Pith. sign in

REVIEW 3 major objections 4 minor 1 cited by

JWST IFU observations uncover host galaxy continua in extremely red and obscured quasars

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read JWST integral-field observations recover the host galaxies of extremely red and obscured quasars, showing compact hosts with half-light radii of 1.4-2.9 kpc and stellar masses near $10^{10.6}$-$10^{10.9}$ solar masses.

desk verdict First JWST IFU host continuum measurements for ERQs are a real step forward, but the compact-size and offset claims need a PSF systematics test. read the letter →

arxiv 2506.12124 v1 pith:XOFPQO7J submitted 2025-06-13 astro-ph.GA astro-ph.HE

Yu-Ching Chen , Nadia L. Zakamska , Andrey Vayner , Jack M. M. Neustadt , Dominika Wylezalek , David S. N. Rupke , Sylvain Veilleux , Caroline Bertemes
show 4 more authors
Yuzo Ishikawa Marie Wingyee Lau Weizhe Liu Marshall D. Perrin
This is my paper
classification astro-ph.GAastro-ph.HE
keywords extremelyredquasarsobscuredJWSTNIRSpecintegralfieldunithostgalaxymorphologyPSFsubtractionstellarmassblackholescalingrelations
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

The paper aims to show that the host galaxies of extremely red and obscured quasars can be recovered from JWST integral-field spectroscopy even where the quasar outshines them by a factor of 3 to over 100. Using a wavelength-dependent point-spread function built from dedicated standard-star observations and subtracted with GALFIT, the authors detect extended stellar continua in all eight targets and model their morphologies. They find compact hosts, most with 0.4-1.3 kpc offsets between the quasar and the host centroid, and they extract host spectra for five targets. If correct, this establishes JWST IFU imaging as a way to measure quasar host properties at cosmic noon and sharpens the evidence that these red quasars are a transitional, possibly merger-driven phase.

What carries the argument

The load-bearing mechanism is an empirical, wavelength-dependent PSF model built from dedicated JWST standard-star observations (program 3399, 16 dithers) reduced like the science data, then subtracted from each target cube with GALFIT along the spectral axis. A PSF plus uniform background are fit with free centroid and flux; the residual images, averaged over line-free wavelength ranges, are modeled with a single Sersic profile to get sizes and shapes, and forced photometry at fixed Sersic parameters yields the host spectrum, which pPXF fits with Bruzual and Charlot stellar population templates. This transfers the quasar-host separation from the spectral domain, where continuum and additive polynomials are degenerate, to the spatial domain, where PSF structure is explicitly modeled.

What would settle it

Run injection-recovery tests with the same standard-star PSF: add simulated Sersic hosts of known radius and centering under a scaled quasar PSF at the observed PSF-to-host ratios (3-170), then apply the full GALFIT pipeline; if recovered half-light radii are systematically biased below input by more than roughly 0.3 kpc, or if spurious 0.4-1.3 kpc centroid offsets appear for centered inputs at the observed noise levels, the compact-size and offset claims do not survive.

Watch

Extended reading notes

Core claim

The central discovery is that the stellar continua of the hosts can be cleanly separated from quasar light across a full spectral cube, not just in a single broadband image. For eight targets, the separated light forms a spatially extended galaxy with a measurable Sersic profile; the five reliably measured hosts have stellar masses in the range $10^{10.6}$-$10^{10.9}$ solar masses and the ERQs have half-light radii of 1.4-2.9 kpc. Most quasars are offset from their host centers by 0.4-1.3 kpc, which the authors interpret as dynamical signatures of a post-merger phase or as the effect of uneven dust obscuration. The same measurements place the ERQs 0.5-2 dex above the local black-hole-to-stellar-mass relation, and, compared with earlier HST-based work, they yield more compact hosts, lower Sersic indices, and lower stellar masses.

Load-bearing premise

The results stand or fall on the assumption that the PSF built from dedicated standard-star observations matches the JWST PSF at the position, wavelength, and dither pattern of each science target; if the true PSF is slightly broader or narrower, the compact radii, low Sersic indices, and quasar-host offsets could be fitting artifacts rather than real host properties.

Editorial extensions

If this is right

  • The measured stellar masses place ERQ hosts in dark matter halos of roughly $10^{12}$-$10^{13}$ solar masses, consistent with abundance matching and clustering expectations for quasars at $z\sim1$-$3$.
  • ERQ hosts sit between the size-mass relations of early-type and late-type galaxies, suggesting a star-forming-to-quiescent transition at cosmic noon.
  • The frequent 0.4-1.3 kpc quasar-host offsets, together with tidal features in two targets, support a picture in which obscured quasars are triggered by mergers or hide behind uneven dust.
  • ERQs appear to host over-massive black holes relative to local relations, linking them to HotDOGs and JWST-discovered high-redshift black hole candidates, though selection bias is a viable alternative.
  • JWST IFU decomposition yields systematically more compact hosts and lower stellar masses than HST-based studies, so previous space-based sizes for such quasars may be systematically overestimated.

Reading between the lines

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

  • If the compact sizes survive an independent PSF construction, the factor-of-two size discrepancy between HST and JWST implies that quasar host size measurements at cosmic noon are resolution-limited, and scaling relations built on HST photometry may need revisiting.
  • The quasar-host offsets could be tested directly: a dust-obscuration origin predicts that extinction-corrected, rest-frame infrared centroids should move toward the quasar, while a recoiling or off-center black hole would leave a centroid offset even at long wavelengths.
  • Extending this PSF-subtraction approach to unobscured quasars, where the quasar-to-host contrast is even higher, would test whether the over-massive black hole trend is confined to dusty systems or is a general property of quasar selection.
  • The marginal host detections among several targets mean the method's yield should be checked against a larger, deeper sample before taking the 1.4-2.9 kpc range as the typical size of ERQ hosts.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. This paper presents JWST NIRSpec IFU observations of six extremely red quasars (ERQs) at z=2.4-2.9 and two obscured quasars at z=0.4 and 1.6. The authors develop a PSF-subtraction approach using dedicated standard-star observations (program 3399) to separate quasar and host continuum, fit single-Sersic models to wavelength-averaged PSF-subtracted images, and use forced photometry plus pPXF fits to BC03 templates to derive rest-frame V-band luminosities and stellar masses for five targets. They report compact host half-light radii of 1.4-2.9 kpc, stellar masses of 10^10.6-10^10.9 Msun, 0.4-1.3 kpc quasar-host offsets, and black hole-to-stellar mass ratios of 0.01-0.04, and compare these with abundance-matching expectations, the local MBH-M* relation, and HST-based measurements.

Significance. If the measurements are robust, the paper would be a valuable step: direct host stellar continuum for obscured quasars at cosmic noon, a test of abundance-matching halo-mass expectations for quasar hosts, and a demonstration that JWST IFU image decomposition can recover host light under high PSF-to-host contrast. The paper has real strengths: independent measurement of masses and radii using external calibrations (BC03 templates, Greene-Ho H-alpha relation), explicit propagation of Sersic-model and 0.3 dex mass-to-light systematics into stellar masses, public data release through MAST, and an appropriately hedged discussion of selection bias in the over-massive black hole conclusion. I find no circularity in the abundance-matching comparison; the measured masses do not use halo predictions. However, the central compact-host and offset claims rest on an unvalidated standard-star PSF model at each target position, and the skeptic's concern that PSF mismatch would create compact, low-Sersic, offset residuals is not addressed in the manuscript.

major comments (3)
  1. [§2.4, §3.1] The PSF model built from program 3399 standard-star observations is load-bearing for every result in the paper, yet the manuscript shows no validation that this model reproduces the on-source PSF at each target position and wavelength. The reported offsets are 0.4-1.3 kpc, i.e., roughly 1-3 pixels at the 0.05 arcsec pixel scale against a PSF FWHM of about 0.066 arcsec at 2 um; a small systematic PSF centroid or width error would produce exactly the compact, low-Sersic residuals and shifted host centroids reported here. I request injected-source recovery tests, a split-dither bootstrap of the 16-dither PSF construction, comparison with any unresolved in-field source, and explicit uncertainties on the quasar-host offsets. Without such tests, the compact sizes and offsets cannot be distinguished from PSF artifacts.
  2. [Table 2, Figure 3] Only three targets (J0834+0159, J1232+0912, and J2215-0056) have well-constrained single-Sersic fits, while J0832+1615, J1217+0234, and F2M1106 are flagged in Section 3.1 as poorly constrained, and XID2028 and J1652+1728 are irregular or clumpy. Yet the abstract and Section 4.1 treat compact hosts as a sample-wide result. Moreover, J1232+0912 and J2215-0056 have Sersic indices pinned at the n=0.5 lower limit, and Section 4.1 itself notes that central PSF over-subtraction can bias n low; the "disk-like, low-Sersic" characterization is therefore not supported for these two objects. The comparison with the van der Wel size-mass relations in Figure 5 should be restricted to the reliable subset and should include the systematic effect of the central-pixel mask and PSF residuals on Re and n.
  3. [§4.2, Table 2] The quasar-host offset is a headline finding, but the offsets are not listed in Table 2 and have no reported uncertainties or significance levels. Because the offsets are small relative to the PSF FWHM and the alternative non-uniform dust obscuration explanation is also invoked, the current presentation cannot support the claim of "significant spatial offsets" as a robust result. Please provide the measured offsets with errors for all eight targets, and demonstrate with simulations that offset recovery is unbiased under the actual PSF model.
minor comments (4)
  1. [§3.1] The sentence "With the exception of J1217–0056" appears to refer to J1217+0234; please correct the target name.
  2. [Table 2] The '?' markers for unconstrained fits appear inside the error fields (e.g., '1.1±0.2?'); define the notation clearly in the caption and separate the flag from the value.
  3. [§2.4] The PSF subtraction method is described as 'Chen et al., in prep.', but since the present paper's conclusions depend on it, the key details (PSF construction, dither combination, GALFIT configuration, masking) should be given in an appendix, or the companion paper should be cited with a preprint identifier.
  4. [Figure 5] The caption says 'stellar luminosity' while the text and axes describe stellar mass; please make the wording consistent.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: host masses, radii, and offsets are measured from JWST data with external calibrations; consistency claims are comparisons rather than derivations.

full rationale

I examined the derivation chain for load-bearing reductions of the results to their own inputs. The host morphology measurements (half-light radii, Sersic indices, and quasar-host offsets) come from GALFIT fits to JWST NIRSpec IFU data after subtracting a wavelength-dependent PSF model built from dedicated standard-star observations (Section 2.4). This PSF model is an external calibration; it is not derived from, or fitted to, the target host properties it is used to measure. The quoted compact radii and offsets are therefore empirical outputs, not self-defined quantities. Stellar masses are obtained by fitting Bruzual & Charlot (2003) templates with pPXF to the extracted host spectra (Section 2.6), and black hole masses use the Greene & Ho (2005) virial calibration (Equation 1); neither calibration incorporates the paper's conclusions. The abundance-matching consistency statement in Section 4.1 compares the measured stellar masses to external predictions from clustering and abundance matching and from the Behroozi et al. (2013) stellar-mass-to-halo-mass relation; it does not derive the measured values from those predictions. The comparison to HST-based results (Section 4.4) is a benchmark against independent prior observations, not an input to the fits. Self-citations to Wylezalek et al. (2022), Vayner et al. (2023, 2024), and Zakamska et al. (2019) provide target selection, context, and prior measurements, but none is used to force the central results. The paper itself flags real limitations—residual PSF-subtraction issues, poorly constrained Sersic indices for some targets, marginal detections, and possible central over-subtraction (Sections 2.5, 3.1, 4.1)—but these are empirical systematic uncertainties, not circular logic. The PSF-model accuracy concern raised by the skeptic is a testable technical risk, not a case where the derivation reduces to its inputs. I find no step where a prediction is equivalent by construction to a fitted parameter or where a load-bearing premise is justified only by a self-citation chain.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The central measurements rest on several domain assumptions: the standard-star PSF represents the on-source PSF; host light outside the masked center follows a Sersic profile; BC03 templates describe the stellar populations; and the Greene-Ho calibration gives black hole masses. The main freely fitted values are the Sersic parameters, PSF flux and centroid, and mass-to-light ratios; none of these are derived from independent physical theory, and several are manually chosen (mask sizes, wavelength windows). No invented entities are introduced.

free parameters (6)
  • Sersic index n = 0.5 to 1.6 for reliable fits, many at or near the allowed range 0.5-8
    Fitted by GALFIT on PSF-subtracted images; central to morphology claims and acknowledged to be biased low by PSF over-subtraction (Section 3.1, Table 2).
  • Effective radius Re = 0.7 to 4.9 kpc; central ERQs 1.4-2.9 kpc
    Fitted Sersic scale parameter; the compact host claim depends directly on it (Table 2).
  • Host galaxy AB magnitude = 21.1 to 24.0 in the chosen rest-frame windows
    Fitted in GALFIT and used for luminosity and stellar mass; depends on wavelength windows selected by eye to avoid lines (Table 2, Section 2.5).
  • PSF centroid and flux = per image, not tabulated
    Left free in GALFIT during PSF subtraction; coupling between PSF and host parameters can bias sizes and offsets (Section 2.4).
  • Central pixel exclusion radius = 2 to 4 pixels depending on quasar brightness
    Chosen by hand to avoid PSF undersampling artifacts; directly affects Sersic index and Re (Section 2.5).
  • Mass-to-light ratio M/L_V = 0.51 to 1.68 solar units
    Derived from pPXF fits of BC03 templates; stellar masses scale with M/L, with an added 0.3 dex systematic; no dust reddening component is fit (Table 3, Section 2.6).
assumptions (5)
  • domain assumption The standard-star PSF (program 3399) is representative of the on-source PSF for all science targets, including wavelength dependence and dither sampling.
    Invoked in Section 2.4 to build the wavelength-dependent PSF model used for subtraction; if false, all host continuum measurements are biased.
  • domain assumption The host galaxy light outside the masked central 2-4 pixels is well described by a single Sersic profile with free centroid (or quasar-fixed for J1217+0234).
    Invoked in Section 2.5 for GALFIT modeling; several targets show clumpy or tidal structures that violate this, as noted in Section 3.1.
  • domain assumption The BC03 stellar population synthesis templates, with the chosen metallicities and with no multiplicative or additive polynomial or dust reddening, cover the true stellar populations of the hosts.
    Invoked in Section 2.6 for pPXF fitting; low signal-to-noise means the continuum shape alone must constrain M/L, and no reddening is fit.
  • domain assumption The Greene and Ho (2005) single-epoch H-alpha calibration yields unbiased black hole masses for ERQs at z = 2.4-2.9.
    Used in Section 4.3, Equation 1; single-epoch MBH estimates carry roughly 1 dex scatter, which matters for the over-massive claim.
  • domain assumption A flat Lambda-CDM cosmology with Omega_m=0.3, Omega_Lambda=0.7, H0=70 km/s/Mpc is adopted for physical scales.
    Stated in Section 1; angular to physical scale conversions depend on it.

how reviews work

0 comments
Cite this review

Pith. "Pith review of JWST IFU observations uncover host galaxy continua in extremely red and obscured quasars." pith.science (2026). https://pith.science/paper/XOFPQO7J

@misc{pith2026250612124,
  author       = {Pith},
  title        = {Pith review of: JWST IFU observations uncover host galaxy continua in extremely red and obscured quasars},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XOFPQO7J}},
  note         = {Machine review of arXiv:2506.12124}
}
abstract

Uncovering bright quasars' host galaxies at cosmic noon is challenging because of the high contrast between the quasar and its host and redshifted light, making them primarily visible in the infrared. We present JWST NIRSpec integral field unit (IFU) observations of six extremely red quasars (ERQs) at $z=2.4-2.9$ and two dust-obscured quasars at lower redshifts. Using image decomposition across the spectral range, we successfully separate quasar and host galaxy continuum emission, model host morphologies, and extract spectra. The ERQs and obscured quasars have compact host galaxies with half-light radii of 1.4$-$2.9 kpc and stellar masses of 10$^{10.6-10.9}$ $M_{\odot}$. Their stellar masses are consistent with the average stellar mass of quasar hosts as expected from abundance matching and clustering analysis. Most of the quasars in our sample exhibit significant spatial offsets (0.4$-$1.3 kpc) between the quasar and host galaxy, potentially caused by post-merger dynamics or non-uniform dust obscuration. The ERQs reside 0.5$-$2 dex above the local black hole-stellar mass relation, similar to other heavily obscured populations such as HotDOGs, optically selected quasars at cosmic noon, and high-redshift SMBH candidates identified with JWST. However, this "over-massive" feature might be attributed to selection bias. Compared to HST-based studies, our JWST measurements reveal more compact host galaxies, smaller Sersic indices, and lower stellar masses, likely because of improved resolution, more accurate modeling, and minimal line contamination. These findings highlight the unique capabilities of JWST IFU in revealing quasar host galaxy properties and potential evolutionary stages of obscured quasars at cosmic noon.

Figures

Figures reproduced from arXiv: 2506.12124 by the authors.

Figure 1
Figure 1. Example wavelength-averaged PSF-subtracted images before and after MSA leakage correction. Several bright stripe-like artifacts disappear after the MSA leakage correction. 3-dimensional drizzled data cubes using the standard Spec3 pipeline. We choose drizzle algorithm instead of the Shepard’s method of weighting emsm algorithm to avoid further smoothing along the spectral direc￾tion (Law et al. 2023). The final pixe… view at source ↗
Figure 2
Figure 2. Total spectra and wavelength-average quasar-subtracted images of the eight targets. The left panel of each target shows the total spectrum with shaded regions, which represents the wavelength ranges used for the images. The right two panels show wavelength-average images after PSF subtraction. The green stars represent the quasar locations. The north is up and the east to the left [PITH_FULL_IMAGE:figures/full_fig_… view at source ↗
Figure 3
Figure 3. Two-dimensional host galaxy fitting results. We used GALFIT on wavelength-average PSF-subtracted images to model the host galaxy’s profile. From left to right, the sub-panels display: (a) the wavelength-average PSF-subtracted image, (b) the best-fit Sersic profile, and (c) the corresponding residual image. The green stars mark the quasar positions. The north is up and the east to the left We found that J0832+1615, J… view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: The 1-dimensional host galaxy spectra using the forced photometry with fitted host galaxy model. The black lines are data and the red lines are best-fit lines from pPXF ness of our measurements and the link to these theoret￾ical models in characterizing quasar host gal…
Figure 5
Figure 5. Figure 5: The effective radius as a function of stellar lumi￾nosity for the ERQs in comparison with inactive galaxy sam￾ples (van der Wel et al. 2014). The blue (red) line represents the relation for early-type (late-type) galaxies at z ∼ 2.25. The 1σ errors of the relations are…
Figure 6
Figure 6. Figure 6: The black hole mass - stellar mass relation of the 5 ERQs and obscured quasars in comparison to vari￾ous quasar samples and correlations (Kormendy & Ho 2013; Reines & Volonteri 2015; Bennert et al. 2021; Dong & Wu 2016; Mechtley et al. 2016; Suh et al. 2020; Li et al. …

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Investigating Little Red Dots with UV Excess: Are They the High-Redshift Siblings of Blue Hot DOGs?

    astro-ph.GA 2025-08 conditional novelty 6.0 of 10

    Little Red Dots are not the high-redshift relatives of Blue-excess Hot DOGs; they have less dust obscuration, little hot dust, and likely a different power source.

Reference graph

Works this paper leans on

82 extracted references · 5 canonical work pages · cited by 1 Pith paper

  1. [1]

    J., Eisenhardt, P

    Assef, R. J., Eisenhardt, P. R. M., Stern, D., et al. 2015, ApJ, 804, 27, doi: 10.1088/0004-637X/804/1/27 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Colla...

    doi:10.1088/0004-637x/804/1/27 2015

  2. [2]

    Baggen, J. F. W., van Dokkum, P., Brammer, G., et al. 2024, ApJL, 977, L13, doi: 10.3847/2041-8213/ad90b8

    doi:10.3847/2041-8213/ad90b8 2024

  3. [3]

    C., Blandford, R

    Begelman, M. C., Blandford, R. D., & Rees, M. J. 1980, Nature, 287, 307, doi: 10.1038/287307a0

    doi:10.1038/287307a0 1980

  4. [4]

    S., Wechsler, R

    Behroozi, P. S., Wechsler, R. H., & Conroy, C. 2013, ApJ, 770, 57, doi: 10.1088/0004-637X/770/1/57

    doi:10.1088/0004-637x/770/1/57 2013

  5. [5]

    Malkan, M. A. 2011, ApJ, 726, 59, doi: 10.1088/0004-637X/726/2/59

    doi:10.1088/0004-637x/726/2/59 2011

  6. [6]

    N., Treu, T., Ding, X., et al

    Bennert, V. N., Treu, T., Ding, X., et al. 2021, ApJ, 921, 36, doi: 10.3847/1538-4357/ac151a

    doi:10.3847/1538-4357/ac151a 2021

  7. [7]

    Bertemes, C., Wylezalek, D., Rupke, D. S. N., et al. 2025, A&A, 693, A176, doi: 10.1051/0004-6361/202450451

    doi:10.1051/0004-6361/202450451 2025

  8. [8]

    2008, MNRAS, 390, 1311, doi: 10.1111/j.1365-2966.2008.13790.x B¨ oker, T., Arribas, S., L¨ utzgendorf, N., et al

    Blecha, L., & Loeb, A. 2008, MNRAS, 390, 1311, doi: 10.1111/j.1365-2966.2008.13790.x B¨ oker, T., Arribas, S., L¨ utzgendorf, N., et al. 2022, A&A, 661, A82, doi: 10.1051/0004-6361/202142589

    arXiv 2008

Show all 82 references
  1. [9]

    Brodwin, M., Dey, A., Brown, M. J. I., et al. 2008, ApJL, 687, L65, doi: 10.1086/593327

    2008 doi

  2. [10]

    2018, A&A, 612, A29, doi: 10.1051/0004-6361/201731641

    Brusa, M., Cresci, G., Daddi, E., et al. 2018, A&A, 612, A29, doi: 10.1051/0004-6361/201731641

    2018 doi

  3. [11]

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

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

    2003

  4. [12]

    2024, JWST Calibration Pipeline, 1.14.0, Zenodo, doi: 10.5281/zenodo.6984365

    Bushouse, H., Eisenhamer, J., Dencheva, N., et al. 2024, JWST Calibration Pipeline, 1.14.0, Zenodo, doi: 10.5281/zenodo.6984365

    2024 doi

  5. [13]

    2017, MNRAS, 466, 798, doi: 10.1093/mnras/stw3020 —

    Cappellari, M. 2017, MNRAS, 466, 798, doi: 10.1093/mnras/stw3020 —. 2023, MNRAS, 526, 3273, doi: 10.1093/mnras/stad2597

    2017 doi

  6. [14]

    C., Blain, A., Ibata, R., et al

    Chapman, S. C., Blain, A., Ibata, R., et al. 2009, ApJ, 691, 560, doi: 10.1088/0004-637X/691/1/560

    2009 doi

  7. [15]

    E., & White, M

    Conroy, C., Gunn, J. E., & White, M. 2009, ApJ, 699, 486, doi: 10.1088/0004-637X/699/1/486

    2009 doi

  8. [16]

    2015, ApJ, 799, 82, doi: 10.1088/0004-637X/799/1/82

    Cresci, G., Mainieri, V., Brusa, M., et al. 2015, ApJ, 799, 82, doi: 10.1088/0004-637X/799/1/82

    2015 doi

  9. [17]

    2023, A&A, 672, A128, doi: 10.1051/0004-6361/202346001

    Cresci, G., Tozzi, G., Perna, M., et al. 2023, A&A, 672, A128, doi: 10.1051/0004-6361/202346001

    2023 doi

  10. [18]

    J., Springel, V., White, S

    Croton, D. J., Springel, V., White, S. D. M., et al. 2006, MNRAS, 365, 11, doi: 10.1111/j.1365-2966.2005.09675.x Q3D: Host galaxy13

    2006

  11. [19]

    2018, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Deshpande, A., L¨ utzgendorf, N., Ferruit, P., et al. 2018, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 10698, Space Telescopes and Instrumentation 2018: Optical, Infrared, and Millimeter Wave, ed. M. Lystrup, H. A. MacEwen, G. G

    2018

  12. [20]

    Batalha, N

    Fazio, N. Batalha, N. Siegler, & E. C. Tong, 106985N, doi: 10.1117/12.2312425 Di Matteo, T., Springel, V., & Hernquist, L. 2005, Nature, 433, 604, doi: 10.1038/nature03335

    2005 doi

  13. [21]

    A., Myers, A

    DiPompeo, M. A., Myers, A. D., Hickox, R. C., et al. 2015, MNRAS, 446, 3492, doi: 10.1093/mnras/stu2341

    2015 doi

  14. [22]

    Y., & Wu, X.-B

    Dong, X. Y., & Wu, X.-B. 2016, ApJ, 824, 70, doi: 10.3847/0004-637X/824/2/70

    2016 doi

  15. [23]

    D., White, M., et al

    Eftekharzadeh, S., Myers, A. D., White, M., et al. 2015, MNRAS, 453, 2779, doi: 10.1093/mnras/stv1763

    2015 doi

  16. [24]

    Eisenhardt, P. R. M., Wu, J., Tsai, C.-W., et al. 2012, ApJ, 755, 173, doi: 10.1088/0004-637X/755/2/173

    2012 doi

  17. [25]

    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 Euclid Collaboration, Bisigello, L., Rodighiero, G., et al. 2025, arXiv e-prints, arXiv:2503.15323, doi: 10.48550/arXiv.2503.15323

    2023 doi arXiv

  18. [26]

    Fabian, A. C. 2012, ARA&A, 50, 455, doi: 10.1146/annurev-astro-081811-125521

    2012 doi

  19. [27]

    2016, ApJL, 822, L32, doi: 10.3847/2041-8205/822/2/L32

    Fan, L., Han, Y., Fang, G., et al. 2016, ApJL, 822, L32, doi: 10.3847/2041-8205/822/2/L32

    2016 doi

  20. [28]

    2017, ApJ, 844, 106, doi: 10.3847/1538-4357/aa78f2

    Farrah, D., Petty, S., Connolly, B., et al. 2017, ApJ, 844, 106, doi: 10.3847/1538-4357/aa78f2

    2017 doi

  21. [29]

    L., Bagley, M

    Finkelstein, S. L., Bagley, M. B., Ferguson, H. C., et al. 2023, ApJL, 946, L13, doi: 10.3847/2041-8213/acade4

    2023 doi

  22. [30]

    P., Mather, J

    Gardner, J. P., Mather, J. C., Clampin, M., et al. 2006, SSRv, 123, 485, doi: 10.1007/s11214-006-8315-7

    2006 doi

  23. [31]

    W., & Perrotta, S

    Gillette, J., Hamann, F., Lau, M. W., & Perrotta, S. 2024, MNRAS, 527, 950, doi: 10.1093/mnras/stad2890

    2024 doi

  24. [32]

    2015, ApJ, 806, 218, doi: 10.1088/0004-637X/806/2/218

    Glikman, E., Simmons, B., Mailly, M., et al. 2015, ApJ, 806, 218, doi: 10.1088/0004-637X/806/2/218

    2015 doi

  25. [33]

    E., & Ho, L

    Greene, J. E., & Ho, L. C. 2005, ApJ, 630, 122, doi: 10.1086/431897

    2005 doi

  26. [34]

    E., Labbe, I., Goulding, A

    Greene, J. E., Labbe, I., Goulding, A. D., et al. 2024, ApJ, 964, 39, doi: 10.3847/1538-4357/ad1e5f

    2024 doi

  27. [35]

    L., Ross, N., et al

    Hamann, F., Zakamska, N. L., Ross, N., et al. 2017, MNRAS, 464, 3431, doi: 10.1093/mnras/stw2387

    2017 doi

  28. [36]

    2023, ApJ, 959, 39, doi: 10.3847/1538-4357/ad029e

    Harikane, Y., Zhang, Y., Nakajima, K., et al. 2023, ApJ, 959, 39, doi: 10.3847/1538-4357/ad029e

    2023 doi

  29. [37]

    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

    2020 doi

  30. [38]

    C., Wardlow, J

    Hickox, R. C., Wardlow, J. L., Smail, I., et al. 2012, MNRAS, 421, 284, doi: 10.1111/j.1365-2966.2011.20303.x

    2012

  31. [39]

    F., Hernquist, L., Cox, T

    Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2006, ApJS, 163, 1, doi: 10.1086/499298

    2006 doi

  32. [40]

    F., Hernquist, L., Cox, T

    Hopkins, P. F., Hernquist, L., Cox, T. J., & Kereˇ s, D. 2008, ApJS, 175, 356, doi: 10.1086/524362

    2008 doi

  33. [41]

    2022, A&A, 661, A80, doi: 10.1051/0004-6361/202142663

    Jakobsen, P., Ferruit, P., Alves de Oliveira, C., et al. 2022, A&A, 661, A80, doi: 10.1051/0004-6361/202142663

    2022 doi

  34. [42]

    D., Onoue, M., Inayoshi, K., et al

    Kocevski, D. D., Onoue, M., Inayoshi, K., et al. 2023, ApJL, 954, L4, doi: 10.3847/2041-8213/ace5a0

    2023 doi

  35. [43]

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

    2013 doi

  36. [44]

    W., Perrotta, S., Hamann, F., et al

    Lau, M. W., Perrotta, S., Hamann, F., et al. 2024, MNRAS, 532, 2044, doi: 10.1093/mnras/stae1621

    2024 doi

  37. [45]

    Law, D. R., E. Morrison, J., Argyriou, I., et al. 2023, AJ, 166, 45, doi: 10.3847/1538-3881/acdddc

    2023 doi

  38. [46]

    D., Shen, Y., et al

    Li, J., Silverman, J. D., Shen, Y., et al. 2025, ApJ, 981, 19, doi: 10.3847/1538-4357/ada603

    2025 doi

  39. [47]

    Li, J. I. H., Shen, Y., Ho, L. C., et al. 2021, ApJ, 906, 103, doi: 10.3847/1538-4357/abc8e6

    2021 doi

  40. [48]

    2025, ApJ, 980, 31, doi: 10.3847/1538-4357/ada772

    Liu, W., Veilleux, S., Sankar, S., et al. 2025, ApJ, 980, 31, doi: 10.3847/1538-4357/ada772

    2025 doi

  41. [49]

    2007, PhRvL, 99, 041103, doi: 10.1103/PhysRevLett.99.041103

    Loeb, A. 2007, PhRvL, 99, 041103, doi: 10.1103/PhysRevLett.99.041103

    2007 doi

  42. [50]

    E., Setton, D

    Ma, Y., Greene, J. E., Setton, D. J., et al. 2025, arXiv e-prints, arXiv:2504.08032, doi: 10.48550/arXiv.2504.08032

    2025 doi arXiv

  43. [51]

    2024, A&A, 691, A145, doi: 10.1051/0004-6361/202347640

    Maiolino, R., Scholtz, J., Curtis-Lake, E., et al. 2024, A&A, 691, A145, doi: 10.1051/0004-6361/202347640

    2024 doi

  44. [52]

    J., & Ma, C.-P

    McConnell, N. J., & Ma, C.-P. 2013, ApJ, 764, 184, doi: 10.1088/0004-637X/764/2/184

    2013 doi

  45. [53]

    A., et al

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

    2016 doi

  46. [54]

    Y., Ho, L

    Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2002, AJ, 124, 266, doi: 10.1086/340952 —. 2010, AJ, 139, 2097, doi: 10.1088/0004-6256/139/6/2097

    2002 doi

  47. [55]

    2015, A&A, 574, A82, doi: 10.1051/0004-6361/201425035

    Perna, M., Brusa, M., Cresci, G., et al. 2015, A&A, 574, A82, doi: 10.1051/0004-6361/201425035

    2015 doi

  48. [56]

    L., et al

    Perrotta, S., Hamann, F., Zakamska, N. L., et al. 2019, MNRAS, 488, 4126, doi: 10.1093/mnras/stz1993

    2019 doi

  49. [57]

    Rauscher, B. J. 2024, PASP, 136, 015001, doi: 10.1088/1538-3873/ad1b36

    2024 doi

  50. [58]

    E., & Volonteri, M

    Reines, A. E., & Volonteri, M. 2015, ApJ, 813, 82, doi: 10.1088/0004-637X/813/2/82 Rodr ´ ıguez-Torres, S. A., Comparat, J., Prada, F., et al. 2017, MNRAS, 468, 728, doi: 10.1093/mnras/stx454

    2015 doi

  51. [59]

    P., Hamann, F., Zakamska, N

    Ross, N. P., Hamann, F., Zakamska, N. L., et al. 2015, MNRAS, 453, 3932, doi: 10.1093/mnras/stv1710

    2015 doi

  52. [60]

    2023, q3dfit: PSF decomposition and spectral analysis for JWST-IFU spectroscopy, Astrophysics Source Code Library, record ascl:2310.004 14Chen et al

    Rupke, D., Wylezalek, D., Zakamska, N., et al. 2023, q3dfit: PSF decomposition and spectral analysis for JWST-IFU spectroscopy, Astrophysics Source Code Library, record ascl:2310.004 14Chen et al

    2023

  53. [61]

    Rupke, D. S. N. 2014, IFSFIT: Spectral Fitting for Integral Field Spectrographs. http://ascl.net/1409.005

    2014

  54. [62]

    Rupke, D. S. N., G¨ ultekin, K., & Veilleux, S. 2017, ApJ, 850, 40, doi: 10.3847/1538-4357/aa94d1

    2017 doi

  55. [63]

    Rupke, D. S. N., Schweitzer, M., Viola, V., et al. 2021, QUESTFIT: Fitter for mid-infrared galaxy spectra. http://ascl.net/2112.002

    2021

  56. [64]

    B., Soifer, B

    Sanders, D. B., Soifer, B. T., Elias, J. H., et al. 1988, ApJ, 325, 74, doi: 10.1086/165983

    1988 doi

  57. [65]

    Sersic, J. L. 1968, Atlas de Galaxias Australes

    1968

  58. [66]

    2023, Science Advances, 9, eadg8287, doi: 10.1126/sciadv.adg8287

    Shen, L., Liu, G., He, Z., et al. 2023, Science Advances, 9, eadg8287, doi: 10.1126/sciadv.adg8287

    2023 doi

  59. [67]

    E., Ho, L

    Shen, Y., Greene, J. E., Ho, L. C., et al. 2015, ApJ, 805, 96, doi: 10.1088/0004-637X/805/2/96

    2015 doi

  60. [68]

    Silk, J., & Rees, M. J. 1998, A&A, 331, L1, doi: 10.48550/arXiv.astro-ph/9801013

    1998 doi arXiv

  61. [69]

    2024, MNRAS, 533, 2948, doi: 10.1093/mnras/stae1970

    Stepney, M., Banerji, M., Tang, S., et al. 2024, MNRAS, 533, 2948, doi: 10.1093/mnras/stae1970

    2024 doi

  62. [70]

    2020, ApJ, 889, 32, doi: 10.3847/1538-4357/ab5f5f van der Wel, A., Franx, M., van Dokkum, P

    Suh, H., Civano, F., Trakhtenbrot, B., et al. 2020, ApJ, 889, 32, doi: 10.3847/1538-4357/ab5f5f van der Wel, A., Franx, M., van Dokkum, P. G., et al. 2014, ApJ, 788, 28, doi: 10.1088/0004-637X/788/1/28

    2020 doi

  63. [71]

    L., Riffel, R

    Vayner, A., Zakamska, N. L., Riffel, R. A., et al. 2021, MNRAS, 504, 4445, doi: 10.1093/mnras/stab1176

    2021 doi

  64. [72]

    L., Ishikawa, Y., et al

    Vayner, A., Zakamska, N. L., Ishikawa, Y., et al. 2023, ApJ, 955, 92, doi: 10.3847/1538-4357/ace784 —. 2024, ApJ, 960, 126, doi: 10.3847/1538-4357/ad0be9

    2023 doi

  65. [73]

    2023, ApJ, 953, 56, doi: 10.3847/1538-4357/ace10f

    Veilleux, S., Liu, W., Vayner, A., et al. 2023, ApJ, 953, 56, doi: 10.3847/1538-4357/ace10f

    2023 doi

  66. [74]

    2023, MNRAS, 521, 241, doi: 10.1093/mnras/stad499

    Volonteri, M., Habouzit, M., & Colpi, M. 2023, MNRAS, 521, 241, doi: 10.1093/mnras/stad499

    2023 doi

  67. [75]

    2012, ApJ, 756, 96, doi: 10.1088/0004-637X/756/1/96

    Wu, J., Tsai, C.-W., Sayers, J., et al. 2012, ApJ, 756, 96, doi: 10.1088/0004-637X/756/1/96

    2012 doi

  68. [76]

    2013, ApJ, 769, 79, doi: 10.1088/0004-637X/769/1/79

    Wylezalek, D., Galametz, A., Stern, D., et al. 2013, ApJ, 769, 79, doi: 10.1088/0004-637X/769/1/79

    2013 doi

  69. [77]

    2014, ApJ, 786, 17, doi: 10.1088/0004-637X/786/1/17

    Wylezalek, D., Vernet, J., De Breuck, C., et al. 2014, ApJ, 786, 17, doi: 10.1088/0004-637X/786/1/17

    2014 doi

  70. [78]

    Wylezalek, D., Vayner, A., Rupke, D. S. N., et al. 2022, ApJL, 940, L7, doi: 10.3847/2041-8213/ac98c3

    2022 doi

  71. [79]

    2002, MNRAS, 331, 935, doi: 10.1046/j.1365-8711.2002.05242.x

    Yu, Q. 2002, MNRAS, 331, 935, doi: 10.1046/j.1365-8711.2002.05242.x

    2002

  72. [80]

    L., & Greene, J

    Zakamska, N. L., & Greene, J. E. 2014, MNRAS, 442, 784, doi: 10.1093/mnras/stu842

    2014 doi

  73. [81]

    L., Hamann, F., Pˆ aris, I., et al

    Zakamska, N. L., Hamann, F., Pˆ aris, I., et al. 2016, MNRAS, 459, 3144, doi: 10.1093/mnras/stw718

    2016 doi

  74. [82]

    L., Sun, A.-L., Strauss, M

    Zakamska, N. L., Sun, A.-L., Strauss, M. A., et al. 2019, MNRAS, 489, 497, doi: 10.1093/mnras/stz2071

    2019 doi

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.