, 10.1051/0004-6361/201936817

    Duras , F., Bongiorno , A., Ricci , F., et al. 2020, , 636, A73, 10.1051/0004-6361/201936817

  32. [40]

    J., McDowell , J

    Elvis , M., Wilkes , B. J., McDowell , J. C., et al. 1994, , 95, 1, 10.1086/192093

  33. [41]

    2009, , 184, 158, 10.1088/0067-0049/184/1/158

    Elvis , M., Civano , F., Vignali , C., et al. 2009, , 184, 158, 10.1088/0067-0049/184/1/158

  34. [42]

    Fabian , A. C. 2012, , 50, 455, 10.1146/annurev-astro-081811-125521

  35. [43]

    C., Allen , G

    Fruscione , A., McDowell , J. C., Allen , G. E., et al. 2006, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 6270, Observatory Operations: Strategies, Processes, and Systems, ed. D. R. Silva & R. E. Doxsey , 62701V, 10.1117/12.671760

  36. [45]

    2018, , 861, 7, 10.3847/1538-4357/aac6c4

    Fujimoto , S., Ouchi , M., Kohno , K., et al. 2018, , 861, 7, 10.3847/1538-4357/aac6c4

  37. [46]

    J., et al

    Gao , F., Wang , L., Pearson , W. J., et al. 2020, , 637, A94, 10.1051/0004-6361/201937178

  38. [47]

    2024, arXiv e-prints, arXiv:2406.03544, 10.48550/arXiv.2406.03544

    Gillman , S., Smail , I., Gullberg , B., et al. 2024, arXiv e-prints, arXiv:2406.03544, 10.48550/arXiv.2406.03544

  39. [48]

    D., Greene , J

    Goulding , A. D., Greene , J. E., Bezanson , R., et al. 2018, , 70, S37, 10.1093/pasj/psx135

  40. [49]

    M., et al

    Gullberg , B., Smail , I., Swinbank , A. M., et al. 2019, , 490, 4956, 10.1093/mnras/stz2835

  41. [50]

    2018, , 858, 77, 10.3847/1538-4357/aabacf

    Hasinger , G., Capak , P., Salvato , M., et al. 2018, , 858, 77, 10.3847/1538-4357/aabacf

  42. [51]

    2018, , 70, 105, 10.1093/pasj/psy104

    Hatsukade , B., Kohno , K., Yamaguchi , Y., et al. 2018, , 70, 105, 10.1093/pasj/psy104

  43. [52]

    C., Narayanan , D., Kere s , D., et al

    Hayward , C. C., Narayanan , D., Kere s , D., et al. 2013, , 428, 2529, 10.1093/mnras/sts222

  44. [53]

    C., & Alexander , D

    Hickox , R. C., & Alexander , D. M. 2018, , 56, 625, 10.1146/annurev-astro-081817-051803

  45. [55]

    A., Karim , A., Smail , I., et al

    Hodge , J. A., Karim , A., Smail , I., et al. 2013, , 768, 91, 10.1088/0004-637X/768/1/91

  46. [56]

    A., Swinbank , A

    Hodge , J. A., Swinbank , A. M., Simpson , J. M., et al. 2016, , 833, 103, 10.3847/1538-4357/833/1/103

  47. [57]

    A., Smail , I., Walter , F., et al

    Hodge , J. A., Smail , I., Walter , F., et al. 2019, , 876, 130, 10.3847/1538-4357/ab1846

  48. [58]

    F., Hernquist , L., Cox , T

    Hopkins , P. F., Hernquist , L., Cox , T. J., & Kere s , D. 2008, , 175, 356, 10.1086/524362

  49. [59]

    2012, , 203, 23, 10.1088/0067-0049/203/2/23

    Hsieh , B.-C., Wang , W.-H., Hsieh , C.-C., et al. 2012, , 203, 23, 10.1088/0067-0049/203/2/23

  50. [60]

    2021, , 913, 6, 10.3847/1538-4357/abf11a

    Hwang , Y.-H., Wang , W.-H., Chang , Y.-Y., et al. 2021, , 913, 6, 10.3847/1538-4357/abf11a

  51. [61]

    J., Best , P

    Ibar , E., Ivison , R. J., Best , P. N., et al. 2010, , 401, L53, 10.1111/j.1745-3933.2009.00786.x

  52. [62]

    J., Biggs , A

    Ibar , E., Ivison , R. J., Biggs , A. D., et al. 2009, , 397, 281, 10.1111/j.1365-2966.2009.14866.x

  53. [63]

    J., Caputi , K

    Ikarashi , S., Ivison , R. J., Caputi , K. I., et al. 2015, , 810, 133, 10.1088/0004-637X/810/2/133

  54. [64]

    I., Ohta , K., et al

    Ikarashi , S., Caputi , K. I., Ohta , K., et al. 2017, , 849, L36, 10.3847/2041-8213/aa9572

  55. [65]

    B., Pope , A., et al

    Iono , D., Peck , A. B., Pope , A., et al. 2006, , 640, L1, 10.1086/503290

  56. [66]

    2018, , 864, 56, 10.3847/1538-4357/aad4af

    Jin , S., Daddi , E., Liu , D., et al. 2018, , 864, 56, 10.3847/1538-4357/aad4af

  57. [67]

    B., Hodge , J., et al

    Jin , S., Sillassen , N. B., Hodge , J., et al. 2024, , 690, L16, 10.1051/0004-6361/202451445

  58. [68]

    P., K \"o hler , M., Ysard , N., Bocchio , M., & Verstraete , L

    Jones , A. P., K \"o hler , M., Ysard , N., Bocchio , M., & Verstraete , L. 2017, , 602, A46, 10.1051/0004-6361/201630225

  59. [69]

    Kalberla , P. M. W., Burton , W. B., Hartmann , D., et al. 2005, , 440, 775, 10.1051/0004-6361:20041864

  60. [70]

    D., Sanders , D., et al

    Kashino , D., Silverman , J. D., Sanders , D., et al. 2019, , 241, 10, 10.3847/1538-4365/ab06c4

  61. [71]

    L., van Dyk , D

    Kashyap , V. L., van Dyk , D. A., Connors , A., et al. 2010, , 719, 900, 10.1088/0004-637X/719/1/900

  62. [72]

    1998, , 498, 541, 10.1086/305588

    Kennicutt , Robert C., J. 1998, , 498, 541, 10.1086/305588

  63. [73]

    D., Faber , S

    Kocevski , D. D., Faber , S. M., Mozena , M., et al. 2012, , 744, 148, 10.1088/0004-637X/744/2/148

  64. [74]

    D., Hasinger , G., Brightman , M., et al

    Kocevski , D. D., Hasinger , G., Brightman , M., et al. 2018, , 236, 48, 10.3847/1538-4365/aab9b4

  65. [75]

    M., Dunkley , J., et al

    Komatsu , E., Smith , K. M., Dunkley , J., et al. 2011, , 192, 18, 10.1088/0067-0049/192/2/18

  66. [76]

    Kormendy , J., & Ho , L. C. 2013, , 51, 511, 10.1146/annurev-astro-082708-101811

  67. [78]

    J., Ilbert , O., et al

    Laigle , C., McCracken , H. J., Ilbert , O., et al. 2016, , 224, 24, 10.3847/0067-0049/224/2/24

  68. [79]

    2023, , 518, 2546, 10.1093/mnras/stac3255

    Laloux , B., Georgakakis , A., Andonie , C., et al. 2023, , 518, 2546, 10.1093/mnras/stac3255

  69. [80]

    2013, , 559, A14, 10.1051/0004-6361/201322179

    Le F \`e vre , O., Cassata , P., Cucciati , O., et al. 2013, , 559, A14, 10.1051/0004-6361/201322179

  70. [81]

    H., Calzetti , D., & Heckman , T

    Leitherer , C., Li , I. H., Calzetti , D., & Heckman , T. M. 2002, , 140, 303, 10.1086/342486

  71. [82]

    2024, , 961, 226, 10.3847/1538-4357/ad148c

    Liao , C.-L., Chen , C.-C., Wang , W.-H., et al. 2024, , 961, 226, 10.3847/1538-4357/ad148c

  72. [83]

    J., Le Brun , V., Maier , C., et al

    Lilly , S. J., Le Brun , V., Maier , C., et al. 2009, , 184, 218, 10.1088/0067-0049/184/2/218

  73. [84]

    2011, , 532, A90, 10.1051/0004-6361/201117107

    Lutz , D., Poglitsch , A., Altieri , B., et al. 2011, , 532, A90, 10.1051/0004-6361/201117107

  74. [85]

    2014, , 52, 415, 10.1146/annurev-astro-081811-125615

    Madau , P., & Dickinson , M. 2014, , 52, 415, 10.1146/annurev-astro-081811-125615

  75. [86]

    2012, , 539, A155, 10.1051/0004-6361/201118312

    Magnelli , B., Lutz , D., Santini , P., et al. 2012, , 539, A155, 10.1051/0004-6361/201118312

  76. [87]

    2019, , 882, 141, 10.3847/1538-4357/ab385b

    Marian , V., Jahnke , K., Mechtley , M., et al. 2019, , 882, 141, 10.3847/1538-4357/ab385b

  77. [88]

    C., Stern , D

    Masters , D. C., Stern , D. K., Cohen , J. G., et al. 2019, , 877, 81, 10.3847/1538-4357/ab184d

  78. [89]

    G., et al

    McAlpine , S., Smail , I., Bower , R. G., et al. 2019, , 488, 2440, 10.1093/mnras/stz1692

  79. [90]

    J., Milvang-Jensen , B., Dunlop , J., et al

    McCracken , H. J., Milvang-Jensen , B., Dunlop , J., et al. 2012, , 544, A156, 10.1051/0004-6361/201219507

  80. [91]

    M., Long , A

    McKinney , J., Casey , C. M., Long , A. S., et al. 2024, arXiv e-prints, arXiv:2408.08346, 10.48550/arXiv.2408.08346

  81. [92]

    A., et al

    Mechtley , M., Jahnke , K., Windhorst , R. A., et al. 2016, , 830, 156, 10.3847/0004-637X/830/2/156

  82. [93]

    2021, , 907, 122, 10.3847/1538-4357/abcc72

    Mitsuhashi , I., Matsuda , Y., Smail , I., et al. 2021, , 907, 122, 10.3847/1538-4357/abcc72

  83. [94]

    E., & C-COSMOS Team

    Miyaji , T., Griffiths , R. E., & C-COSMOS Team . 2008, in AAS/High Energy Astrophysics Division, Vol. 10, AAS/High Energy Astrophysics Division \#10, 4.01

  84. [95]

    G., Brammer , G

    Momcheva , I. G., Brammer , G. B., van Dokkum , P. G., et al. 2016, , 225, 27, 10.3847/0067-0049/225/2/27

  85. [96]

    2013, arXiv e-prints, arXiv:1306.2307, 10.48550/arXiv.1306.2307

    Nandra , K., Barret , D., Barcons , X., et al. 2013, arXiv e-prints, arXiv:1306.2307, 10.48550/arXiv.1306.2307

  86. [97]

    2009, , 507, 1793, 10.1051/0004-6361/200912497

    Noll , S., Burgarella , D., Giovannoli , E., et al. 2009, , 507, 1793, 10.1051/0004-6361/200912497

  87. [98]

    2021, , 906, 84, 10.3847/1538-4357/abccce

    Ogawa , S., Ueda , Y., Tanimoto , A., & Yamada , S. 2021, , 906, 84, 10.3847/1538-4357/abccce

  88. [99]

    2019, , 875, 115, 10.3847/1538-4357/ab0e08

    Ogawa , S., Ueda , Y., Yamada , S., Tanimoto , A., & Kawaguchi , T. 2019, , 875, 115, 10.3847/1538-4357/ab0e08

  89. [100]

    B., & Gunn , J

    Oke , J. B., & Gunn , J. E. 1983, , 266, 713, 10.1086/160817

  90. [101]

    J., Bock , J., Altieri , B., et al

    Oliver , S. J., Bock , J., Altieri , B., et al. 2012, , 424, 1614, 10.1111/j.1365-2966.2012.20912.x

  91. [102]

    2024, , 527, 12044, 10.1093/mnras/stad3916

    Pearson , J., Serjeant , S., Wang , W.-H., et al. 2024, , 527, 12044, 10.1093/mnras/stad3916

  92. [103]

    M., et al

    Pope , A., Chary , R.-R., Alexander , D. M., et al. 2008, , 675, 1171, 10.1086/527030

  93. [104]

    C., Pfeifle , R

    Ricci , C., Privon , G. C., Pfeifle , R. W., et al. 2021, , 506, 5935, 10.1093/mnras/stab2052

  94. [105]

    B., Salvato , M., Aussel , H., et al

    Sanders , D. B., Salvato , M., Aussel , H., et al. 2007, , 172, 86, 10.1086/517885

  95. [106]

    2017, , 468, 2249, 10.1093/mnras/stx626

    Sazonov , S., & Khabibullin , I. 2017, , 468, 2249, 10.1093/mnras/stx626

  96. [107]

    2005, , 437, 861, 10.1051/0004-6361:20042363

    Schartmann , M., Meisenheimer , K., Camenzind , M., Wolf , S., & Henning , T. 2005, , 437, 861, 10.1051/0004-6361:20042363

  97. [108]

    D., Kashino , D., Sanders , D., et al

    Silverman , J. D., Kashino , D., Sanders , D., et al. 2015, , 220, 12, 10.1088/0067-0049/220/1/12

  98. [109]

    M., Smail , I., Swinbank , A

    Simpson , J. M., Smail , I., Swinbank , A. M., et al. 2015, , 799, 81, 10.1088/0004-637X/799/1/81

  99. [110]

    2017, , 839, 58, 10.3847/1538-4357/aa65d0

    ---. 2017, , 839, 58, 10.3847/1538-4357/aa65d0

  100. [111]

    2019, , 880, 43, 10.3847/1538-4357/ab23ff

    ---. 2019, , 880, 43, 10.3847/1538-4357/ab23ff

  101. [112]

    M., Smail , I., Dudzevi c i \= u t \

    Simpson , J. M., Smail , I., Dudzevi c i \= u t \. e , U., et al. 2020, , 495, 3409, 10.1093/mnras/staa1345

  102. [113]

    E., Whitaker , K

    Skelton , R. E., Whitaker , K. E., Momcheva , I. G., et al. 2014, , 214, 24, 10.1088/0067-0049/214/2/24

  103. [114]

    2017, , 602, A1, 10.1051/0004-6361/201628704

    Smol c i \'c , V., Novak , M., Bondi , M., et al. 2017, , 602, A1, 10.1051/0004-6361/201628704

  104. [115]

    M., Smail , I., Swinbank , A

    Stach , S. M., Smail , I., Swinbank , A. M., et al. 2018, , 860, 161, 10.3847/1538-4357/aac5e5

  105. [116]

    M., Dudzevi c i \= u t \

    Stach , S. M., Dudzevi c i \= u t \. e , U., Smail , I., et al. 2019, , 487, 4648, 10.1093/mnras/stz1536

  106. [117]

    Stalevski , M., Fritz , J., Baes , M., Nakos , T., & Popovi \'c , L. C . 2012, , 420, 2756, 10.1111/j.1365-2966.2011.19775.x

  107. [118]

    2016, , 458, 2288, 10.1093/mnras/stw444

    Stalevski , M., Ricci , C., Ueda , Y., et al. 2016, , 458, 2288, 10.1093/mnras/stw444

  108. [119]

    L., Speagle , J

    Steinhardt , C. L., Speagle , J. S., Capak , P., et al. 2014, , 791, L25, 10.1088/2041-8205/791/2/L25

  109. [120]

    P., Gaetz , T

    Suzuki , H., Plucinsky , P. P., Gaetz , T. J., & Bamba , A. 2021, , 655, A116, 10.1051/0004-6361/202141458

  110. [121]

    M., Simpson , J

    Swinbank , A. M., Simpson , J. M., Smail , I., et al. 2014, , 438, 1267, 10.1093/mnras/stt2273

  111. [122]

    J., et al

    Tamura , Y., Iono , D., Wilner , D. J., et al. 2010, , 724, 1270, 10.1088/0004-637X/724/2/1270

  112. [123]

    2019, , 877, 95, 10.3847/1538-4357/ab1b20

    Tanimoto , A., Ueda , Y., Odaka , H., et al. 2019, , 877, 95, 10.3847/1538-4357/ab1b20

  113. [124]

    H., Brandt , W

    Teng , S. H., Brandt , W. N., Harrison , F. A., et al. 2014, , 785, 19, 10.1088/0004-637X/785/1/19

  114. [125]

    2020, , 899, 35, 10.3847/1538-4357/ab9cb7

    Toba , Y., Goto , T., Oi , N., et al. 2020, , 899, 35, 10.3847/1538-4357/ab9cb7

  115. [126]

    2018, , 620, A140, 10.1051/0004-6361/201834105

    Torres-Alb \`a , N., Iwasawa , K., D \' az-Santos , T., et al. 2018, , 620, A140, 10.1051/0004-6361/201834105

  116. [127]

    Ueda , Y., Akiyama , M., Hasinger , G., Miyaji , T., & Watson , M. G. 2014, , 786, 104, 10.1088/0004-637X/786/2/104

  117. [128]

    2003, , 598, 886, 10.1086/378940

    Ueda , Y., Akiyama , M., Ohta , K., & Miyaji , T. 2003, , 598, 886, 10.1086/378940

  118. [129]

    2018, , 853, 24, 10.3847/1538-4357/aa9f10

    Ueda , Y., Hatsukade , B., Kohno , K., et al. 2018, , 853, 24, 10.3847/1538-4357/aa9f10

  119. [130]

    2024, , 965, 108, 10.3847/1538-4357/ad26f7

    Uematsu , R., Ueda , Y., Kohno , K., et al. 2024, , 965, 108, 10.3847/1538-4357/ad26f7

  120. [131]

    2015, , 815, L8, 10.1088/2041-8205/815/1/L8

    Umehata , H., Tamura , Y., Kohno , K., et al. 2015, , 815, L8, 10.1088/2041-8205/815/1/L8

  121. [132]

    2019, Science, 366, 97, 10.1126/science.aaw5949

    Umehata , H., Fumagalli , M., Smail , I., et al. 2019, Science, 366, 97, 10.1126/science.aaw5949

  122. [133]

    2023, The Open Journal of Astrophysics, 6, 34, 10.21105/astro.2309.03276

    Villforth , C. 2023, The Open Journal of Astrophysics, 6, 34, 10.21105/astro.2309.03276

  123. [134]

    X., Brandt , W

    Wang , S. X., Brandt , W. N., Luo , B., et al. 2013, , 778, 179, 10.1088/0004-637X/778/2/179

  124. [135]

    2016, , 828, 56, 10.3847/0004-637X/828/1/56

    Wang , T., Elbaz , D., Daddi , E., et al. 2016, , 828, 56, 10.3847/0004-637X/828/1/56

  125. [136]

    R., Kauffmann , O

    Weaver , J. R., Kauffmann , O. B., Ilbert , O., et al. 2022, , 258, 11, 10.3847/1538-4365/ac3078

  126. [137]

    C., Brinkman , B., Canizares , C., et al

    Weisskopf , M. C., Brinkman , B., Canizares , C., et al. 2002, , 114, 1, 10.1086/338108

  127. [138]

    Willingale , R., Starling , R. L. C., Beardmore , A. P., Tanvir , N. R., & O'Brien , P. T. 2013, , 431, 394, 10.1093/mnras/stt175

  128. [139]

    2021, , 257, 61, 10.3847/1538-4365/ac17f5

    Yamada , S., Ueda , Y., Tanimoto , A., et al. 2021, , 257, 61, 10.3847/1538-4365/ac17f5

  129. [140]

    2020, , 491, 740, 10.1093/mnras/stz3001

    Yang , G., Boquien , M., Buat , V., et al. 2020, , 491, 740, 10.1093/mnras/stz3001

  130. [141]

    N., et al

    Yang , G., Boquien , M., Brandt , W. N., et al. 2022, , 927, 192, 10.3847/1538-4357/ac4971

  131. [142]

    I., Papovich , C., et al

    Yang , G., Caputi , K. I., Papovich , C., et al. 2023, , 950, L5, 10.3847/2041-8213/acd639

  132. [143]

    D., Fazio , G

    Younger , J. D., Fazio , G. G., Wilner , D. J., et al. 2008, , 688, 59, 10.1086/591931

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.