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Optimising the analysis of emission lines in galaxies: the case of the MUSE TIMER galaxy NGC 613

T0 review · 3 major / 7 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read A study of the barred galaxy NGC 613 finds gas streaming inward along the bar's dust lanes and a biconical ionised outflow aligned with the radio jet, with a mass outflow rate near 0.04 solar masses per year.

desk verdict A careful, honest case study with a reusable IFU fitting pipeline: the outflow detection is solid, the inflow claim is plausible but needs a stronger test against non-circular bar orbits. read the letter →

arxiv 2505.14781 v1 pith:R5X36ALM submitted 2025-05-20 astro-ph.GA

Luiz A. Silva-Lima , Dimitri A. Gadotti , Lucimara P. Martins , Tutku Kolcu , Paula R. T. Coelho , Francesca Fragkoudi , Taehyun Kim , Camila de Sá-Freitas
show 6 more authors
Jesús Falcón-Barroso Adriana de Lorenzo-Cáceres Jairo Méndez-Abreu Justus Neumann Miguel Querejeta Patricia Sánchez-Blázquez
This is my paper
classification astro-ph.GA
keywords NGC613barredgalaxiesemission-linefittingintegralfieldspectroscopygasinflowsAGNoutflowsstarformationhistorygalaxyevolution
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 develops a staged analysis pipeline for integral-field spectra—one spectrum per pixel—and uses it on the nearby barred galaxy NGC 613 to separate the many overlapping gas components in its centre. The authors claim that gas is flowing inward along the bar's dust lanes, reaching the nucleus, while a biconical ionised outflow, aligned with the radio jet, carries gas out of the galaxy at about $0.04\,M_\odot\,\mathrm{yr}^{-1}$. If correct, NGC 613 displays both ends of a gas cycle in one system: bar-driven inflow feeding the active nucleus and AGN feedback returning gas to the host. The methods—field-mode normalisation for regularised star-formation-history fits, global optimisation to avoid local minima, and Akaike-information-criterion model selection for the number of Gaussian components—are presented as reusable solutions to common problems in emission-line analysis.

What carries the argument

The load-bearing object is a multi-component Gaussian emission-line model: lines are split into low- and high-ionisation groups, each fitted with up to three Gaussian components whose number is chosen by the Akaike Information Criterion, a model-selection rule that penalises extra free parameters. The fitting uses differential-evolution global optimisation on spatially binned spectra to escape local minima, then refines the solution pixel by pixel with an outlier-filtered radial-basis-function interpolation providing initial guesses. To turn kinematics into astrophysics, the authors subtract a Kinemetry circular-disc model from the gas velocity and overlay the residuals on HST dust-lane contours and VLA radio contours; those residual maps are the evidence for inflow and outflow.

What would settle it

Take the observed stellar mass distribution of NGC 613, including the bar, box/peanut, and nuclear disc, and run a hydrodynamical simulation with no net inflow; if it reproduces the same residual velocity pattern along the dust lanes, the inflow claim is falsified. A cheaper test is to recompute the residual map with the inclination and position angle varied within their published uncertainties and check whether the dust-lane inflow signature survives.

Watch

Extended reading notes

Core claim

The central claim, stated on the paper's own terms, is that the residual velocity field of the ionised gas—after subtracting a best-fitting circular-rotation model built from the stellar kinematics with Kinemetry—shows non-circular motions along both HST-traced bar dust lanes that are directed toward the galaxy centre. The same analysis, applied to a second, broader low-ionisation component and to the high-ionisation [O III] lines, reveals a biconical (two-sided cone) outflow whose blueshifted and redshifted sides bracket the nucleus and align with the VLA radio jet. From the [O III] luminosity, a mean electron density of about $112\,\mathrm{cm}^{-3}$, and the O3N2 oxygen-abundance indicator, the authors derive an ionised outflow mass of $\log_{10} M_{\rm ion}=4.97\,M_\odot$, a bulk timescale of about $2.1\,\mathrm{Myr}$, a mass outflow rate of about $0.04\,M_\odot\,\mathrm{yr}^{-1}$, and a kinetic energy rate of $2.4\times 10^{40}\,\mathrm{erg\,s^{-1}}$, corresponding to about $1.5\%$ of the AGN bolometric luminosity.

Load-bearing premise

The inflow interpretation rests on the assumption that a single rotating stellar disc tilted at $39^\circ$ with one adopted position angle fully accounts for the galaxy's gravitational circular motion, so the leftover gas velocities must be real inward streaming rather than artefacts of the bar's more complex potential or a mis-specified disc orientation.

Editorial extensions

If this is right

  • Bar-driven inflow along dust lanes can deliver gas to the central kiloparsec, providing a direct observational link between bars and nuclear fuel supply.
  • The biconical outflow is consistent with being AGN-powered, since its kinetic power is about $1.5\%$ of the AGN bolometric luminosity.
  • Diagnostics applied to individual Gaussian components reveal ionisation that a single integrated classification would misattribute, so future integral-field studies should separate components before classifying.
  • The field-normalisation and model-selection choices should make star-formation history and gas kinematics recovery more reliable in other nearby galaxies with complex centres.
  • The measured outflow is small but operates on a roughly $2\,\mathrm{Myr}$ timescale, matching a short feedback episode that can affect the central gas reservoir.

Reading between the lines

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

  • Beyond the paper: applying the same residual-velocity method to a sample of barred versus unbarred galaxies would test whether inflow strength scales with bar strength, which a single object cannot establish.
  • Beyond the paper: the apparent low metallicity of the outflow gas could be checked with temperature-sensitive auroral lines; if it survives, it would mean the outflow ejects comparatively metal-poor gas rather than processed nuclear gas.
  • Beyond the paper: the quoted $0.04\,M_\odot\,\mathrm{yr}^{-1}$ counts only ionised gas, so including molecular and neutral phases would probably raise the true mass-loss rate and could change the feedback-efficiency estimate.
  • Beyond the paper: a second-epoch observation of the same field could test whether the biconical outflow geometry is steady or flickering on megayear timescales.
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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 / 7 minor

Summary. This paper presents a detailed analysis pipeline for MUSE TIMER data of the barred galaxy NGC 613, combining full-spectrum stellar fitting with multi-component Gaussian fitting of emission lines, AIC-based model selection, and spatially resolved diagnostics of extinction, ionisation, metallicity, kinematics, and outflows. The two central astrophysical claims are (i) that residual gas velocities relative to a single-disc circular model trace bar-driven inflows along the dust lanes, and (ii) that a biconical [O III] outflow aligned with the VLA radio jet is powered by the AGN, with an ionised outflow mass of log10 M_ion = 4.97 ± 0.01 M_sun and a mass outflow rate of about 0.04 ± 0.01 M_sun/yr. The methodology also includes a regularisation-setting test for SFH recovery and a multi-stage approach to avoid local minima in emission-line fitting. The paper is largely a case study whose central narrative is a complete gas cycle from bar inflow to nuclear feedback.

Significance. If the two claims hold, the paper provides a spatially resolved, multi-phase picture of gas inflow and AGN-driven outflow in a single nearby barred galaxy, and it strengthens the observational case for bar-driven secular feeding. The methodological contribution is also useful: the combination of global differential-evolution optimisation, outlier detection, RBF-based initialisation for spaxel-by-spaxel fitting, and AICc selection is a sensible and moderately novel recipe for multi-component emission-line work, and the scalar-field normalisation test for regularisation is a practical insight. The paper is honest about several caveats, stating that the outflow mass uncertainties are only statistical lower limits and explicitly questioning whether the low metallicity of the outflow is an artifact. However, the inflow claim depends on the residual-velocity zero point being a correct circular-disc model, and the outflow energetics rest on adopted n_e and C values; both are load-bearing assumptions that need more quantitative support before the central claims can be accepted at face value.

major comments (3)
  1. [Section 7.4, Fig. 14] The inflow interpretation is built on the residual map V_L1_gas - V_circ, where V_circ is a Kinemetry model of a single inclined rotating disc with inclination and PA adopted from Buta et al. (2015) and fitted to the stellar velocity field. NGC 613 is strongly barred, has a box/peanut structure and a nuclear disc/ring, and the paper itself notes the nuclear disc and bar-related kinematic features. In such a potential, stellar and gas orbits are not circular, and Kinemetry on the stellar field can absorb part of the bar's non-circularity into a best-fit 'circular' model. The residual pattern along the dust lanes is qualitatively what inflow models produce, but the same pattern could in principle arise from x1/elliptical orbits or projection effects in a non-circular potential. The paper does not quantify how much of the residual amplitude is attributable to the bar distortion or to uncertainties in inclination and PA. Because this residual map is the primary evidence for the paper's signature inflow claim, I ask for a concrete robustness test: for example, a harmonic decomposition of the gas velocity field, a parametric non-circular flow model fitted to the gas kinematics, or at least a variation of i and PA over their published uncertainties and a statement of how the dust-lane residual pattern changes.
  2. [Section 7.5, Eqs. (11)-(13)] The outflow mass and mass outflow rate rest on three adopted quantities: a single average electron density n_e ≈ 112 cm^-3 derived from [S II] in the central kiloparsec, a condensation factor C = 1, and the O3N2-based oxygen abundance. The quoted uncertainty of ±0.01 dex in log10 M_ion is only the statistical propagation and is explicitly acknowledged in the text as a lower limit. However, the paper then presents M_ion ≈ 1e5 M_sun and Mdot_ion ≈ 0.04 M_sun/yr as central values without a systematic error budget. Since [S II] ratios in the field can range from saturation-limited regimes (n_e between roughly 50 and 2000 cm^-3) and C is typically between 0.1 and 1 in ionised outflows, the systematic uncertainty in M_ion is at least an order of magnitude. I request that the authors provide a propagated systematic range for M_ion, Mdot_ion, and E_dot_out, and explicitly state which values of n_e and C would be needed to change the conclusion that the AGN can power the outflow.
  3. [Section 7.3 and 7.5] The metallicity used in Eq. (11) comes from O3N2, and the paper itself notes in Section 7.3 that the apparent metal-poor outflow seen with O3N2 may be an artifact of ionisation-parameter sensitivity; the alternative calibrations shown in Fig. 12 give different abundances in the outflow region, and for some indexes the outflow is outside the calibration range. Since the outflow mass scales as 10^-[O/H], this systematic uncertainty propagates directly into the mass and rate quoted in the abstract. I ask the authors to either recompute the outflow properties using the metallicity range allowed by the various calibrators, or to state clearly which calibrator was used and why, and how the outflow mass would change under the alternative estimates.
minor comments (7)
  1. [Section 4.2] The word 'dissussed' should be 'discussed' in the sentence describing scalar vs field normalisation.
  2. [Section 4.4.4 and Fig. 2] The caption and text use 'scalar field normalisation' for what is elsewhere called 'field normalisation'; please make the terminology consistent (e.g., 'field-mode normalisation').
  3. [Section 5.2] The text contains the typo 'soucers' for 'sources' in the discussion of ionisation sources.
  4. [Figure 11 caption] The caption lists 'emission line-less retired and line-less retired (ELR and ELR, respectively)'; the second should be 'LLR'.
  5. [Section 7.5] The word 'redsifhted' should be 'redshifted' in the description of the counter-outflow.
  6. [Section 5.2/Summary item (ii)] The claim that the multi-component approach is 'tested to be robust against local minima' is not supported by an explicit quantitative test in the text; the outlier-detection procedure is described, but no comparison of recovered chi-squared or parameters against known injected solutions is shown. Please either add such a test or soften the claim.
  7. [Data availability] The data availability statement points to the ESO archive but no link or version is given for the custom fitting pipeline; for a methodology paper, providing a code repository or a clear statement of availability would improve reproducibility.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the inflow/outflow claims rest on independent kinematic and flux measurements with external calibrations.

full rationale

The central claims do not reduce to their own inputs. The outflow mass and rate are computed from the measured [O III] luminosity, the [S II]-derived electron density (n_e ≈ 112 cm^-3, adopted as an average over the central kiloparsec), and the O3N2 oxygen abundance, via Eq. 11 attributed to Carniani et al. (2015); none of these quantities is defined in terms of the outflow conclusion. The bulk velocity, radius, timescale, and mass outflow rate are derived from the gas velocity relative to the stellar velocity, using the definitions in Smethurst et al. (2019, 2021), again external to the paper. The ionization classification uses the BPT and WHAN diagrams with demarcation lines from Kewley et al. (2001), Kauffmann et al. (2003), Schawinski et al. (2007), Cid Fernandes et al. (2011), and Herpich et al. (2016); the paper does not set these boundaries itself. The inflow interpretation is based on the residual map V_L1_gas − V_circ, where V_circ is a Kinemetry model of a circularly rotating disc built from the stellar kinematics, with inclination and position angle adopted from Buta et al. (2015). The residual map is presented as evidence that requires interpretation, not as a quantity fitted to the inflow conclusion; it could be affected by bar streaming or projection effects, but that is a correctness risk, not circularity. Self-citations to TIMER survey papers and to Kolcu et al. (2023) provide the data and the methodological workflow, but the galaxy-specific inflow and outflow claims are not established by those citations; they depend on the MUSE measurements and external calibrations presented in the paper. The regularisation parameter for the star formation history is set by the chi-square criterion of Press et al. (2007), not by requiring a desired SFH shape, so the SFH recovery is not fitted to its own conclusion. No step in the derivation chain is equivalent by construction to its own input, and no uniqueness theorem or ansatz is smuggled in through self-citation.

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

The paper introduces no new physical entities; the outflow, nuclear disc, and bar dust lanes are interpretations of observed structures. The main free parameters are the adopted regularisation, electron density, condensation factor, intrinsic Balmer ratio, and detection thresholds, all of which directly affect the derived SFH, extinction, or outflow properties.

free parameters (5)
  • Regularisation parameter Δ = 0.05
    Chosen via the Press et al. criterion (χ²_reg ≈ χ²_unr + sqrt(2N_pixels)) on a subsampled cube; controls the smoothness of the recovered star formation history and is used across the field (Section 4.4.4).
  • Adopted electron density n_e = 112 cm^-3
    Average of the [S II]-ratio density measurements in the central kiloparsec, adopted for the outflow mass estimate because outskirts measurements are noisy (Section 7.5).
  • Condensation factor C = 1
    Assumed in the outflow mass formula (Carniani et al. 2015); real clumping would lower the derived ionic mass (Section 7.5).
  • Intrinsic Balmer decrement = Hα/Hβ = 2.863
    Assumed case B recombination at T = 10^4 K and n_e = 10^2 cm^-3 for gas extinction estimates; AGN narrow-line regions can have ratios near 3.1 (Section 7.1).
  • AIC detection thresholds = 1σ for low-ionisation lines, 3σ for [O III], plus additional 3σ for line ratios
    Adopted thresholds control how many components are accepted; changing them changes the component maps (Section 5.2).
assumptions (6)
  • domain assumption MUSE LSF can be modelled as a polynomial (Bacon et al. 2017 Eq. 8) and templates degraded accordingly.
    Used in Section 4.3 to prepare SSP templates; mismatch here would bias kinematics.
  • domain assumption pPXF fitting with additive/multiplicative Legendre polynomials recovers unbiased LOSVD and SSP weights.
    Relied upon throughout Sections 4 and 5; the paper follows standard practice.
  • domain assumption Case B recombination gives a homogeneous intrinsic Hα/Hβ = 2.863 over the field.
    Used for gas extinction (Section 7.1); collisions in partially ionised regions can raise the ratio.
  • domain assumption The outflow mass formula (Eq. 11 of Carniani et al. 2015) applies with condensation factor C = 1.
    Section 7.5; clumping and unknown oxygen abundance dominate the uncertainty.
  • domain assumption A single rotating disc model (Kinemetry) with the literature inclination and PA describes the circular stellar motion.
    Section 7.4; residuals from this model are the only evidence for inflows.
  • domain assumption MILES SSP library with BaSTI isochrones and Kroupa IMF covers the stellar populations present.
    Section 4.1; templates below [M/H] = -1 are removed, potentially biasing metal-poor populations.

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Cite this review

Pith. "Pith review of Optimising the analysis of emission lines in galaxies: the case of the MUSE TIMER galaxy NGC 613." pith.science (2026). https://pith.science/paper/R5X36ALM

@misc{pith2026250514781,
  author       = {Pith},
  title        = {Pith review of: Optimising the analysis of emission lines in galaxies: the case of the MUSE TIMER galaxy NGC 613},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/R5X36ALM}},
  note         = {Machine review of arXiv:2505.14781}
}
read the original abstract

Galaxy evolution is driven by spatially distributed processes with varying timescales. Integral field spectroscopy provides spatially-resolved information about these processes. Nevertheless, disentangling these processes, which are related to both the underlying stellar populations and the interstellar medium can be challenging. We present a case study on NGC~613, observed with MUSE (Multi-Unit Spectroscopic Explorer) for the TIMER (Time Inference with MUSE in Extragalactic Rings) project, a local barred galaxy, which shows several gas ionisation mechanisms and is rich in both large and inner-scale stellar structures. We develop a set of steps to overcome fundamental problems in the modelling of emission lines with multiple components, together with the characterisation of the stellar populations. That results in the disentanglement of the gas ionisation mechanisms and kinematics, along with an optimal parametrisation for star formation history recovery. Our analysis reveals evidence of gas inflows, which are associated with the bar dust lanes traced with \textit{Hubble} Space Telescope (HST). In addition, we show the gas kinematics in a central biconical outflow, which is aligned with a radio jet observed with Very Large Array (VLA). The emission line provides estimates of electron density, gas-phase metallicity, and the mass outflow rate, allowing us to distinguish intertwined ionisation mechanisms and to identify a part of the multiphase gas cycle in NGC 613. It traces the gas kinematics from the bar lanes to inner scale gas reservoirs, where it can eventually trigger star formation or AGN activity, as observed in the outflow.

Figures

Figures reproduced from arXiv: 2505.14781 by the authors.

Figure 1
Figure 1. NGC 613. Left: colour composite image from HST observations in the optical. Right: zoom-in region of the left panel, showing the observed field covered by the observations with MUSE. The image is composed with HST observations with the filters F435W, F606W, and F814W. image of NGC 613 is shown in [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Setting the regularisation parameter and the impact of the observation normalisation in the parametrisation. The regularisation is parametrised with regul=1/Δ, where Δ is the regularisation parameter. The maps are colour coded according to the ratio between the 𝜒reg of the fit and the maximum degraded 𝜒unr + Δ𝜒 of a regularised solution, regarding the criterion outlined in Press et al. (2007). Top row: observations … view at source ↗
Figure 3
Figure 3. Obtaining a solution from interpolation and outlier detection. In the upper panels, the radial velocity for a field with tessellation is displayed. The lower panels display the interpolation products by radial basis function. On the right, the data goes through an outlier detection process. The global optimisation may not achieve the minimum in some sparse bins and get stalled in local minima; we try to detect these… view at source ↗
Figures from the paper (12 more)
Figure 4
Figure 4. Figure 4: Application of AIC to observations of NGC 613. Upper left: Application to low-ionisation lines. Lower left: Application to lines with high-ionisation. The maps are shown in shades of grey according to the number of components. The low ionisation group requires one comp…
Figure 5
Figure 5. Figure 5: Stellar kinematics, modelled as moments of Gauss-Hermite se￾ries. Top left: line-of-sight stellar velocity (𝑉★). Top right: stellar velocity dispersion (𝜎★). Bottom left: skewness (ℎ3). Bottom right: kurtosis (ℎ4). location where they were formed. Where the star format…
Figure 6
Figure 6. Figure 6: Average light-weighted stellar properties. The panels show, respectively, the average age (left), [M/H] (middle), and [𝛼/Fe] (right). 20" 0" 20" 0.04 Gyr 0.08 Gyr 0.18 Gyr 0.40 Gyr 20" 0" 20" 20" 0" 20" 0.88 Gyr 20" 0" 20" 1.94 Gyr 20" 0" 20" 4.27 Gyr 20" 0" 20" 9.41 G…
Figure 7
Figure 7. Figure 7: Star formation rate surface density of the recovered SFH (ΣSFR) in 𝑀⊙ yr−1 kpc−2 . The nuclear disc contour (white dashed ellipse in the upper left panel) is shown with the dimensions from Gadotti et al. (2020) in the upper left panel. define the nature of the ionisati…
Figure 8
Figure 8. Figure 8: Modelled flux of the emission lines, including all lines listed in [PITH_FULL_IMAGE:figures/full_fig_p013_8.png]
Figure 9
Figure 9. Figure 9: Colour excess 𝐸 (𝐵− 𝑉) from stellar component and gas. We show the colour excess that was estimated with pPXF (left), and the gas 𝐸 (𝐵 − 𝑉) was obtained from the Balmer decrement (right). The nuclear disc ellipse dimension (white dotted Gadotti et al. 2020) is marked i…
Figure 10
Figure 10. Figure 10: Ionisation mechanism classification with emission line ratios. We present spatially resolved [N ii]/H𝛼 and [O iii]/H𝛽 ratios, as a proxy for the ionisation sequence (top left and top right, respectively). In the bottom row, the BPT diagrams are shown, both colour-code…
Figure 11
Figure 11. Figure 11: WHAN diagram for each emission line component. The left, middle, and right columns employ the results from the first, second and third components, respectively. The WHAN diagrams are shown in the top row. The black dash-dotted lines delimit the regions according to th…
Figure 12
Figure 12. Figure 12: Oxygen abundance in the gas-phase based on calibrated indexes. In the panels (a) and (b), respectively O3N2 (Alloin et al. 1979; Pettini & Pagel 2004) and O3S2 (Curti et al. 2020) are exhibited; (c) shows the gas metallicity from R3, and (d) from RS32, both indexes wi…
Figure 13
Figure 13. Figure 13: Gas kinematics for each component and emission line group. Top row: The LOSV of the gas, for the emission line group of low ionisation potential ( [PITH_FULL_IMAGE:figures/full_fig_p016_13.png]
Figure 14
Figure 14. Figure 14: Bar dust lane contour, gas velocity in relation to stellar, and gas velocity dispersion. In the left-hand panel, the HST colour index from the filters F435W and F814W is shown, with the regions more affected by extinction used as a proxy for the location of the bar du…
Figure 15
Figure 15. Figure 15: Gas kinematics in the secondary component and radio jet in the nucleus of NGC 613. Left panel: HST image with VLA radio contour. Right panel: gas kinematics in the secondary component, overlaid with the VLA contour. resulting in an estimate of 𝑡out ≈ 2.1 ± 0.3 Myr. Ne…

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Forward citations

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Reference graph

Works this paper leans on

178 extracted references · 13 canonical work pages · cited by 1 Pith paper

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    Akaike H., 1974, @doi [IEEE Transactions on Automatic Control] 10.1109/TAC.1974.1100705 , 19, 716

    arXiv 1974

  3. [3]

    Alloin D., Collin-Souffrin S., Joly M., Vigroux L., 1979, , https://ui.adsabs.harvard.edu/abs/1979A&A....78..200A 78, 200

    1979

  4. [4]

    S., Coldwell G., Lambas D

    Alonso M. S., Coldwell G., Lambas D. G., 2013, @doi [ ] 10.1051/0004-6361/201220117 , https://ui.adsabs.harvard.edu/abs/2013A&A...549A.141A 549, A141

    doi:10.1051/0004-6361/201220117 2013

  5. [5]

    G., 2014, @doi [ ] 10.1051/0004-6361/201424523 , https://ui.adsabs.harvard.edu/abs/2014A&A...572A..86A 572, A86

    Alonso S., Coldwell G., Lambas D. G., 2014, @doi [ ] 10.1051/0004-6361/201424523 , https://ui.adsabs.harvard.edu/abs/2014A&A...572A..86A 572, A86

    work page doi:10.1051/0004-6361/201424523 2014

  6. [6]

    G., 2018, @doi [ ] 10.1051/0004-6361/201832796 , https://ui.adsabs.harvard.edu/abs/2018A&A...618A.149A 618, A149

    Alonso S., Coldwell G., Duplancic F., Mesa V., Lambas D. G., 2018, @doi [ ] 10.1051/0004-6361/201832796 , https://ui.adsabs.harvard.edu/abs/2018A&A...618A.149A 618, A149

    doi:10.1051/0004-6361/201832796 2018

  7. [7]

    Alonso S., Vera-Rueda M., Coldwell G., Duplancic F., Mesa V., 2024, @doi [ ] 10.1051/0004-6361/202451533 , https://ui.adsabs.harvard.edu/abs/2024A&A...690A.273A 690, A273

    work page doi:10.1051/0004-6361/202451533 2024

  8. [8]

    Athanassoula E., 1992, @doi [ ] 10.1093/mnras/259.2.345 , https://ui.adsabs.harvard.edu/abs/1992MNRAS.259..345A 259, 345

    doi:10.1093/mnras/259.2.345 1992

Show all 178 references
  1. [9]

    418, Galactic Bulges

    Athanassoula E., 2016, in Laurikainen E., Peletier R., Gadotti D., eds, Astrophysics and Space Science Library Vol. 418, Galactic Bulges. p. 391 ( @eprint arXiv 1503.04804 ), @doi 10.1007/978-3-319-19378-6_14

    2016 arXiv

  2. [10]

    Athanassoula E., Laurikainen E., Salo H., Bosma A., 2015, @doi [ ] 10.1093/mnras/stv2231 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.454.3843A 454, 3843

    2015 doi

  3. [11]

    Audibert A., et al., 2019, @doi [ ] 10.1051/0004-6361/201935845 , https://ui.adsabs.harvard.edu/abs/2019A&A...632A..33A 632, A33

    2019 doi

  4. [12]

    S., Ramsay S

    Bacon R., et al., 2010, in McLean I. S., Ramsay S. K., Takami H., eds, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 7735, Ground-based and Airborne Instrumentation for Astronomy III. p. 773508 ( @eprint arXiv 2211.16795 ), @doi 10.1117/12.856027

    2010 arXiv

  5. [13]

    Bacon R., et al., 2017, @doi [ ] 10.1051/0004-6361/201730833 , https://ui.adsabs.harvard.edu/abs/2017A&A...608A...1B 608, A1

    2017 doi

  6. [14]

    A., Phillips M

    Baldwin J. A., Phillips M. M., Terlevich R., 1981, @doi [ ] 10.1086/130766 , https://ui.adsabs.harvard.edu/abs/1981PASP...93....5B 93, 5

    1981 doi

  7. [15]

    Belfiore F., et al., 2019, @doi [ ] 10.3847/1538-3881/ab3e4e , https://ui.adsabs.harvard.edu/abs/2019AJ....158..160B 158, 160

    2019 doi

  8. [16]

    H., 2007, @doi [ ] 10.1086/520531 , https://ui.adsabs.harvard.edu/abs/2007ApJ...666..189B 666, 189

    Berentzen I., Shlosman I., Martinez-Valpuesta I., Heller C. H., 2007, @doi [ ] 10.1086/520531 , https://ui.adsabs.harvard.edu/abs/2007ApJ...666..189B 666, 189

    2007 doi

  9. [17]

    Bianchin M., et al., 2022, @doi [ ] 10.1093/mnras/stab3468 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.510..639B 510, 639

    2022 doi

  10. [18]

    Bidaran B., et al., 2020, @doi [ ] 10.1093/mnras/staa2097 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497.1904B 497, 1904

    2020 doi

  11. [19]

    G., Stasi \'n ska G., Bruzual A

    Binette L., Magris C. G., Stasi \'n ska G., Bruzual A. G., 1994, , https://ui.adsabs.harvard.edu/abs/1994A&A...292...13B 292, 13

    1994

  12. [20]

    Bittner A., et al., 2019, @doi [ ] 10.1051/0004-6361/201935829 , https://ui.adsabs.harvard.edu/abs/2019A&A...628A.117B 628, A117

    2019 doi

  13. [21]

    Bittner A., et al., 2020, @doi [ ] 10.1051/0004-6361/202038450 , https://ui.adsabs.harvard.edu/abs/2020A&A...643A..65B 643, A65

    2020 doi

  14. [22]

    Bittner A., et al., 2021, @doi [ ] 10.1051/0004-6361/202039505 , https://ui.adsabs.harvard.edu/abs/2021A&A...646A..42B 646, A42

    2021 doi

  15. [23]

    H., Ryder S., 2008, @doi [ ] 10.1088/0004-6256/135/2/479 , https://ui.adsabs.harvard.edu/abs/2008AJ....135..479B 135, 479

    B \"o ker T., Falc \'o n-Barroso J., Schinnerer E., Knapen J. H., Ryder S., 2008, @doi [ ] 10.1088/0004-6256/135/2/479 , https://ui.adsabs.harvard.edu/abs/2008AJ....135..479B 135, 479

    2008 doi

  16. [24]

    A., Wilson A

    Braatz J. A., Wilson A. S., Henkel C., 1996, @doi [ ] 10.1086/192328 , https://ui.adsabs.harvard.edu/abs/1996ApJS..106...51B 106, 51

    1996 doi

  17. [25]

    P., Anderson D

    Burnham K. P., Anderson D. R., eds, 2004, Model Selection and Multimodel Inference . Springer, New York, NY, @doi 10.1007/b97636 , http://link.springer.com/10.1007/b97636

    2004 doi

  18. [26]

    J., et al., 2015, @doi [ ] 10.1088/0067-0049/217/2/32 , https://ui.adsabs.harvard.edu/abs/2015ApJS..217...32B 217, 32

    Buta R. J., et al., 2015, @doi [ ] 10.1088/0067-0049/217/2/32 , https://ui.adsabs.harvard.edu/abs/2015ApJS..217...32B 217, 32

    2015 doi

  19. [27]

    C., Kinney A

    Calzetti D., Armus L., Bohlin R. C., Kinney A. L., Koornneef J., Storchi-Bergmann T., 2000, @doi [ ] 10.1086/308692 , https://ui.adsabs.harvard.edu/abs/2000ApJ...533..682C 533, 682

    2000 doi

  20. [28]

    Cano-D \' az M., Maiolino R., Marconi A., Netzer H., Shemmer O., Cresci G., 2012, @doi [ ] 10.1051/0004-6361/201118358 , https://ui.adsabs.harvard.edu/abs/2012A&A...537L...8C 537, L8

    2012 doi

  21. [29]

    Cappellari M., 2017, @doi [ ] 10.1093/mnras/stw3020 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.466..798C 466, 798

    2017 doi

  22. [30]

    Cappellari M., 2023, @doi [ ] 10.1093/mnras/stad2597 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.526.3273C 526, 3273

    2023 doi

  23. [31]

    Cappellari M., Copin Y., 2003, @doi [ ] 10.1046/j.1365-8711.2003.06541.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.342..345C 342, 345

    2003

  24. [32]

    Cappellari M., Emsellem E., 2004, @doi [ ] 10.1086/381875 , https://ui.adsabs.harvard.edu/abs/2004PASP..116..138C 116, 138

    2004 doi

  25. [34]

    A., Clayton G

    Cardelli J. A., Clayton G. C., Mathis J. S., 1989, @doi [ ] 10.1086/167900 , https://ui.adsabs.harvard.edu/abs/1989ApJ...345..245C 345, 245

    1989 doi

  26. [35]

    Carniani S., et al., 2015, @doi [ ] 10.1051/0004-6361/201526557 , https://ui.adsabs.harvard.edu/abs/2015A&A...580A.102C 580, A102

    2015 doi

  27. [36]

    F., Blanc G., Weinzirl T., Song M., Luo R., 2020, @doi [ ] 10.1093/mnras/staa397 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.4094C 493, 4094

    Carrillo A., Jogee S., Drory N., Kaplan K. F., Blanc G., Weinzirl T., Song M., Luo R., 2020, @doi [ ] 10.1093/mnras/staa397 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.4094C 493, 4094

    2020 doi

  28. [37]

    M., 2008, @doi [ ] 10.1051/0004-6361:20078316 , https://ui.adsabs.harvard.edu/abs/2008A&A...479..111C 479, 111

    Castangia P., Tarchi A., Henkel C., Menten K. M., 2008, @doi [ ] 10.1051/0004-6361:20078316 , https://ui.adsabs.harvard.edu/abs/2008A&A...479..111C 479, 111

    2008 doi

  29. [38]

    Castangia P., Panessa F., Henkel C., Kadler M., Tarchi A., 2013, @doi [ ] 10.1093/mnras/stt1824 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.436.3388C 436, 3388

    2013 doi

  30. [39]

    Centeno R., Socas-Navarro H., 2008, @doi [ ] 10.1086/590405 , https://ui.adsabs.harvard.edu/abs/2008ApJ...682L..61C 682, L61

    2008 doi

  31. [43]

    Cisternas M., et al., 2013, @doi [ ] 10.1088/0004-637X/776/1/50 , https://ui.adsabs.harvard.edu/abs/2013ApJ...776...50C 776, 50

    2013 doi

  32. [44]

    A., 2011, @doi [ ] 10.1088/2041-8205/743/1/L13 , https://ui.adsabs.harvard.edu/abs/2011ApJ...743L..13C 743, L13

    Coelho P., Gadotti D. A., 2011, @doi [ ] 10.1088/2041-8205/743/1/L13 , https://ui.adsabs.harvard.edu/abs/2011ApJ...743L..13C 743, L13

    2011 doi

  33. [45]

    P., Castilho B

    Coelho P., Barbuy B., Mel \'e ndez J., Schiavon R. P., Castilho B. V., 2005, @doi [ ] 10.1051/0004-6361:20053511 , https://ui.adsabs.harvard.edu/abs/2005A&A...443..735C 443, 735

    2005 doi

  34. [47]

    Combes F., et al., 2019, @doi [ ] 10.1051/0004-6361/201834560 , https://ui.adsabs.harvard.edu/abs/2019A&A...623A..79C 623, A79

    2019 doi

  35. [48]

    M., et al., 2021, @doi [ ] 10.1093/mnras/stab229 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505..991C 505, 991

    Croom S. M., et al., 2021, @doi [ ] 10.1093/mnras/stab229 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.505..991C 505, 991

    2021 doi

  36. [49]

    Curti M., Mannucci F., Cresci G., Maiolino R., 2020, @doi [ ] 10.1093/mnras/stz2910 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491..944C 491, 944

    2020 doi

  37. [50]

    L., 2021, @doi [Computing in Science and Engineering] 10.1109/MCSE.2021.3083216 , https://ui.adsabs.harvard.edu/abs/2021CSE....23d..47D 23, 47

    Dalcin L., Fang Y.-L. L., 2021, @doi [Computing in Science and Engineering] 10.1109/MCSE.2021.3083216 , https://ui.adsabs.harvard.edu/abs/2021CSE....23d..47D 23, 47

    2021

  38. [51]

    Dalcín L., Paz R., Storti M., 2005, @doi [Journal of Parallel and Distributed Computing] 10.1016/j.jpdc.2005.03.010 , 65, 1108

    2005 doi

  39. [52]

    Dalcín L., Paz R., Storti M., D’Elía J., 2008, @doi [Journal of Parallel and Distributed Computing] 10.1016/j.jpdc.2007.09.005 , 68, 655

    2008 doi

  40. [53]

    D., Paz R

    Dalcín L. D., Paz R. R., Kler P. A., Cosimo A., 2011, @doi [Advances in Water Resources] 10.1016/j.advwatres.2011.04.013 , 34, 1124

    2011 doi

  41. [54]

    L., et al., 2016, @doi [ ] 10.1093/mnras/stw1754 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.462.1616D 462, 1616

    Davies R. L., et al., 2016, @doi [ ] 10.1093/mnras/stw1754 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.462.1616D 462, 1616

    2016 doi

  42. [55]

    L., et al., 2017, @doi [ ] 10.1093/mnras/stx1559 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4974D 470, 4974

    Davies R. L., et al., 2017, @doi [ ] 10.1093/mnras/stx1559 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.470.4974D 470, 4974

    2017 doi

  43. [56]

    Di Matteo T., Springel V., Hernquist L., 2005, @doi [ ] 10.1038/nature03335 , https://ui.adsabs.harvard.edu/abs/2005Natur.433..604D 433, 604

    2005 doi

  44. [58]

    Dom \' nguez A., et al., 2013, @doi [ ] 10.1088/0004-637X/763/2/145 , https://ui.adsabs.harvard.edu/abs/2013ApJ...763..145D 763, 145

    2013 doi

  45. [59]

    A., Kewley L

    Dopita M. A., Kewley L. J., Sutherland R. S., Nicholls D. C., 2016, @doi [ ] 10.1007/s10509-016-2657-8 , https://ui.adsabs.harvard.edu/abs/2016Ap&SS.361...61D 361, 61

    2016 doi

  46. [60]

    L., Viswanathan A., Patton D

    Ellison S. L., Viswanathan A., Patton D. R., Bottrell C., McConnachie A. W., Gwyn S., Cuillandre J.-C., 2019, @doi [ ] 10.1093/mnras/stz1431 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.2491E 487, 2491

    2019 doi

  47. [61]

    Emsellem E., et al., 2022, @doi [ ] 10.1051/0004-6361/202141727 , https://ui.adsabs.harvard.edu/abs/2022A&A...659A.191E 659, A191

    2022 doi

  48. [62]

    Erwin P., 2004, @doi [ ] 10.1051/0004-6361:20034408 , https://ui.adsabs.harvard.edu/abs/2004A&A...415..941E 415, 941

    2004 doi

  49. [63]

    B., et al., 2000, @doi [ ] 10.1086/301203 , https://ui.adsabs.harvard.edu/abs/2000AJ....119..536E 119, 536

    Eskridge P. B., et al., 2000, @doi [ ] 10.1086/301203 , https://ui.adsabs.harvard.edu/abs/2000AJ....119..536E 119, 536

    2000 doi

  50. [65]

    J., Gorgas J., Peletier R

    Falc \'o n-Barroso J., S \'a nchez-Bl \'a zquez P., Vazdekis A., Ricciardelli E., Cardiel N., Cenarro A. J., Gorgas J., Peletier R. F., 2011, @doi [ ] 10.1051/0004-6361/201116842 , https://ui.adsabs.harvard.edu/abs/2011A&A...532A..95F 532, A95

    2011 doi

  51. [66]

    H., Lan c on A., Ryder S., 2014, @doi [ ] 10.1093/mnras/stt2189 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.438..329F 438, 329

    Falc \'o n-Barroso J., Ramos Almeida C., B \"o ker T., Schinnerer E., Knapen J. H., Lan c on A., Ryder S., 2014, @doi [ ] 10.1093/mnras/stt2189 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.438..329F 438, 329

    2014 doi

  52. [67]

    N., Tombesi F., 2023, @doi [Advances in Space Research] 10.1016/j.asr.2022.11.055 , https://ui.adsabs.harvard.edu/abs/2023AdSpR..71.3499F 71, 3499

    Farhan A., Ercan E. N., Tombesi F., 2023, @doi [Advances in Space Research] 10.1016/j.asr.2022.11.055 , https://ui.adsabs.harvard.edu/abs/2023AdSpR..71.3499F 71, 3499

    2023 doi

  53. [68]

    Fiore F., et al., 2017, @doi [ ] 10.1051/0004-6361/201629478 , https://ui.adsabs.harvard.edu/abs/2017A&A...601A.143F 601, A143

    2017 doi

  54. [69]

    Fragkoudi F., Athanassoula E., Bosma A., Iannuzzi F., 2015, @doi [ ] 10.1093/mnras/stv537 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450..229F 450, 229

    2015 doi

  55. [70]

    Fragkoudi F., Athanassoula E., Bosma A., 2016, @doi [ ] 10.1093/mnrasl/slw120 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.462L..41F 462, L41

    2016 doi

  56. [71]

    arXiv:2406.09453

    Fragkoudi F., Grand R., Pakmor R., G \'o mez F., Marinacci F., Springel V., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.09453 , https://ui.adsabs.harvard.edu/abs/2024arXiv240609453F p. arXiv:2406.09453

    2024 doi arXiv

  57. [72]

    A., de Souza R

    Gadotti D. A., de Souza R. E., 2005, @doi [ ] 10.1086/431717 , https://ui.adsabs.harvard.edu/abs/2005ApJ...629..797G 629, 797

    2005 doi

  58. [73]

    A., et al., 2019, @doi [ ] 10.1093/mnras/sty2666 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.482..506G 482, 506

    Gadotti D. A., et al., 2019, @doi [ ] 10.1093/mnras/sty2666 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.482..506G 482, 506

    2019 doi

  59. [74]

    A., et al., 2020, @doi [ ] 10.1051/0004-6361/202038448 , https://ui.adsabs.harvard.edu/abs/2020A&A...643A..14G 643, A14

    Gadotti D. A., et al., 2020, @doi [ ] 10.1051/0004-6361/202038448 , https://ui.adsabs.harvard.edu/abs/2020A&A...643A..14G 643, A14

    2020 doi

  60. [75]

    A., et al., 2015, @doi [ ] 10.1093/mnras/stv235 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.448.3442G 448, 3442

    Galloway M. A., et al., 2015, @doi [ ] 10.1093/mnras/stv235 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.448.3442G 448, 3442

    2015 doi

  61. [76]

    L., et al., 2024, @doi [ ] 10.1093/mnras/stae1620 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532.2320G 532, 2320

    Garland I. L., et al., 2024, @doi [ ] 10.1093/mnras/stae1620 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532.2320G 532, 2320

    2024 doi

  62. [77]

    E., 1993, @doi [ ] 10.1093/mnras/265.1.213 , https://ui.adsabs.harvard.edu/abs/1993MNRAS.265..213G 265, 213

    Gerhard O. E., 1993, @doi [ ] 10.1093/mnras/265.1.213 , https://ui.adsabs.harvard.edu/abs/1993MNRAS.265..213G 265, 213

    1993 doi

  63. [78]

    Gon c alves G., Coelho P., Schiavon R., Usher C., 2020, @doi [ ] 10.1093/mnras/staa3051 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.499.2327G 499, 2327

    2020 doi

  64. [80]

    D., et al., 2017, @doi [ ] 10.3847/1538-4357/aa755b , https://ui.adsabs.harvard.edu/abs/2017ApJ...843..135G 843, 135

    Goulding A. D., et al., 2017, @doi [ ] 10.3847/1538-4357/aa755b , https://ui.adsabs.harvard.edu/abs/2017ApJ...843..135G 843, 135

    2017 doi

  65. [81]

    M., 2018, @doi [The Journal of Open Source Software] 10.21105/joss.00695 , https://ui.adsabs.harvard.edu/abs/2018JOSS....3..695G 3, 695

    Green G. M., 2018, @doi [The Journal of Open Source Software] 10.21105/joss.00695 , https://ui.adsabs.harvard.edu/abs/2018JOSS....3..695G 3, 695

    2018 doi

  66. [82]

    M., Contini T., Weilbacher P

    Gu \'e rou A., Emsellem E., Krajnovi \'c D., McDermid R. M., Contini T., Weilbacher P. M., 2016, @doi [ ] 10.1051/0004-6361/201628743 , https://ui.adsabs.harvard.edu/abs/2016A&A...591A.143G 591, A143

    2016 doi

  67. [83]

    Guo Y., et al., 2023, @doi [ ] 10.3847/2041-8213/acacfb , https://ui.adsabs.harvard.edu/abs/2023ApJ...945L..10G 945, L10

    2023 doi

  68. [84]

    arXiv:2409.06100

    Guo Y., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2409.06100 , https://ui.adsabs.harvard.edu/abs/2024arXiv240906100G p. arXiv:2409.06100

    2024 doi arXiv

  69. [85]

    R., et al., 2020, @doi [ ] 10.1038/s41586-020-2649-2 , https://ui.adsabs.harvard.edu/abs/2020Natur.585..357H 585, 357

    Harris C. R., et al., 2020, @doi [ ] 10.1038/s41586-020-2649-2 , https://ui.adsabs.harvard.edu/abs/2020Natur.585..357H 585, 357

    2020 doi

  70. [86]

    L., Biermann P., 1984, , https://ui.adsabs.harvard.edu/abs/1984A&A...141L...1H 141, L1

    Henkel C., Guesten R., Downes D., Thum C., Wilson T. L., Biermann P., 1984, , https://ui.adsabs.harvard.edu/abs/1984A&A...141L...1H 141, L1

    1984

  71. [87]

    D., et al., 2019, @doi [ ] 10.1093/mnras/stz471 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.2457H 485, 2457

    Henshaw J. D., et al., 2019, @doi [ ] 10.1093/mnras/stz471 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.2457H 485, 2457

    2019 doi

  72. [88]

    Henshaw J., Ginsburg A., Riener M., 2020, scousepy: Semi-automated multi-COmponent Universal Spectral-line fitting Engine , Astrophysics Source Code Library, record ascl:2003.004

    2020

  73. [89]

    Herpich F., Mateus A., Stasi \'n ska G., Cid Fernandes R., Vale Asari N., 2016, @doi [ ] 10.1093/mnras/stw1742 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.462.1826H 462, 1826

    2016 doi

  74. [90]

    C., 2008, @doi [ ] 10.1146/annurev.astro.45.051806.110546 , https://ui.adsabs.harvard.edu/abs/2008ARA&A..46..475H 46, 475

    Ho L. C., 2008, @doi [ ] 10.1146/annurev.astro.45.051806.110546 , https://ui.adsabs.harvard.edu/abs/2008ARA&A..46..475H 46, 475

    2008 arXiv

  75. [91]

    T., et al., 2014, @doi [ ] 10.1093/mnras/stu1653 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444.3894H 444, 3894

    Ho I. T., et al., 2014, @doi [ ] 10.1093/mnras/stu1653 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444.3894H 444, 3894

    2014 doi

  76. [92]

    T., et al., 2016, @doi [ ] 10.1007/s10509-016-2865-2 , https://ui.adsabs.harvard.edu/abs/2016Ap&SS.361..280H 361, 280

    Ho I. T., et al., 2016, @doi [ ] 10.1007/s10509-016-2865-2 , https://ui.adsabs.harvard.edu/abs/2016Ap&SS.361..280H 361, 280

    2016 doi

  77. [94]

    Hummel E., Jorsater S., 1992, , https://ui.adsabs.harvard.edu/abs/1992A&A...261...85H 261, 85

    1992

  78. [95]

    O., Sandqvist A., 1987, , https://ui.adsabs.harvard.edu/abs/1987A&A...172...51H 172, 51

    Hummel E., Jorsater S., Lindblad P. O., Sandqvist A., 1987, , https://ui.adsabs.harvard.edu/abs/1987A&A...172...51H 172, 51

    1987

  79. [96]

    M., Tsai C.-L., 1989, @doi [Biometrika] 10.1093/biomet/76.2.297 , 76, 297

    Hurvich C. M., Tsai C.-L., 1989, @doi [Biometrika] 10.1093/biomet/76.2.297 , 76, 297

    1989 doi

  80. [97]

    J., 1997, @doi [ ] 10.1051/aas:1997236 , https://ui.adsabs.harvard.edu/abs/1997A&AS..125..479J 125, 479

    Jungwiert B., Combes F., Axon D. J., 1997, @doi [ ] 10.1051/aas:1997236 , https://ui.adsabs.harvard.edu/abs/1997A&AS..125..479J 125, 479

    1997 doi

  81. [98]

    Kakkad D., et al., 2018, @doi [ ] 10.1051/0004-6361/201832790 , https://ui.adsabs.harvard.edu/abs/2018A&A...618A...6K 618, A6

    2018 doi

  82. [99]

    Kauffmann G., et al., 2003, @doi [ ] 10.1111/j.1365-2966.2003.07154.x , https://ui.adsabs.harvard.edu/abs/2003MNRAS.346.1055K 346, 1055

    2003

  83. [100]

    J., Dopita M

    Kewley L. J., Dopita M. A., Sutherland R. S., Heisler C. A., Trevena J., 2001, @doi [ ] 10.1086/321545 , https://ui.adsabs.harvard.edu/abs/2001ApJ...556..121K 556, 121

    2001 doi

  84. [102]

    Kim T., et al., 2014, @doi [ ] 10.1088/0004-637X/782/2/64 , https://ui.adsabs.harvard.edu/abs/2014ApJ...782...64K 782, 64

    2014 doi

  85. [103]

    Kim T., et al., 2024, @doi [ ] 10.3847/1538-4357/ad410e , https://ui.adsabs.harvard.edu/abs/2024ApJ...968...87K 968, 87

    2024 doi

  86. [104]

    H., Shlosman I., Peletier R

    Knapen J. H., Shlosman I., Peletier R. F., 2000, @doi [ ] 10.1086/308266 , https://ui.adsabs.harvard.edu/abs/2000ApJ...529...93K 529, 93

    2000 doi

  87. [105]

    Kolcu T., et al., 2023, @doi [ ] 10.1093/mnras/stad1896 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.524..207K 524, 207

    2023 doi

  88. [106]

    Koleva M., Prugniel P., Ocvirk P., Le Borgne D., Soubiran C., 2008, @doi [ ] 10.1111/j.1365-2966.2008.12908.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.385.1998K 385, 1998

    2008

  89. [107]

    T., et al., 2006, @doi [ ] 10.1086/498641 , https://ui.adsabs.harvard.edu/abs/2006ApJ...638..100K 638, 100

    Kondratko P. T., et al., 2006, @doi [ ] 10.1086/498641 , https://ui.adsabs.harvard.edu/abs/2006ApJ...638..100K 638, 100

    2006 doi

  90. [108]

    Kormendy J., Kennicutt Jr. R. C., 2004, @doi [ ] 10.1146/annurev.astro.42.053102.134024 , https://ui.adsabs.harvard.edu/abs/2004ARA&A..42..603K 42, 603

    2004

  91. [110]

    Krajnovi \'c D., et al., 2015, @doi [ ] 10.1093/mnras/stv958 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452....2K 452, 2

    2015 doi

  92. [111]

    Kroupa P., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04022.x , https://ui.adsabs.harvard.edu/abs/2001MNRAS.322..231K 322, 231

    2001

  93. [112]

    Kumari N., Maiolino R., Belfiore F., Curti M., 2019, @doi [ ] 10.1093/mnras/stz366 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485..367K 485, 367

    2019 doi

  94. [113]

    H., Peletier R

    Laine S., Shlosman I., Knapen J. H., Peletier R. F., 2002, @doi [ ] 10.1086/323964 , https://ui.adsabs.harvard.edu/abs/2002ApJ...567...97L 567, 97

    2002 doi

  95. [114]

    Laurikainen E., Salo H., Athanassoula E., Bosma A., Herrera-Endoqui M., 2014, @doi [ ] 10.1093/mnrasl/slu118 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444L..80L 444, L80

    2014 doi

  96. [115]

    A., et al., 2024, @doi [ ] 10.1093/mnras/stae921 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.530.1984L 530, 1984

    Le Conte Z. A., et al., 2024, @doi [ ] 10.1093/mnras/stae921 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.530.1984L 530, 1984

    2024 doi

  97. [116]

    Leitherer C., et al., 1999, @doi [ ] 10.1086/313233 , https://ui.adsabs.harvard.edu/abs/1999ApJS..123....3L 123, 3

    1999 doi

  98. [117]

    B., Giavalisco M., Bender R., Capaccioli M., 1996, , https://ui.adsabs.harvard.edu/abs/1996A&AS..120..463M 120, 463

    Macchetto F., Pastoriza M., Caon N., Sparks W. B., Giavalisco M., Bender R., Capaccioli M., 1996, , https://ui.adsabs.harvard.edu/abs/1996A&AS..120..463M 120, 463

    1996

  99. [118]

    Maiolino R., Mannucci F., 2019, @doi [ ] 10.1007/s00159-018-0112-2 , https://ui.adsabs.harvard.edu/abs/2019A&ARv..27....3M 27, 3

    2019 doi

  100. [119]

    Makarov D., Prugniel P., Terekhova N., Courtois H., Vauglin I., 2014, @doi [ ] 10.1051/0004-6361/201423496 , https://ui.adsabs.harvard.edu/abs/2014A&A...570A..13M 570, A13

    2014 doi

  101. [120]

    B., 2009, in Bohlender D

    Markwardt C. B., 2009, in Bohlender D. A., Durand D., Dowler P., eds, Astronomical Society of the Pacific Conference Series Vol. 411, Astronomical Data Analysis Software and Systems XVIII. p. 251 ( @eprint arXiv 0902.2850 ), @doi 10.48550/arXiv.0902.2850

    2009 doi arXiv

  102. [121]

    Martig M., et al., 2021, @doi [ ] 10.1093/mnras/stab2729 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.2458M 508, 2458

    2021 doi

  103. [122]

    W., Mulchaey J

    Martini P., Regan M. W., Mulchaey J. S., Pogge R. W., 2003, @doi [ ] 10.1086/374685 , https://ui.adsabs.harvard.edu/abs/2003ApJ...589..774M 589, 774

    2003 doi

  104. [123]

    M., et al., 2018, @doi [ ] 10.1093/mnras/sty127 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475.5194M 475, 5194

    Medling A. M., et al., 2018, @doi [ ] 10.1093/mnras/sty127 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.475.5194M 475, 5194

    2018 doi

  105. [124]

    M \'e ndez-Abreu J., Costantin L., Kruk S., 2023, @doi [ ] 10.1051/0004-6361/202346685 , https://ui.adsabs.harvard.edu/abs/2023A&A...678A..54M 678, A54

    2023 doi

  106. [125]

    H., Scoville N

    Men \'e ndez-Delmestre K., Sheth K., Schinnerer E., Jarrett T. H., Scoville N. Z., 2007, @doi [ ] 10.1086/511025 , https://ui.adsabs.harvard.edu/abs/2007ApJ...657..790M 657, 790

    2007 doi

  107. [127]

    Mingozzi M., et al., 2019, @doi [ ] 10.1051/0004-6361/201834372 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.146M 622, A146

    2019 doi

  108. [128]

    G., Lee J

    Momcheva I. G., Lee J. C., Ly C., Salim S., Dale D. A., Ouchi M., Finn R., Ono Y., 2013, @doi [ ] 10.1088/0004-6256/145/2/47 , https://ui.adsabs.harvard.edu/abs/2013AJ....145...47M 145, 47

    2013 doi

  109. [129]

    C., et al., 2013, @doi [ ] 10.1088/0004-637X/771/1/59 , https://ui.adsabs.harvard.edu/abs/2013ApJ...771...59M 771, 59

    Mu \ n oz-Mateos J. C., et al., 2013, @doi [ ] 10.1088/0004-637X/771/1/59 , https://ui.adsabs.harvard.edu/abs/2013ApJ...771...59M 771, 59

    2013 doi

  110. [130]

    G., de Freitas Pacheco J

    Nasonova O. G., de Freitas Pacheco J. A., Karachentsev I. D., 2011, @doi [ ] 10.1051/0004-6361/201016004 , https://ui.adsabs.harvard.edu/abs/2011A&A...532A.104N 532, A104

    2011 doi

  111. [131]

    Neumann J., et al., 2022, @doi [ ] 10.1093/mnras/stac1260 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.513.5988N 513, 5988

    2022 doi

  112. [133]

    K., 2012, @doi [ ] 10.1088/0067-0049/198/1/4 , https://ui.adsabs.harvard.edu/abs/2012ApJS..198....4O 198, 4

    Oh S., Oh K., Yi S. K., 2012, @doi [ ] 10.1088/0067-0049/198/1/4 , https://ui.adsabs.harvard.edu/abs/2012ApJS..198....4O 198, 4

    2012 doi

  113. [134]

    Onodera M., et al., 2012, @doi [ ] 10.1088/0004-637X/755/1/26 , https://ui.adsabs.harvard.edu/abs/2012ApJ...755...26O 755, 26

    2012 doi

  114. [135]

    E., Ferland G

    Osterbrock D. E., Ferland G. J., 2006, Astrophysics of gaseous nebulae and active galactic nuclei . University Science Books

    2006

  115. [136]

    Pedregosa F., et al., 2011, @doi [Journal of Machine Learning Research] 10.48550/arXiv.1201.0490 , https://ui.adsabs.harvard.edu/abs/2011JMLR...12.2825P 12, 2825

    2011 doi arXiv

  116. [137]

    Pettini M., Pagel B. E. J., 2004, @doi [ ] 10.1111/j.1365-2966.2004.07591.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.348L..59P 348, L59

    2004

  117. [138]

    Pietrinferni A., Cassisi S., Salaris M., Castelli F., 2004, @doi [ ] 10.1086/422498 , https://ui.adsabs.harvard.edu/abs/2004ApJ...612..168P 612, 168

    2004 doi

  118. [139]

    Pietrinferni A., Cassisi S., Salaris M., Castelli F., 2006, @doi [ ] 10.1086/501344 , https://ui.adsabs.harvard.edu/abs/2006ApJ...642..797P 642, 797

    2006 doi

  119. [140]

    G., Stone J

    Piner B. G., Stone J. M., Teuben P. J., 1995, @doi [ ] 10.1086/176075 , https://ui.adsabs.harvard.edu/abs/1995ApJ...449..508P 449, 508

    1995 doi

  120. [141]

    Pinna F., et al., 2021, @doi [ ] 10.3847/1538-4357/ac158f , https://ui.adsabs.harvard.edu/abs/2021ApJ...921....8P 921, 8

    2021 doi

  121. [142]

    H., Teukolsky S

    Press W. H., Teukolsky S. A., Vetterling W. T., 2007, Numerical Recipes : The Art of Scientific Computing , 3rd edn. Cambridge University Press, Cambridge

    2007

  122. [143]

    Querejeta M., et al., 2015, @doi [ ] 10.1088/0067-0049/219/1/5 , https://ui.adsabs.harvard.edu/abs/2015ApJS..219....5Q 219, 5

    2015 doi

  123. [144]

    Rakshit S., Woo J.-H., 2018, @doi [ ] 10.3847/1538-4357/aad9f8 , https://ui.adsabs.harvard.edu/abs/2018ApJ...865....5R 865, 5

    2018 doi

  124. [145]

    W., Mulchaey J

    Regan M. W., Mulchaey J. S., 1999, @doi [ ] 10.1086/300888 , https://ui.adsabs.harvard.edu/abs/1999AJ....117.2676R 117, 2676

    1999 doi

  125. [146]

    Riffel R., et al., 2024, @doi [ ] 10.1093/mnras/stae1192 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531..554R 531, 554

    2024 doi

  126. [147]

    Rosado-Belza D., et al., 2020, @doi [ ] 10.1051/0004-6361/202039530 , https://ui.adsabs.harvard.edu/abs/2020A&A...644A.116R 644, A116

    2020 doi

  127. [148]

    Rosas-Guevara Y., et al., 2022, @doi [ ] 10.1093/mnras/stac816 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.5339R 512, 5339

    2022 doi

  128. [149]

    Ruschel-Dutra D., et al., 2021, @doi [ ] 10.1093/mnras/stab2058 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.507...74R 507, 74

    2021 doi

  129. [151]

    K., P \'e rez I., Peletier R

    S \'a nchez-Bl \'a zquez P., Ocvirk P., Gibson B. K., P \'e rez I., Peletier R. F., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18749.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.415..709S 415, 709

    2011

  130. [152]

    S \'a nchez-Garc \' a O., et al., 2023, @doi [ ] 10.3847/1538-4357/acb269 , https://ui.adsabs.harvard.edu/abs/2023ApJ...945...99S 945, 99

    2023 doi

  131. [153]

    F., et al., 2012, @doi [ ] 10.1051/0004-6361/201117353 , https://ui.adsabs.harvard.edu/abs/2012A&A...538A...8S 538, A8

    S \'a nchez S. F., et al., 2012, @doi [ ] 10.1051/0004-6361/201117353 , https://ui.adsabs.harvard.edu/abs/2012A&A...538A...8S 538, A8

    2012 doi

  132. [154]

    L., et al., 2016, @doi [ ] 10.3847/0004-637X/816/1/23 , https://ui.adsabs.harvard.edu/abs/2016ApJ...816...23S 816, 23

    Sanders R. L., et al., 2016, @doi [ ] 10.3847/0004-637X/816/1/23 , https://ui.adsabs.harvard.edu/abs/2016ApJ...816...23S 816, 23

    2016 doi

  133. [155]

    Sarzi M., et al., 2006, @doi [Monthly Notices of the Royal Astronomical Society] 10.1111/j.1365-2966.2005.09839.x , 366, 1151

    2006

  134. [156]

    Sarzi M., et al., 2010, @doi [Monthly Notices of the Royal Astronomical Society] 10.1111/j.1365-2966.2009.16039.x , 402, 2187

    2010

  135. [157]

    Sarzi M., et al., 2018, @doi [ ] 10.1051/0004-6361/201833137 , https://ui.adsabs.harvard.edu/abs/2018A&A...616A.121S 616, A121

    2018 doi

  136. [159]

    Schinnerer E., et al., 2023, @doi [ ] 10.3847/2041-8213/acac9e , https://ui.adsabs.harvard.edu/abs/2023ApJ...944L..15S 944, L15

    2023 doi

  137. [160]

    J., Finkbeiner D

    Schlegel D. J., Finkbeiner D. P., Davis M., 1998, @doi [ ] 10.1086/305772 , https://ui.adsabs.harvard.edu/abs/1998ApJ...500..525S 500, 525

    1998 doi

  138. [161]

    M., Ellison S

    Scudder J. M., Ellison S. L., Torrey P., Patton D. R., Mendel J. T., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21749.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.426..549S 426, 549

    2012

  139. [162]

    A., 2014, @doi [Reviews of Modern Physics] 10.1103/RevModPhys.86.1 , https://ui.adsabs.harvard.edu/abs/2014RvMP...86....1S 86, 1

    Sellwood J. A., 2014, @doi [Reviews of Modern Physics] 10.1103/RevModPhys.86.1 , https://ui.adsabs.harvard.edu/abs/2014RvMP...86....1S 86, 1

    2014 doi

  140. [163]

    A., Wilkinson A., 1993, @doi [Reports on Progress in Physics] 10.1088/0034-4885/56/2/001 , https://ui.adsabs.harvard.edu/abs/1993RPPh...56..173S 56, 173

    Sellwood J. A., Wilkinson A., 1993, @doi [Reports on Progress in Physics] 10.1088/0034-4885/56/2/001 , https://ui.adsabs.harvard.edu/abs/1993RPPh...56..173S 56, 173

    1993 doi

  141. [164]

    Sheth K., et al., 2010, @doi [ ] 10.1086/657638 , https://ui.adsabs.harvard.edu/abs/2010PASP..122.1397S 122, 1397

    2010 doi

  142. [165]

    S., Baba J., Saitoh T

    Shin J., Kim S. S., Baba J., Saitoh T. R., Hwang J.-S., Chun K., Hozumi S., 2017, @doi [ ] 10.3847/1538-4357/aa7061 , https://ui.adsabs.harvard.edu/abs/2017ApJ...841...74S 841, 74

    2017 doi

  143. [166]

    A., Martins L

    Silva-Lima L. A., Martins L. P., Coelho P. R. T., Gadotti D. A., 2022, @doi [ ] 10.1051/0004-6361/202142432 , https://ui.adsabs.harvard.edu/abs/2022A&A...661A.105S 661, A105

    2022 doi

  144. [167]

    J., Simmons B

    Smethurst R. J., Simmons B. D., Lintott C. J., Shanahan J., 2019, @doi [ ] 10.1093/mnras/stz2443 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.4016S 489, 4016

    2019 doi

  145. [168]

    J., et al., 2021, @doi [ ] 10.1093/mnras/stab2340 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.3985S 507, 3985

    Smethurst R. J., et al., 2021, @doi [ ] 10.1093/mnras/stab2340 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.3985S 507, 3985

    2021 doi

  146. [169]

    C., Binney J., Magorrian J., 2015, @doi [ ] 10.1093/mnras/stv441 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.449.2421S 449, 2421

    Sormani M. C., Binney J., Magorrian J., 2015, @doi [ ] 10.1093/mnras/stv441 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.449.2421S 449, 2421

    2015 doi

  147. [170]

    C., Sobacchi E., Fragkoudi F., Ridley M., Tre R

    Sormani M. C., Sobacchi E., Fragkoudi F., Ridley M., Tre R. G., Glover S. C. O., Klessen R. S., 2018, @doi [ ] 10.1093/mnras/sty2246 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.481....2S 481, 2

    2018 doi

  148. [171]

    C., et al., 2019, @doi [ ] 10.1093/mnras/stz2054 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.4663S 488, 4663

    Sormani M. C., et al., 2019, @doi [ ] 10.1093/mnras/stz2054 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.4663S 488, 4663

    2019 doi

  149. [172]

    C., et al., 2023, @doi [ ] 10.1093/mnras/stad1554 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.2918S 523, 2918

    Sormani M. C., et al., 2023, @doi [ ] 10.1093/mnras/stad1554 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.2918S 523, 2918

    2023 doi

  150. [173]

    V., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10732.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.371..972S 371, 972

    Stasi \'n ska G., Cid Fernandes R., Mateus A., Sodr \'e L., Asari N. V., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10732.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.371..972S 371, 972

    2006

  151. [174]

    Stasińska G., Trevisan M., Vale Asari N., 2022, @doi [Frontiers in Astronomy and Space Sciences] 10.3389/fspas.2022.913485 , 9, 913485

    2022

  152. [175]

    Thater S., et al., 2022, @doi [ ] 10.1093/mnras/stab3210 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.5416T 509, 5416

    2022 doi

  153. [176]

    N., Arsenin V

    Tikhonov A. N., Arsenin V. Y., 1977, Solutions of ill-posed problems. V. H. Winston & Sons, Washington, D.C.: John Wiley & Sons, New York

    1977

  154. [177]

    F., Jimenez R., Panter B., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12323.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.381.1252T 381, 1252

    Tojeiro R., Heavens A. F., Jimenez R., Panter B., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12323.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.381.1252T 381, 1252

    2007

  155. [178]

    J., Beasley M

    Vazdekis A., S \'a nchez-Bl \'a zquez P., Falc \'o n-Barroso J., Cenarro A. J., Beasley M. A., Cardiel N., Gorgas J., Peletier R. F., 2010, @doi [ ] 10.1111/j.1365-2966.2010.16407.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.404.1639V 404, 1639

    2010

  156. [179]

    Vazdekis A., et al., 2015, @doi [ ] 10.1093/mnras/stv151 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.449.1177V 449, 1177

    2015 doi

  157. [180]

    Venturi G., et al., 2018, @doi [ ] 10.1051/0004-6361/201833668 , https://ui.adsabs.harvard.edu/abs/2018A&A...619A..74V 619, A74

    2018 doi

  158. [181]

    Venturi G., et al., 2021, @doi [ ] 10.1051/0004-6361/202039869 , https://ui.adsabs.harvard.edu/abs/2021A&A...648A..17V 648, A17

    2021 doi

  159. [182]

    P., Veron P., 1986, , https://ui.adsabs.harvard.edu/abs/1986A&AS...66..335V 66, 335

    Veron-Cetty M. P., Veron P., 1986, , https://ui.adsabs.harvard.edu/abs/1986A&AS...66..335V 66, 335

    1986

  160. [183]

    Virtanen P., et al., 2020, @doi [Nature Methods] 10.1038/s41592-019-0686-2 , https://rdcu.be/b08Wh 17, 261

    2020 doi

  161. [184]

    M., Streicher O., Urrutia T., Jarno A., P \'e contal-Rousset A., Bacon R., B \"o hm P., 2012, in Radziwill N

    Weilbacher P. M., Streicher O., Urrutia T., Jarno A., P \'e contal-Rousset A., Bacon R., B \"o hm P., 2012, in Radziwill N. M., Chiozzi G., eds, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 8451, Software and Cyberinfrastructure for Astronom...

    2012 doi

  162. [185]

    B., et al., 2019, @doi [ ] 10.3847/1538-3881/ab44a2 , https://ui.adsabs.harvard.edu/abs/2019AJ....158..231W 158, 231

    Westfall K. B., et al., 2019, @doi [ ] 10.3847/1538-3881/ab44a2 , https://ui.adsabs.harvard.edu/abs/2019AJ....158..231W 158, 231

    2019 doi

  163. [186]

    M., Maraston C., Goddard D., Thomas D., Parikh T., 2017, @doi [ ] 10.1093/mnras/stx2215 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.472.4297W 472, 4297

    Wilkinson D. M., Maraston C., Goddard D., Thomas D., Parikh T., 2017, @doi [ ] 10.1093/mnras/stx2215 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.472.4297W 472, 4297

    2017 doi

  164. [187]

    S., Henkel C., Kadler M., Greenhill L

    Zhang J. S., Henkel C., Kadler M., Greenhill L. J., Nagar N., Wilson A. S., Braatz J. A., 2006, @doi [ ] 10.1051/0004-6361:20054138 , https://ui.adsabs.harvard.edu/abs/2006A&A...450..933Z 450, 933

    2006 doi

  165. [188]

    de Lorenzo-C \'a ceres A., Falc \'o n-Barroso J., Vazdekis A., 2013, @doi [ ] 10.1093/mnras/stt334 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.431.2397D 431, 2397

    2013 doi

  166. [189]

    de Lorenzo-C \'a ceres A., et al., 2019, @doi [ ] 10.1093/mnras/stz221 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.5296D 484, 5296

    2019 doi

  167. [190]

    de Sá-Freitas C., et al., 2023a, @doi [ ] 10.1051/0004-6361/202244667 , https://ui.adsabs.harvard.edu/abs/2023A&A...671A...8D 671, A8

    doi

  168. [191]

    de Sá-Freitas C., et al., 2023b, @doi [ ] 10.1051/0004-6361/202347028 , https://ui.adsabs.harvard.edu/abs/2023A&A...678A.202D 678, A202

    doi

  169. [192]

    arXiv:2503.20864

    de Sá-Freitas C., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2503.20864 , https://ui.adsabs.harvard.edu/abs/2025arXiv250320864D p. arXiv:2503.20864

    2025 doi

  170. [193]

    P., Franx M., 1993, @doi [ ] 10.1086/172534 , https://ui.adsabs.harvard.edu/abs/1993ApJ...407..525V 407, 525

    van der Marel R. P., Franx M., 1993, @doi [ ] 10.1086/172534 , https://ui.adsabs.harvard.edu/abs/1993ApJ...407..525V 407, 525

    1993 doi

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