Issue |
A&A
Volume 690, October 2024
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Article Number | A143 | |
Number of page(s) | 27 | |
Section | Extragalactic astronomy | |
DOI | https://doi.org/10.1051/0004-6361/202142892 | |
Published online | 04 October 2024 |
Resolving double-peaked emission line galaxies using MaNGA
I. Mechanisms of star formation quenching
1
Observatoire de Paris, PSL University, CNRS, Sorbonne Université, LERMA, 75014 Paris, France
2
Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
3
ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Australia
4
Collège de France, 11 Place Marcelin Berthelot, 75005 Paris, France
5
Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
Received:
13
December
2021
Accepted:
2
July
2024
Understanding the relationship between quenching mechanisms that transform star-forming galaxies into quiescent ones and galaxy properties remains a challenge. We investigate the gas and stellar properties of 69 double-peaked galaxies selected from the Sloan Digital Sky Survey (SDSS) and observed as part of the Mapping Nearby Galaxies at APO (MaNGA) survey to elucidate the mechanisms driving star formation quenching within these systems. We study their star formation activity along with their physical properties: colour, morphology, environment, stellar age, and gas ionisation diagnostics. We find that these 69 double-peaked MaNGA galaxies encompass a higher fraction of galaxies in the green valley, based on the corrected NUV − r colour, compared to our defined control samples of single-peaked emission line galaxies. This green colour traces intermediate stellar populations compared to blue and red galaxies, as indicated by the Dn(4000) index. These green galaxies show no recent star formation bursts within the last 2 Gyr. They exhibit emission line ratios that are suggestive of both ongoing star formation and nuclear activity. They are predominantly located in isolated or small group environments, indicating that internal processes rather than external factors drive their quenching. Moreover, optical emission lines detected throughout a significant area of these systems suggest that gas depletion is unlikely to be the primary quenching mechanism. These findings support a scenario where quenching is instead caused by reduced star formation efficiency.
Key words: methods: data analysis / techniques: spectroscopic / Galaxy: evolution / galaxies: interactions / galaxies: ISM / galaxies: kinematics and dynamics
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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1. Introduction
Observations of large galaxy samples have shown that galaxies in the Local Universe follow a bi-modal distribution in the colour–magnitude and colour–mass diagrams (Blanton et al. 2011; Baldry et al. 2004). The two main populations correspond to a ‘blue cloud’ with galaxies characterised by active star formation, and a ‘red sequence’, referring to passive galaxies; whereas the region lying between these two groups is known as the ‘green valley’ (Salim 2014). This latter region may be defined in the UV-optical colour-magnitude diagram and is considered as a way to pinpoint transitional galaxies (Salim 2014), lying below the star-forming sequence but not yet entirely passive. The bi-modality is found to mainly depend on the specific evolutionary stage, but also on morphology (discs dominating in the blue cloud and spheroids in the red sequence), even though it is challenging to build pure and complete morphological samples based on colour selection (Smethurst et al. 2022). Therefore, objects lying in the green valley, which are thought to be in transition, are critical to the understanding of the paths from the active sequence to quiescence.
The termination of star formation activity, or quenching, plays a key role in this transition. However, this process remains an open question, as the mechanisms involved are numerous and complex. For instance, the environment can reduce the gas fraction in galaxy clusters, through ram pressure stripping (Boselli et al. 2016) or strangulation (Weinmann et al. 2009). Hence, high-density environments reduce star formation and shorten the quenching timescale (e.g. Coenda et al. 2018). Other mechanisms can stop the star formation activity, such as morphological quenching (Martig et al. 2009), which corresponds to the stabilisation of the gas due to bulge growth and/or bar-driven processes, preventing the gas from collapsing and forming stars. Saintonge et al. (2011) also showed that the molecular gas depletion time is longer at high stellar masses. Furthermore, these authors discussed a possible active galactic nucleus (AGN) contribution as one of the processes responsible for the quenching. Barrows et al. (2017) found a positive correlation between the specific star formation rate and AGN luminosity; however, on the other hand, Kaviraj et al. (2015) showed that nearby merger-triggered AGN are unlikely to provide strong regulation in the star formation process, given the different timescales involved. Gas depletion appears to be one of the most obvious mechanisms behind the quenching of star formation, but the removal of the gas itself can be caused by different phenomena, such as ram pressure stripping, viscous stripping, or strangulation. The first has been shown to be the most efficient in rich galaxy clusters, but Rasmussen et al. (2008) demonstrated that it is not sufficient to explain gas depletion in compact groups. The two latter effects were then proposed as an alternative way to interpret the gas depletion. Tidal interactions and merging processes can drive the gas towards the centre of galaxies, which triggers a starburst and thus enhances central star formation on a relatively short time-scale (Di Matteo et al. 2008; Patton et al. 2011). This subsequent active star formation will finally consume the gas reservoir and result in the final quenching. Identifying and studying galaxy pairs or at least interacting galaxies thus appear crucial to investigate the star formation cycle of galaxies. For spectacular systems such as the Antennae (Whitmore et al. 2014; Lahén et al. 2018), the Taffy galaxies (Condon et al. 1993) or IIZw096 (Inami et al. 2010), the merging process is obvious. In parallel, for other objects with no morphological signatures, it can be challenging to unveil an ongoing merger event, especially a minor merger. Therefore, investigating the gas kinematics is necessary. Some complex emission line profiles can be used as a tracers of galaxy interactions, such as the double-peaked (DP) emission lines. A systematic search for these features was performed in Ge et al. (2012) and more detailed works on the origin of double-peaked profiles have mostly been focussed on dual AGN (e.g. Comerford et al. 2012; Nevin et al. 2018).
Based on the asset that double-peaked emission lines can trace key processes of galaxy evolution, Maschmann et al. (2020) (hereafter M20) selected 5663 galaxies from the Reference Catalogue of Spectral Energy Distribution (RCSED, Chilingarian et al. 2017) exhibiting such line shapes. They developed an automated selection procedure to find DP galaxies without relying on a visual inspection of the spectra. These DP galaxies display significant differences compared to a control sample that was selected following the same stellar mass and redshift distributions: they mostly evolve in an isolated environment, but show a significant excess of S0 galaxies, a large stellar velocity dispersion, and an enhanced central star formation activity. No dependency on inclination was found, discarding a simple scenario of a rotating disc. The authors have argued that this sample corresponds to a minor-merger sequence, as suggested in Bournaud et al. (2007) (see details in Maschmann et al. 2020). More detailed studies on smaller galaxy samples, such as that of Comerford et al. (2018), have been able to identify a past merger as the underlying process of the observed DP emission lines. Similarly, Maschmann & Melchior (2019) found different ionisation sources in the two emission line components of DP galaxies, possibly manifesting the two progenitors of a galaxy merger. A more detailed analysis with spatially-resolved spectroscopic observations succeeded in decomposing two kinematic components (Mazzilli Ciraulo et al. 2021): the two components from two galaxies in the act of merging created DP emission line features. However, it is still challenging to draw conclusions on the underlying process leading to DP emission lines in large galaxy samples; this is because there are numerous effects, such as a rotating inner disc or nuclear outflows, that may be responsible for DP emission lines (detailed discussion therein Maschmann et al. 2020). The emergence and availability of large integral field spectroscopic surveys enable the nature of the closest galaxies (at z < 0.14), revealing the DP emission line profiles that are to be investigated in further details. Therefore, we cross-identified the galaxies of the DP catalogue mentioned above with the targets encompassed in the summary file from the MaNGA Data Reduction Pipeline (DRP, Law et al. 2016) of the SDSS Data Release 17 (Abdurro’uf et al. 2022). We identified a sample of 69 nearby galaxies located at an average redshift of 0.0575 (DL = 246.4 Mpc), hereafter referred to as the DP/MaNGA sample.
In Sect. 2, we describe the DP/MaNGA sample and the data gathered for the corresponding galaxies. We also define control samples of single-Gaussian-shaped emission-line galaxies that will be used for comparison. In Sect. 3, we explore the properties of these 69 DP/MaNGA galaxies in contrast to the control samples. We discuss the AGN-like emission with respect to the star formation activity in Sect. 4. We study the star formation history indicators in Sect. 5. In Sect. 6, we discuss how these galaxies fit in the more general evolution of star formation quenching in galaxies, followed by a summary in Sect. 7. A cosmology of Ωm = 0.3, ΩΛ = 0.7, and H0 = 0.7 is assumed throughout this work.
2. Sample and data description
2.1. The DP/MaNGA sample
We have drawn our sample of galaxies from the catalogue of double-peaked emission line galaxies published by Maschmann et al. (2020). The DP emission selection is based on three different steps. First, galaxies at z < 0.34 with a strong Hα or [OIII]λ5007 line (i.e. S/N > 10) were selected. Then, galaxies with at least three emission lines obeying S/N > 5 were chosen. These criteria imply that the DP galaxies have gas without being too obscured by dust.
Selection criteria for double-peaked emission line galaxies.
Mapping Nearby Galaxies at APO (MaNGA, Bundy et al. 2015) is part of the fourth generation of SDSS (SDSS-IV, Blanton et al. 2017) and it consists of an integral field unit survey targeting local (0.01 < z < 0.15) galaxies with stellar masses of M⋆ ≥ 109 M⊙. One essential design criterion of this survey is to provide a uniform radial coverage in units of r-band effective radius, Reff. About two-thirds of the MaNGA targets have been observed to 1.5 Reff and one-third to 2.5 Reff (Wake et al. 2017). By construction, the distribution of the MaNGA galaxies in the M⋆ − z plane is thus bimodal. The observations are performed using integral field units (IFUs) of different sizes, from 19 to 127 fibres corresponding to an outer-on-sky diameter from 12.5 to 32.5″ (Drory et al. 2015). The spectra have been observed in the range of 3600–10 400 Å with an averaged spectral resolution of R ∼ 2000 and a mean spatial resolution of ∼2.5″. Individual fibre spectra were re-arranged into a data cube with 0.5″ × 0.5″ spaxels, meaning that about 25 adjacent spaxels are correlated. The MaNGA data are well-suited to study the ionised gas, namely, its distribution, kinematics and excitation within the observed sources. Value-added catalogues are available for MaNGA galaxies and enable us to investigate the photometry measurements and morphology (MaNGA PyMorph DR17 photometric catalogue and MaNGA Morphology Deep Learning DR17, Fischer et al. 2019; Domínguez Sánchez et al. 2022), as well as the stellar properties and global properties (MaNGA Pipe3D, Sánchez et al. 2016a,b) of the targets. To study DP galaxies in greater detail, we cross-matched the DP catalogue of Maschmann et al. (2020) with the MaNGA DR17 catalogue (Abdurro’uf et al. 2022) and found 69 DP galaxies observed by MaNGA. These galaxies are listed in Table A1, sorted by redshift. We fit all spectra of these 69 DP/MaNGA galaxies by using a double-Gaussian function. An example of a spectrum, extracted from a MaNGA data cube, fit with our multi-component algorithm is shown on Fig. B.1. We used similar criteria as in Maschmann et al. (2020) to define whether the DP features are found throughout the galaxy or only in the centre. An emission line is considered as double-peaked if both peaks have a signal-to-noise ratio (S/N) greater than 3; the velocity difference between both components is greater than 180 km s−1 (about three times the MaNGA spectral resolution); an F-test ensures that the double Gaussian fit is better than the single Gaussian one; the amplitude ratio between both peaks is between and 3. Based on these criteria, we find 26 galaxies for which the DP features are detected throughout a region at least as extended as the MaNGA PSF (these galaxies are pointed out by checkmarks in Tab. A1). For these galaxies, the DP emission lines can be caused by outflows (as for G9, Nevin et al. 2018), or a merger event (as for G61, see Mazzilli Ciraulo et al. 2021). For the 24 others, the DP characteristics are likely due to rotation and a large velocity gradient in the centre. Based on colour–magnitude diagrams, Salim (2014) denotes the green valley (GV) such as 4 < NUV − r < 5, using uncorrected colour measurements, and recommends to correct the colour for dust attenuation. In Fig. 1, we show the colour–magnitude diagram for the DP/MaNGA and the control samples (see Sect. 2.2). We used dust- and K-corrected r-band and NUV magnitudes provided by the RCSED catalogue (Chilingarian et al. 2017). The average colour error for our sample is about 0.08 mag on NUV − r. We corrected these magnitudes for dust attenuation by following the method described in Appendix C. Briefly, we computed the average colour excess ⟨E(B − V)⟩ from the Balmer decrement map for each galaxy (displayed in Appendix D). Finally, this ⟨E(B − V)⟩ was used to correct both the NUV and r magnitudes, following Calzetti et al. (2000) as in de Sá-Freitas et al. (2022, Eq. (3)). We computed the absolute magnitude Mr from the apparent magnitude accounting for redshift effects, following Eq. (1) of Wyder et al. (2007). The contours correspond to ∼7300 galaxies from MaNGA DR17 with NUV and r magnitude measurements. The coloured stars are the DP/MaNGA galaxies and the grey dots (resp. solid circles) show the CS1 (resp. CS2) galaxies discussed in Sect. 2.2. After our dust attenuation correction applied to 7351 MaNGA DR17, we noted an average decrease of NUV − r colour of 0.5 mag. Thus, we shifted the green valley demarcation lines of this amount. We classified galaxies within the red sequence (NUV – r > 4.5), the GV (3.5 < NUV − r < 4.5) and the blue cloud (NUV − r < 3.5). For the eight DP/MaNGA galaxies without GALEX measurements, we used the u − r colour, corrected it for dust attenuation, and followed the classification defined in Ge et al. (2019).
Fig. 1. Colour–magnitude diagram for 61 DP/MaNGA galaxies (the eight others do not have a NUV − r colour measurement). Here, Mr is the r-band absolute magnitude. The colour NUV − r is taken from the RCSED catalogue and is K- and Galactic extinction-corrected (Chilingarian et al. 2017). Top panel: apparent NUV − r colour. The green dashed lines show the green valley definition as in Salim (2014). Bottom panel: NUV − r colour corrected for dust attenuation. In both panels, the contours represent the 7351 galaxies from the MaNGA DR17 with a NUV − r colour measurement in the RCSED catalogue. The shaded green dashed lines refer to the green valley definition as in Salim (2014), while the other dashed lines show our green valley definition after dust attenuation correction. |
Classification based on the NUV − r colour.
2.2. Selection of the control samples
We defined the control samples of galaxies with single-Gaussian shaped emission lines to make a comparison with our sample to them and, thus, we were able to find the distinctive characteristics of the 69 DP/MaNGA galaxies. Following the procedure described in Maschmann et al. (2020), we selected the galaxies for our control samples, following the same redshift and stellar mass M⋆ distribution as the DP/MaNGA sample. We started from the control sample (CS) defined in Maschmann et al. (2020), which consists of 89 412 galaxies characterised by single-Gaussian shaped emission lines in the 3″ SDSS fibre. This criterion is met if χ2(Gaussian fit) < χ2(non-parametric fit). Since this CS is dominated by galaxies with smaller stellar masses compared to the DP/MaNGA sample, we are limited in the number of galaxies with the same redshift and stellar mass distribution. We selected a first control sample (hereafter CS1), consisting of 301 galaxies from the CS of M20. We choose to keep the five closest CS galaxies from each DP/MaNGA galaxy in the M⋆ − z plane. In this way, it turns out that some of our galaxies share the same control-sample objects. Therefore CS1 consists of 301 and not 345 galaxies. This CS1 only includes 31 galaxies observed by MaNGA. To enable a comparison with MaNGA-selected control galaxies, we selected a second control sample (hereafter CS2). Therefore, we first cross-matched the CS with the MaNGA DR17 catalogue and then selected again the five closest galaxies in the M⋆ − z plane. Secondly, we selected the CS2 consisting of 143 galaxies. As shown in Fig. 2, the CS2 comprises less massive galaxies than the CS1. This is due to the fact that at higher masses only a few galaxies with a single-peaked central emission line profile was observed by MaNGA. To visualise the samples selected for this work in contrast to the samples of Maschmann et al. (2020) and the MaNGA DR17, we show their stellar mass–redshift distribution in Fig. 2.
Fig. 2. Distribution in the M⋆ − z plane of the DP/MaNGA (colour-coded stars on left panel), CS1 (coloured dots on middle panel) and CS2 (coloured circles in right panel) galaxies. These three samples are respectively superimposed on the DPS distribution, the CS from Maschmann et al. (2020), and the whole MaNGA sample from DR17 (Bundy et al. 2015; Abdurro’uf et al. 2022). The bimodality of the MaNGA sample distribution is due to the survey design criteria. The colour coding refers to the NUV − r colour: ⋆blue cloud galaxies, ⋆green valley galaxies; ⋆ red sequence galaxies; ⋆ no NUV − r measurement available. |
2.3. Other archival data
To discuss the physical properties of the DP/MaNGA galaxies, we made use of different catalogues, such as the Reference Catalogue of Spectral Energy Distributions (RCSED, Chilingarian et al. 2017), which encompasses 800 299 galaxies at low and intermediate redshifts. For each, it offers spectrophotometric measurements from different surveys as well as value-added data such as K-correction, emission line flux measurements, gas-phase metallicity. Salim et al. (2016) analysed GALEX, SDSS, and WISE data and used them to build a catalogue that encompasses the stellar mass, dust attenuation, and star formation rate for ∼7 × 105 galaxies. They used a Chabrier initial mass function (IMF) (Chabrier 2003). Four galaxies out of the DP/MaNGA collection were not included in their dataset (i.e. G17, G24, G56, and G64). For these objects, we relied on the star formation rate estimates computed by Brinchmann et al. (2004) and available through the MPA-JHU DR7 release of spectrum measurements1. These latter SFR estimates are derived using a Kroupa initial mass function (Kroupa 2001), and this dataset also comprises stellar mass estimates based on fits to the photometry following Kauffmann et al. (2003b). As precised in Salim et al. (2016), a −0.025 dex offset is applied when comparing these different SFR estimates, to make the adjustment from the Kroupa to Chabrier IMF. We adopted the Salim et al. (2016) estimate as broadly as possible, since it includes 22 μm photometry, thus minimising possible dust extinction and emission biases.
2.4. MaNGA data products
We aim at deriving spatially-resolved as well as global properties of the DP/MaNGA galaxies. We use the final data cubes provided by the Data Reduction Pipeline (DRP, Law et al. 2016) that are logarithmic sampled and the maps provided by the Data Analysis Pipeline (DAP, Westfall et al. 2019). Briefly, each spectrum of the 3D data is fitted using the penalized PiXel-Fitting routine (pPXF, Cappellari & Emsellem 2004; Cappellari 2017): the stellar continuum is adjusted by fitting 49 families of stellar spectra from the MILES library (Falcón-Barroso et al. 2011) and then subtracted to the observed spectrum. The nebular emission lines in the resulting spectrum are fitted using a Gaussian function. The MaNGA DAP proposes two analysis methods to derive physical quantities: the Voronoi-binned maps for which a Voronoi binning scheme has been applied and has associated the summed flux to each spaxel belonging to the same spatial bin; the hybrid maps for which a similar Voronoi binning scheme has been applied for stellar properties but for which emission line measurements are proceeded spaxel-by-spaxel. We also exploited the stellar continuum measurements and the derived stellar mass density provided in the value-added catalogue Pipe3D for MaNGA DR17 (Sánchez et al. 2016b, 2018). To compute quantities such as specific star-formation rate, we use the resolved stellar mass measurements of Pipe3D, whose procedure does not rely on the same binning scheme. Therefore, we decided to work with the hybrid-scheme maps and spaxel-by-spaxel emission line measurements.
3. DP/MaNGA sample properties
3.1. Morphology
A visual inspection of the g, r, z images provided by the Legacy survey (Dey et al. 2019) reveals that our sample brings together a broad diversity of galaxy types, namely late-type galaxies (LTGs), elliptical galaxies and disrupted galaxies, which are most likely mergers. We display the Legacy survey snapshots in Figs. 3 and 4 and we show, for each galaxy, the corresponding MaNGA IFU footprint with a magenta hexagon. We present the morphological classification of the DP/MaNGA sample in Table A1 and add the morphological type of each galaxy in the top right of their snapshot in Figs. 3 and 4. As an additional morphology investigation, we computed a photometric diagnostic based on the Gini coefficient and the second moment of the galaxy’s brightest regions, M20. The resulting Gini–M20 diagram is shown on Fig. F.1. The majority of the DP/MaNGA galaxies is located in the region associated with elliptical, S0, and Sa galaxies.
Fig. 3. 69 × 69″ Legacy survey snapshots of some blue cloud DP/MaNGA galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8 < log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. The images of the remaining blue cloud galaxies are displayed on Fig. E1. |
Fig. 4. 69 × 69″ Legacy survey snapshots of some green valley and red sequence (red-framed) DP/MaNGA galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8 < log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. The images of the remaining green valley galaxies are displayed on Fig. E2. |
3.1.1. Methodology
Fischer et al. (2019) performed a Sérsic (as well as a Sérsic + an exponential) fit to the 2D surface brightness profiles for all MaNGA DR17 galaxies and provide photometric measurements. They used the python package PYMORPH2 and incorporated improvements compared to the fitting procedure, which are presented in Meert et al. (2015). We used their semi-minor over semi-major axis ratio (b/a) to compute the inclination angle i following:
where q0 is the intrinsic axial ratio of edge-on galaxies, set to q0 = 0.2 (Holmberg 1958). We made use of the companion MaNGA Morphology Deep Learning DR17 Morphology catalogue, which encompasses machine learning-based morphological classifications (Domínguez Sánchez et al. 2022). This catalogue covers MaNGA galaxies that were not processed in former bulge-disc decomposition catalogues based on SDSS DR7 photometry. We used the following galaxy type probabilities computed by Domínguez Sánchez et al. (2022): the T-Type for estimating the morphological type on the Hubble Sequence and PS0 for denoting the probability of detecting an S0 galaxy. We follow the recommended criteria to classify the galaxies of our sample as:
-
Late-Type Galaxies (LTGs): T-Type > 0 and P_LTG ≥ 0.5;
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Early-Type Galaxies (ETGs): T-Type ≤ 0 and
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S0: P_S0 > 0.5 and P_LTG < 0.5;
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Ellipticals (E): P_S0 ≤ 0.5 and P_LTG < 0.5.
-
We also manually classified G37 and G61 as mergers, based on its morphology for G37 and on its kinematics analysis for G61 (see Mazzilli Ciraulo et al. 2021).
3.1.2. Morphology of the DP/MaNGA galaxies
Figure 5 displays the morphology distribution of the 69 DP/MaNGA galaxies. We observe that the sample is dominated by late-type galaxies (58%) and we note that contrary to Maschmann et al. (2020), there is no significant excess of S0. This could be due to the fact that the DP/MaNGA are relatively close galaxies (with a median redshift of 0.0522), while distant S0 galaxies may correspond to unresolved LTGs. The control samples show a quite similar morphology distribution, even though they both encompass less S0 than the DP/MaNGA sample. Based on the Gini–M20 diagram presented on Fig. F.1, however, we notice that LTGS in the DP/MaNGA sample are predominantly classified as Sa galaxies. Maschmann et al. (2020) show that the DP feature is not related to the inclination of the galactic disc. The DP/MaNGA sample here has a mean inclination value of 54° and spans values between 24° and 84° (based on the r-band measurements from the MaNGA PyMorph DR17 catalogue and using Eq. (1)).
Fig. 5. Morphology distribution for the DP/MaNGA galaxies (in magenta). The filled histogram corresponds to the green-valley DP/MaNGA galaxies. The error bars represent the binomial errors. |
3.2. Mass–size relation and Sérsic index
Figure 6 shows the mass-size relation for the DP/MaNGA galaxies and the control samples. The stellar masses are from Salim et al. (2016), except for G17, G25, G56, and G64 whose estimates are taken from Kauffmann et al. (2003b). The half-light radius, Reff, values come from the NASA-Sloan Atlas catalogue (NSA)3. We superimposed the low-z relations from van der Wel et al. (2014). The fit based on the CS1 and CS2 measurements, shown as an orange dotted line, lies between these two relations and above the polynomial fit of the DP/MaNGA sample. For the DP/MaNGA galaxies, while most of these galaxies are classified as late-type galaxies, the derived best fit is closer to the early-type trend (), as presented by the magenta dotted line.
Fig. 6. Size–stellar mass distribution for the DP/MaNGA galaxies. The dashed lines correspond to the low-z relations proposed by van der Wel et al. (2014) ( for ETGs in red and for LTGs in blue). The colour-coding refers to the morphology: ⋆ETGs, that are ⋆ ellipticals, ⋆ S0; ⋆ mergers; ⋆ LTGs. The magenta dotted line refers to the relation found for the DP/MaNGA galaxies and the orange dotted line shows the best fit for the CS1 and CS2 combined. |
The DP/MaNGA galaxies exhibit a higher Sérsic index than the CS1 and CS2 galaxies, as shown in Fig. 7. This further supports our finding on the mass-size relation.
3.3. Environment
The datasets presented in Yang et al. (2007) and in Saulder et al. (2016) provide galaxy groups and enable us to know whether a galaxy is isolated or not. To discriminate from the different environments, we used the galaxy group sizes as defined in Blanton & Moustakas (2009): a poor group holds two to four objects, a rich group five to nine and a cluster ten or more. We took the classification from Saulder et al. (2016) when available and from Yang et al. (2007) for the sources with a redshift greater than 0.11. We show the environment distribution of the DP/MaNGA as well as the CS1 and CS2 galaxies in Fig. 8. The DP/MaNGA galaxies are mainly isolated and in poor groups, with quite a similar distribution to the CS1/CS2 galaxies. We note a small excess of sources without any neighbour compared to both CS1 and CS2, and fewer objects evolving in a rich group with respect to the CS2. This result is compatible with the findings of Maschmann et al. (2020) based on 5663 DP galaxies.
Fig. 7. Sérsic indices for the DP/MaNGA galaxies (in magenta). The Sérsic indices are taken from the MaNGA PyMorph DR17 photometric catalogue. The filled histogram corresponds to the green-valley DP/MaNGA galaxies. |
Fig. 8. Environment distribution for the DP/MaNGA galaxies (top). Distribution between isolated, central and satellite galaxies for the DP/MaNGA sample (bottom). The error bars show the binomial errors. The filled histogram corresponds to the green-valley DP/MaNGA galaxies. |
The bottom panel of Fig. 8 shows that most of the DP/MaNGA galaxies correspond to central galaxies of groups or clusters with a central-to-satellite ratio of 2.6; while 6 out of the 19 satellite DP/MaNGA galaxies are in the green valley. The DP/MaNGA sub-sample is fairly similar to the CS1 which has a central-to-satellite ratio of 2.3, but a bit more different from the CS2 that has a ratio of 1.7. When we consider the DPS (resp. NBCS), 17% (resp. 9%) of the satellite galaxies are in the green valley, supporting the fact that this excess of green satellite galaxies is real. Lastly, we note that while the central/satellite ratio in the green valley is similar for DP/MaNGA and DPS galaxies, the global DPS central/satellite ratio is of the order of 2.3, independently of the redshift range (to compare with 2.6 for the DP/MaNGA).
3.4. Star formation
Fig. 9. SFR ratio between the estimate within the fibre and the one for whole galaxy, taken from Brinchmann et al. (2004), for the DP/MaNGA galaxies. The filled histogram corresponds to the green-valley DP/MaNGA galaxies. |
Maschmann et al. (2020) discuss that late-type DP galaxies exhibit a central enhancement of their star formation activity with respect to their control sample. We performed the same analysis by computing the ratio of the SFR computed inside the SDSS 3″ fibre SFRfibre and the total SFR SFRtotal, provided by Brinchmann et al. (2004). Their SFRfibre estimate is based on emission line measurements and their SFRtotal is derived through an empirical aperture correction. For the DP/MaNGA sample, we did detect a global excess of central star formation enhancement, compared to the control samples, as shown in Fig. 9.
Fig. 10. Colour–sSFR diagram for the 61 DP/MaNGA galaxies with a NUV − r measurement. The sSFR is the specific star formation rate, defined as SFR/M⋆. The colour NUV − r is the K- and Galactic extinction-corrected value taken from the RCSED (Chilingarian et al. 2017) corrected for dust extinction. The median uncertainty for the DP/MaNGA sample is shown in the bottom-left. |
Salim (2014) showed that the green-valley galaxies, defined by their NUV − r colour, correspond mainly to galaxies in transition with intermediate specific star formation ratio (sSFR = SFR/M⋆). Figure 10 displays the NUV − r colour with respect to the sSFR for the DP/MaNGA galaxies. The NUV magnitude comes from Galaxy Evolution Explorer (GALEX, Martin et al. 2005; Morrissey et al. 2007) and the r magnitude is provided by the SDSS survey. For the sSFR, we use the estimates from Salim et al. (2016) when available, and those from Brinchmann et al. (2004), for the four galaxies that are not in S16. As specified in S16, there is no systematics between these estimates for star-forming galaxies. As discussed in Salim (2014), the NUV − r colour is much more correlated with sSFR than optical colours. The DP/MaNGA galaxies closely follow the distribution previously detailed in Salim (2014). Figure 11 displays the star-forming main sequence (SFMS, e.g. Whitaker et al. 2012; Speagle et al. 2014; Renzini & Peng 2015; Fraser-McKelvie et al. 2021). The DP/MaNGA galaxies are superimposed on the 2D histogram showing the distribution of the MaNGA galaxies that have a Salim et al. (2016) SFR estimate. The DP/MaNGA galaxies are consistent with the SFMS definitions from the literature. The locus of our defined blue cloud galaxies is not clearly different from the one of our defined green valley galaxies. Despite their red colour, the red sequence galaxies do not exhibit a lower SFR than some of the blue cloud or green valley galaxies at similar stellar masses, apart from G9, which corresponds to a quiescent object.
Fig. 11. SFR vs. stellar mass diagram. The DP/MaNGA are represented by coloured stars. The SFR and stellar masses are based on Salim et al. (2016), except for G17, G25, G56, and G64 (based on Brinchmann et al. 2004). The median uncertainty for the DP/MaNGA sample is shown in the top-right. The galaxies from the control samples are shown in grey. The underlying orange 2D histogram represents the galaxies from the MaNGA DR17 with corresponding measurements from Salim et al. (2016). |
3.5. Stellar indicator of age: 4000Å break
Figures 12 and 13 display the Dn(4000) maps, discussed by Kauffmann et al. (2003c) (hereafter K03). Here, it is defined as the ratio of the integral of the flux in the 4000−4100 Å range divided by the integral of the flux in the 3850−3950 Å range. This indicator quantifies the strength of the 4000-Å break, which traces a deficiency of hot, blue stars. As discussed by these authors, this index is a reliable age indicator for young stellar populations, namely those younger than 1 Gyr are characterised by an index of Dn(4000) < 1.5. Figure 12 shows that the blue cloud galaxies host (on average) younger stellar populations than their green valley and red sequence counterparts. The median Dn(4000) index value for the blue cloud is ∼1.46, with a standard deviation of 0.11. The red sequence galaxies have a median Dn(4000) index of ∼1.91, with a standard deviation of 0.12. For the green valley galaxies, the respective median and standard deviation are ∼1.74 and 0.17. The spatial distribution of Dn(4000), however, is not homogeneous among them. Some galaxies seem to host younger stars in their outskirts than in their inner regions (like G27 or G53), while some others show an opposite spatial trend (e.g. G22 or G34).
Fig. 12. Dn4000 of some DP/MaNGA galaxies of the blue cloud. The black ellipses represent one effective radius, Reff. The number in the top-left corner is the median Dn4000 value. The maps of the remaining blue cloud galaxies are displayed in Fig. G1. |
Fig. 13. Dn4000 of some DP/MaNGA galaxies of the green valley and red sequence (these latter are framed by a dark-red rectangle). The black ellipses represent one effective radius, Reff. The maps of the remaining green valley galaxies are displayed in Fig. G3. |
4. AGNs and star formation activity
Active galactic nuclei are one of the potential causes of quenching. This process is referred to as ‘AGN negative feedback’ and involves different mechanisms. Such AGN activity can trigger galactic winds and lead to gas removal, but it can also heat the interstellar medium, inject turbulence, and subsequently affect the star formation efficiency by preventing the gas from cooling. In this section, we disentangle the excitation source in the DP/MaNGA galaxies.
4.1. Resolved AGN fraction
4.1.1. Methodology
Optical emission lines can be excited by the radiation of star forming regions, but also by non-thermal sources, such as AGNs or shocks. Diagnostics based on line ratios such as [NII]/Hα and [OIII]/Hβ are widely used, since these ratios involved close emission lines and, thus, they are not significantly affected by dust extinction. The Hα emission is a tracer of young, hot stars and, therefore, of star-formation activity, but it is also contaminated by an AGN’s narrow line region. The observed Hα flux is thus over-estimating the SFR. Jin et al. (2021) proposed an approach to correct for the AGN’s contamination in the Hα emission that we followed. We computed the AGN fraction, fAGN, for each spaxel, based on the emission flux measurements provided by the DAP, which corresponds to the AGN’s contribution to the Hα flux (Jin et al. 2021). Following the 3D diagnostic diagram presented in Ji & Yan (2020), the P1 indicator is computed as:
Then, the AGN fraction is set such that:
In this way, the AGN fraction is within the range of 0 ≤ fAGN ≤ 1, depending on the value of P1. This relation was applied to all spaxels with a reliable emission (S/N > 3) in the emission lines required for the P1 parameter computation. Figures H1 and H2 show the resulting 2D maps of the fAGN value for the 69 DP/MaNGA galaxies. The fAGN maps do not show significant average differences between the blue, green, and red galaxies. If we look at the galaxies individually, however, the fAGN values closest to 1 (consistent with an important AGN contribution to the gas ionisation) are found either in green valley or red sequence galaxies. We defined two sub-groups among the green valley galaxies fAGN: ‘AGN galaxies’ are those with more than three-quarters of their detected spaxels between 0 and 0.3 Reff with a non-zero fAGN; ‘no-AGN’ galaxies comprise the rest.
4.1.2. Resolved AGN fraction and stellar population ages
Figure 14 shows the radial resolved AGN fraction values, colour-coded by the Dn(4000) measurements. Different trends can be seen, as described in the following. For the red sequence galaxies, hosting overall older stellar populations than the blue cloud and green valley galaxies, the AGN fraction values span a range between 0 and ∼0.8. We can also notice that only one of these four galaxies has fAGN measurements outer than 1.2 Reff. The emission lines of the three others are not reliably detected at a high radius. The blue cloud galaxies host older stellar populations mostly within 1 Reff. These populations seem to be associated with higher fAGN values. The green valley galaxy, which we have sub-divided into two sub-groups, shows different profiles: the ‘no-AGN’ group only has a few spaxels with an AGN fraction above 0.5, regardless of the radius; while the ‘AGN’ group exhibit higher AGN contributions at all radii.
Fig. 14. Spaxel-by-spaxel radial profiles of the AGN fraction fAGN for the DP/MaNGA galaxies. The top panels display the GV galaxies, with the left (resp. right) panel showing the profiles of the objects without (resp. with) any important AGN fraction in their inner parts. The bottom-left (resp. right) panel displays the blue (resp. red) galaxies. The dots are colour-coded with the Dn(4000) values, shown in Figs. 12 and 13. |
4.1.3. Nuclear activity and star formation concentration
Figure 15 displays the sSFR radial profiles for the blue, green and red galaxies, in the top-left panel. These values are derived from the SFR maps that we obtained from the MaNGA data, by using the extinction-corrected Hα emission, converted into SFR values using a Salpeter IMF, and the stellar mass maps from the Pipe3D value-added catalogue. In each panel, we show extinction-corrected profiles as solid lines and extinction- and AGN-contamination-corrected profiles as dashed lines.
Fig. 15. Radial profiles of sSFR (SFRHα/M⋆). Top left: blue cloud, green valley, and red sequence median radial profiles. Top right: median radial profiles for the GV galaxies for those with (resp. without) central AGN-like emission in orange (resp. in green). The panels of the second row display the same radial profiles but for the CS2. The solid lines show the sSFR values corrected for extinction only. The dashed lines display the sSFR values corrected for extinction and the AGN contribution. |
As expected, the blue cloud galaxies have higher sSFR values than the green and red galaxies, at all radii. Moreover, the difference between sSFR estimates uncorrected and corrected for AGN’s contribution is very small. The green and red galaxies have lower sSFR values and the AGN’s contribution correction decreases these values up to 0.15 dex. Among the green galaxies, the radial profiles differ between the ‘no-AGN’ and ‘AGN’ groups. The former group exhibits a constantly decreasing profile from ∼0.4 Reff, with similar sSFR values as the ‘AGN’ group at larger radii; the latter has a flatter profile. The green and red galaxies of the control sample have (on average) lower sSFR values, and a greater AGN contribution (the correction decreases the values up to 0.56 dex). The green valley sub-groups of the CS2 show different profiles compared to the DP/MaNGA sample. The sSFR values are overall lower, the AGN contribution correction is more important and especially high for the ‘no-AGN’ group. However, these interpretations can be misleading, because these groups encompass a very small number of galaxies. Figure 16 displays the central star formation excess computed as the ratio of SFR within 1 Reff (on the left panel) and within 0.5 Reff (on the right panel) over the total Hα-based SFR, for DP/MaNGA and CS2 galaxies. We separated the galaxies with and without AGN-like line ratios, as defined in Sect. 4.1.1. The ratios show that for most of the DP/MaNGA galaxies, the SFR within 1 Reff represents more than 50% of the Hα-based SFR. The distribution of the CS2 galaxies is different, with a SFR1 Reff corresponding mostly to ∼50 − 70% of the total SFR. The distributions of SFR1/2 Reff/SFR give a similar indication: SFR1/2 Reff represents a higher fraction of the total SFR in the DP/MaNGA galaxies as in the CS2 galaxies.
Fig. 16. Star formation excess computed within an elliptical radius of Reff (left) and 0.5 Reff (right). The DP/MaNGA galaxies with and without nuclear activity are compared with their counterparts from the CS2 control sample. |
4.2. Resolved BPT diagrams
Figure 17 display the so-called BPT diagnostic diagrams, introduced by Baldwin et al. (1981), and widely used to investigate the source of the gas ionisation. The four emission lines used in this diagnostic diagram are required to reach a minimal S/N of 3, so the lower number of detected spaxels away from the galaxy centre can be caused by a lack of ionised gas at large radii. However, this is also to be accounted in terms of the spatial coverage of the MaNGA, which is either out to 1.5Reff or 2.5Reff (Wake et al. 2017). In our case, the majority of the blue cloud galaxies are covered to 2.5Reff, while most of the green valley objects are covered to 1.5Reff.
Fig. 17. Spaxel-by-spaxel BPT diagrams. The empirical demarcation line between pure star formation and composite excitation is dashed (Kauffmann et al. 2003a). The solid curved line corresponds to the distinction between the excitation due to starbursts and that due to other mechanisms (Kewley et al. 2001). The empirical Seyfert-LI(N)ER line is the one from Schawinski et al. (2007). The colour coding indicates the distance to the centre, in units of Reff. |
The spaxels of the red sequence galaxies all lie above the ‘star-formation-only’ demarcation line, corresponding to composite, LI(N)ER, and Seyfert emission. The galaxies within the blue cloud mostly lie in the star-formation and composite regions, with a few spaxels (both at small and large radii) lying in the Seyfert and LI(N)ER parts of the diagram. We cannot exclude the possibility that there is no nuclear activity or shocks in the galaxies. The galaxies within the green valley, which we have separated into two categories, do not show many spaxels consistent with pure star formation in either sub-group. The ‘no-AGN’ galaxies mostly have composite measurements, while the ‘AGN galaxies’ exhibit Seyfert-like at different radii. These green valley galaxies exhibiting composite emission can contain a combination of star formation and a Seyfert nucleus, or a combination of star formation and LI(N)ER emission (e.g. Kewley et al. 2006). The BPT diagrams for the CS2 galaxies, following the same group division, are shown in Fig. I1. We note that the CS2 red galaxies show a non-negligible number of star-forming pixels in their outskirts.
5. Star formation histories
In this section, we investigate the star formation histories of the DP/MaNGA galaxies within the green valley. Kauffmann et al. (2003b) used the 4000 Å break strength and the Balmer absorption line index, HδA, as diagnostics of the past star formation histories of galaxies. Combining these two spectral features, they are able to distinguish galaxies with star formation dominated by bursts from those that have a more continuous star formation activity. These two stellar indicators are sensitive to bursts occurring during the past 1–2 Gyr. Figures 18 and 19 show the Dn(4000)/HδA and the Dn(4000)/log(EW(Hα)) planes for the spaxel measurements of the DP/MaNGA galaxies. All three measurements come from the DAP and are corrected for velocity dispersion. We only considered spectra where the mean g-band-weighted S/N per pixel is greater than 5, to avoid noisy measurements. The HδA index is based on the absorption line feature and computed after the subtraction of the best-fit emission-line model. The dashed lines on Figs. 18 and 19 indicate particular values discussed in the literature: Dn(4000) < 1.5 correspond to stellar ages of < 1 Gyr (Kauffmann et al. 2003b), while EW(Hα) is proposed as a class frontier below which galaxies are identified as retired (Cid Fernandes et al. 2011).
Fig. 18. Stellar age indicators for individual spaxels of the blue cloud and red sequence galaxies, represented in blue and red respectively, in different radial bins. The crosses at the bottom-left corner display the mean uncertainties on the spaxel measurements in the corresponding radial bin. The uncertainties on log[EW(Hα)] are 0.01 and 0.02 respectively. The brownish areas indicate regions where the galaxy can be identified as having undergone a burst in the past 2 Gyr. The darker shade denotes areas where galaxies are most likely currently experiencing or have recently experienced a burst that started within the last 0.1 Gyr (details in Kauffmann et al. 2003b). |
Fig. 19. Same as Figure 18 for green valley galaxies. The uncertainties on log[EW(Hα)] are 0.01 and 0.02, respectively. |
Most of the galaxies within the blue cloud have EW(Hα) > 3 Å. The Dn(4000) measurements span a range between 1.1 and 2, with higher values associated to lower HδA values. Some spaxels lie in the top-left corner of the Dn(4000)/HδA plane and overlap with the regions where galaxies experiencing star formation bursts in the past 2 Gyr lie. The galaxies within the red sequence typically exhibit high Dn(4000) values, with Dn(4000) indexes exceeding 1.5, and low HδA values, indicative of old stellar populations, as expected. The galaxies within the green valley have overall lower HδA values than the blue cloud galaxies, with no spaxel consistent with star formation burst younger than 2 Gyr. Most spaxels within 0–0.6 Reff of the galaxies show EW(Hα) values above 3 Å. At larger radii, Dn(4000) values are higher and EW(Hα) are lower than those of the blue cloud galaxies.
6. Discussion
In this section, we discuss how the DP/MaNGA galaxies can inform our understanding of the star formation quenching mechanisms.
6.1. Quenching inside-out
The galaxies within the green valley are redder that their blue counterparts as they host redder stellar populations. Some of these galaxies display obvious signature of non-thermal emission in their centre based on their emission line ratios, suggesting that star formation is not the only source of gas ionisation. Those galaxies host old stellar populations in their centre, but show EW(Hα) values larger than 3 Å between 0 and 0.3Reff, which likely excludes ionisation due to a smooth background of hot evolved stars (Belfiore et al. 2016). This finding is consistent with the findings of Bluck et al. (2020a,b), based on the study of ∼35 000 local galaxies, that quenching is essentially a global process, driven by the properties of the innermost regions within central galaxies. This process favours heating from AGNs as the most significant quenching mechanism in high-mass galaxies.
6.2. Quenching outside-in
Some of these DP/MaNGA galaxies (including some within the blue cloud) show older stellar populations in their outskirts compared to their innermost regions, suggesting that their star formation activity stops inwards. Outside-in quenching can be caused either by environment or gas exhaustion, as discussed in Peng et al. (2010) (see also Schawinski et al. 2014). Admittedly the DP/MaNGA galaxies are mainly classified as isolated or in small groups and do not show high asymmetry parameter (for a description of this morphological parameter, see Conselice 2003) values4. Only G49 exhibits A ∼ 1, while the median asymmetry value is 0.08 (with a standard deviation of 0.31) for the DP/MaNGA sample. However, detecting resulting tidal features or disturbances from recent minor-merger events require deep, high-resolution images (Kaviraj 2010), and galaxies can show low asymmetry values even though they have undergone a merger (Conselice 2003).
6.3. Minor mergers and other alternatives
The DP galaxies are characterised by a larger Sérsic index than the control samples matched in stellar mass and redshift, as well as by a central star formation rate excess. Various works (e.g. Bell 2008; Dimauro et al. 2022) have concluded that the presence of a bulge is a necessary, but insufficient criterion to quench star formation.
Classical bulges are typically thought to form through mergers (e.g. Weinzirl et al. 2009), with some violent processes followed by strong relaxation (see also Mihos & Hernquist 1994). Additionally, bulge growth can occur through multiple sequential merger scenarios proposed by Bournaud et al. (2007). This framework may apply to the DP/MaNGA galaxies, where DP features extend beyond their innermost region. However, further multi-component spectral analysis is required to determine whether each component can be associated to a galaxy (as in Mazzilli Ciraulo et al. 2021). These DP/MaNGA galaxies also align with findings by Lotz et al. (2008), where post-coalescence galaxies show more concentrated light distribution, while tidal features vanish.
On the other hand, Kaviraj et al. (2009) suggested that merger events onto early-type galaxies could lead to red NUV − r colour. They claim that intermediate NUV − r colour (3.8 < NUV − r < 5.5) can result from minor mergers with smaller mass ratios than 1:6 or from mergers with higher mass ratios but more than ∼1 Gyr old. Conversely, early-types with bluer colour (NUV − r < 3.8) can originate from mergers with mass ratios between 1:4 and 1:6, involving progenitors with gas fractions greater than ∼20%.
Furthermore, Martig et al. (2013) argued that only a few amounts of gas can be stabilised against star formation in galaxies with massive spheroids (the so-called morphological quenching). Indeed, high surface densities can allow the gas to fragment. This concentration can also be observed for bar-driven gas infall (e.g. Schinnerer et al. 2007; Kim & Elmegreen 2017). While the presence of bars in the DP/MaNGA sample is limited (approximately 16% according to the photometric value-added catalogue), the spatial resolution may hinder the detection of inner bars. However, we cannot exclude at this stage that the DP feature is due to a decoupled inner kinematic structure.
Double-peaked emission line profiles can also be produced by outflows. Their signatures include blue wings in ionised gas spectra. The DP/MaNGA galaxies exhibiting significant regions with double-peaked spectral features, as found by our fitting algorithm (see column 10 of Tab. A1), could be outflow candidates. A thorough kinematic analysis is necessary to confirm these candidates and characterise the amount of energy and momentum carried by the outflows, as well as their ability to quench star formation in their host galaxies.
7. Summary
We have studied the gas and star properties of 69 double-peaked galaxies selected from the Sloan Digital Sky Survey and observed as part of the Mapping Nearby Galaxies at APO (MaNGA) survey, with the aim to study the star formation quenching mechanisms at play within these galaxies. Based on their dust-attenuation corrected colour and magnitude, we categorised these galaxies into three groups: the blue cloud, the green valley, and the red sequence. We made use of the MaNGA maps to investigate the sources of gas ionisation using emission line ratio diagnostics, and compared them with stellar population age tracers, such as Dn(4000) and HδA indices. This enabled us to compare the star formation spatial distribution and the possible causes of quenching. Our main results are that the 69 DP/MaNGA galaxies have a higher fraction of galaxies within the green valley compared to the control samples. We find that these green valley galaxies exhibit:
-
a green colour due to mostly older stellar populations, on average;
-
emission line ratios consistent with a combination of star formation and nuclear activity;
-
no obvious sign of star formation burst within the past 2 Gyr.
It is important to note that these green valley galaxies are mostly isolated or in small groups; hence, we can favour internal processes rather than environment effects as the primary drivers of their quenching. Moreover, the strongest optical emission lines are detected up to 2.5 effective radii in most of these galaxies; thus, we can argue that their quenching is not due to gas depletion rather other physical mechanisms. To conclusively determine whether the double-peaked emission profiles are linked to potential quenching mechanisms, such as minor merger events or outflows, a thorough kinematic analysis (ideally at a higher spectral resolution) is required.
In a forthcoming paper, we will further study the double-peaked MaNGA galaxies by measuring their cold gas content using CO and HI observations to further explore the quenching mechanisms at play in these galaxies.
Acknowledgments
We thank the anonymous referee for comments and questions that have significantly improved this paper. B.MC. is thankful to François Caillet for technical help. This work was supported by the Programme National Cosmologie et Galaxies (PNCG) of CNRS/INSU with INP and IN2P3, co-funded by CEA and CNES. This research made use of Marvin, a core Python package and web framework for MaNGA data, developed by Brian Cherinka, José Sánchez-Gallego, Brett Andrews, and Joel Brownstein (Cherinka et al. 2019). https://sdss-marvin.readthedocs.io/en/stable/ Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org. SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional / MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group,Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University. The Legacy Surveys consist of three individual and complementary projects: the Dark Energy Camera Legacy Survey (DECaLS; Proposal ID #2014B-0404; PIs: David Schlegel and Arjun Dey), the Beijing-Arizona Sky Survey (BASS; NOAO Prop. ID #2015A-0801; PIs: Zhou Xu and Xiaohui Fan), and the Mayall z-band Legacy Survey (MzLS; Prop. ID #2016A-0453; PI: Arjun Dey). DECaLS, BASS and MzLS together include data obtained, respectively, at the Blanco telescope, Cerro Tololo Inter-American Observatory, NSF’s NOIRLab; the Bok telescope, Steward Observatory, University of Arizona; and the Mayall telescope, Kitt Peak National Observatory, NOIRLab. The Legacy Surveys project is honored to be permitted to conduct astronomical research on Iolkam Du’ag (Kitt Peak), a mountain with particular significance to the Tohono O’odham Nation. This project makes use of the MaNGA-Pipe3D dataproducts. We thank the IA-UNAM MaNGA team for creating this catalogue, and the Conacyt Project CB-285080 for supporting them.
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Appendix A: Properties of the DP/MaNGA galaxies
See Table A1.
The 69-galaxy DP/MaNGA sample.
Appendix B: MaNGA spectrum fitted with multiple components
Fig. B.1. Example of a fitted spectrum in the MaNGA cube of G17 using our multi-component procedure. The Legacy snapshot is shown top-left, with the MaNGA footprint in magenta and the location of the bin as a turquoise dot. In each other panel, we the emission lines with their double-Gaussian fit. Below each line we show the fit residuals. |
Appendix C: Colour correction for dust attenuation
Since we are mainly interested in the galaxies within the green valley, we perform a dust attenuation correction. Dusty star-forming galaxies can indeed contaminate the green valley if one uses observed colours, as has already been established (e.g. Gonçalves et al. 2012; Sodré et al. 2013). We follow a similar methodology as in de Sá-Freitas et al. (2022), but by using the flux measurements of the Balmer lines (Hα and Hβ) taken from the MaNGA DAP maps. The Balmer decrement maps are display in Figs. D1 and D2. We calculate the colour excess following Domínguez et al. (2013):
We assume the intrinsic Balmer decrement 2.87, corresponding to a gas temperature of T = 104K for case B recombination (Osterbrock & Ferland 2006). This colour excess is computed for each spaxel where both Hα and Hβ flux measurements have a S/N greater than 3. Then, we use E(B−V)stars = 0.44 E(B−V)gas. We finally can calculate the intrinsic magnitudes following Calzetti et al. (2000):
where mobs is the observed magnitude, k(λ) is the reddening curve at the given wavelength (at the central wavelength of the NUV, r or u filters in this work), and ⟨E(B-V)stars⟩ is the average colour excess for the galaxy we correct. The average error on intrinsic colour NUV − r for the DP/MaNGA sample is 0.15, with a standard deviation of 0.05.
Appendix D: Balmer decrement maps
Figures D1 and D2 display the 2D maps of the Balmer decrement (Hα/Hβ) for the DP/MaNGA galaxies. We use them to measure the colour excess and correct the NUV and r colours for dust attenuation.
Fig. D.1. Balmer decrement maps for the DP/MaNGA galaxies of the blue cloud. The black ellipses represent one effective radius, Reff. |
Fig. D.1. continued |
Fig. D.2. Balmer decrement maps for the DP/MaNGA galaxies of the green valley and red sequence (these latter framed with a dark-red rectangle). The black ellipses represent one effective radius, Reff. |
Appendix E: Legacy survey images
We display in Figs. E1 and E2 the g, r, z composite images of the blue cloud and green valley not shown in the main body of the article. These images illustrate the variety of morphologies within the DP/MaNGA sample.
Fig. E.1. 69x69″ Legacy survey snapshots of the remaining blue cloud galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8< log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. |
Fig. E.1. continued |
Fig. E.2. 69x69″ Legacy survey snapshots of the remaining green valley galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8< log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. |
Appendix F: Gini-M20 diagram
In Fig. F.1, we display the so-called Gini-M20 diagram for the DP/MaNGA galaxies, created using measurements obtained using STATMORPH5 (Rodriguez-Gomez et al. 2019). Table F.1 summarises the classification of the galaxies with reliable measurements.
Fig. F.1. Gini-M20 diagram, based on the r-band Legacy survey image. The orange line sets the division between merger candidates and normal Hubble types (Lotz et al. 2004). The black dotted line separates early-type (E, S0 and Sa) from late-type objects (Sb to Sd, as well as Irr) (Lotz et al. 2008). G49, a late-type galaxy, does not appear on this panel but has (-1.21,0.86) for coordinates, so lies in the “likely mergers” region. The DP/MaNGA galaxies are colour-coded according to their morphology: ⋆ETGs, whose ⋆ ellipticals and ⋆ S0; ⋆ mergers; ⋆ LTGs. |
The Gini coefficient measures the inhomogeneity of a galaxy’s light distribution. Lotz et al. (2004) introduced a diagnostic combining the Gini coefficient with the second moment of the galaxy’s brightest regions (M20) to distinguish between galaxies undergoing mergers and those that are not. We illustrate this diagnostic in Fig. F.1. Galaxies currently undergoing mergers appear on the left side of the Gini-M20 diagram, marked by a purple line (Lotz et al. 2008). After the merger has completed, galaxies typically move back to the right side of the diagram, where two distinct populations are observed: elliptical, S0, and Sa galaxies in the upper right, and irregular and spiral galaxies (Sb, Sc, Sd, or Irr) in the lower right (Lotz et al. 2008). These regions are delineated by a black dashed line. Combining this diagnostic with asymmetry, based on hydrodynamical simulations, allows sensitivity to merger timescales of approximately 200-400 Myr for major disk mergers and 60 Myr for minor mergers (Lotz et al. 2010).
Classification of the DP/MaNGA sample based on the Gini-M20 diagram.
Appendix G: Dn4000 index maps
We show in Figs. G2 and G3 the Dn(4000) index maps of the blue cloud and green valley not included in the main body of the article. We discuss this index as a stellar age indicator in Sect. 5.
Fig. G.1. Dn4000 of the remaining blue cloud galaxies. The black ellipses represent one effective radius, Reff. |
Fig. G.1. continued |
Fig. G.2. Dn4000 of the remaining green valley galaxies. The black ellipses represent one effective radius, Reff. |
Appendix H: fAGN individual maps and averaged trends
We estimate an averaged AGN fraction ⟨fAGN⟩, a root-mean-square σAGN and an error ϵAGN of this quantity for each of the galaxy sub-groups:
where Nspaxels is the number of spaxels considered to compute the averaged value within each galaxy group.
Hα-flux weighted AGN fraction statistics
Fig. H.1. 2D maps of the AGN fraction fAGN for the blue-cloud galaxies. The black ellipses represent one effective radius, Reff. |
Fig. H.1. continued |
Fig. H.2. Same as the previous figure but for the green-valley and red-sequence galaxies (these latter are framed by a dark-red rectangle). |
Appendix I: BPT diagrams for the CS2 sample
Figure I1 displays the BPT for the galaxies from our second control sample (CS2) organised in four categories as defined in Sect. 4.1.1 and in Fig. 17.
Fig. I.1. BPT diagrams for the galaxies of the CS2 sample. Left: GV galaxies with and without AGN-like central emission, respectively. Right: Blue-cloud and red-sequence galaxies. The colour indicates the distance to the centre, in units of Reff. |
All Tables
All Figures
Fig. 1. Colour–magnitude diagram for 61 DP/MaNGA galaxies (the eight others do not have a NUV − r colour measurement). Here, Mr is the r-band absolute magnitude. The colour NUV − r is taken from the RCSED catalogue and is K- and Galactic extinction-corrected (Chilingarian et al. 2017). Top panel: apparent NUV − r colour. The green dashed lines show the green valley definition as in Salim (2014). Bottom panel: NUV − r colour corrected for dust attenuation. In both panels, the contours represent the 7351 galaxies from the MaNGA DR17 with a NUV − r colour measurement in the RCSED catalogue. The shaded green dashed lines refer to the green valley definition as in Salim (2014), while the other dashed lines show our green valley definition after dust attenuation correction. |
|
In the text |
Fig. 2. Distribution in the M⋆ − z plane of the DP/MaNGA (colour-coded stars on left panel), CS1 (coloured dots on middle panel) and CS2 (coloured circles in right panel) galaxies. These three samples are respectively superimposed on the DPS distribution, the CS from Maschmann et al. (2020), and the whole MaNGA sample from DR17 (Bundy et al. 2015; Abdurro’uf et al. 2022). The bimodality of the MaNGA sample distribution is due to the survey design criteria. The colour coding refers to the NUV − r colour: ⋆blue cloud galaxies, ⋆green valley galaxies; ⋆ red sequence galaxies; ⋆ no NUV − r measurement available. |
|
In the text |
Fig. 3. 69 × 69″ Legacy survey snapshots of some blue cloud DP/MaNGA galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8 < log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. The images of the remaining blue cloud galaxies are displayed on Fig. E1. |
|
In the text |
Fig. 4. 69 × 69″ Legacy survey snapshots of some green valley and red sequence (red-framed) DP/MaNGA galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8 < log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. The images of the remaining green valley galaxies are displayed on Fig. E2. |
|
In the text |
Fig. 5. Morphology distribution for the DP/MaNGA galaxies (in magenta). The filled histogram corresponds to the green-valley DP/MaNGA galaxies. The error bars represent the binomial errors. |
|
In the text |
Fig. 6. Size–stellar mass distribution for the DP/MaNGA galaxies. The dashed lines correspond to the low-z relations proposed by van der Wel et al. (2014) ( for ETGs in red and for LTGs in blue). The colour-coding refers to the morphology: ⋆ETGs, that are ⋆ ellipticals, ⋆ S0; ⋆ mergers; ⋆ LTGs. The magenta dotted line refers to the relation found for the DP/MaNGA galaxies and the orange dotted line shows the best fit for the CS1 and CS2 combined. |
|
In the text |
Fig. 7. Sérsic indices for the DP/MaNGA galaxies (in magenta). The Sérsic indices are taken from the MaNGA PyMorph DR17 photometric catalogue. The filled histogram corresponds to the green-valley DP/MaNGA galaxies. |
|
In the text |
Fig. 8. Environment distribution for the DP/MaNGA galaxies (top). Distribution between isolated, central and satellite galaxies for the DP/MaNGA sample (bottom). The error bars show the binomial errors. The filled histogram corresponds to the green-valley DP/MaNGA galaxies. |
|
In the text |
Fig. 9. SFR ratio between the estimate within the fibre and the one for whole galaxy, taken from Brinchmann et al. (2004), for the DP/MaNGA galaxies. The filled histogram corresponds to the green-valley DP/MaNGA galaxies. |
|
In the text |
Fig. 10. Colour–sSFR diagram for the 61 DP/MaNGA galaxies with a NUV − r measurement. The sSFR is the specific star formation rate, defined as SFR/M⋆. The colour NUV − r is the K- and Galactic extinction-corrected value taken from the RCSED (Chilingarian et al. 2017) corrected for dust extinction. The median uncertainty for the DP/MaNGA sample is shown in the bottom-left. |
|
In the text |
Fig. 11. SFR vs. stellar mass diagram. The DP/MaNGA are represented by coloured stars. The SFR and stellar masses are based on Salim et al. (2016), except for G17, G25, G56, and G64 (based on Brinchmann et al. 2004). The median uncertainty for the DP/MaNGA sample is shown in the top-right. The galaxies from the control samples are shown in grey. The underlying orange 2D histogram represents the galaxies from the MaNGA DR17 with corresponding measurements from Salim et al. (2016). |
|
In the text |
Fig. 12. Dn4000 of some DP/MaNGA galaxies of the blue cloud. The black ellipses represent one effective radius, Reff. The number in the top-left corner is the median Dn4000 value. The maps of the remaining blue cloud galaxies are displayed in Fig. G1. |
|
In the text |
Fig. 13. Dn4000 of some DP/MaNGA galaxies of the green valley and red sequence (these latter are framed by a dark-red rectangle). The black ellipses represent one effective radius, Reff. The maps of the remaining green valley galaxies are displayed in Fig. G3. |
|
In the text |
Fig. 14. Spaxel-by-spaxel radial profiles of the AGN fraction fAGN for the DP/MaNGA galaxies. The top panels display the GV galaxies, with the left (resp. right) panel showing the profiles of the objects without (resp. with) any important AGN fraction in their inner parts. The bottom-left (resp. right) panel displays the blue (resp. red) galaxies. The dots are colour-coded with the Dn(4000) values, shown in Figs. 12 and 13. |
|
In the text |
Fig. 15. Radial profiles of sSFR (SFRHα/M⋆). Top left: blue cloud, green valley, and red sequence median radial profiles. Top right: median radial profiles for the GV galaxies for those with (resp. without) central AGN-like emission in orange (resp. in green). The panels of the second row display the same radial profiles but for the CS2. The solid lines show the sSFR values corrected for extinction only. The dashed lines display the sSFR values corrected for extinction and the AGN contribution. |
|
In the text |
Fig. 16. Star formation excess computed within an elliptical radius of Reff (left) and 0.5 Reff (right). The DP/MaNGA galaxies with and without nuclear activity are compared with their counterparts from the CS2 control sample. |
|
In the text |
Fig. 17. Spaxel-by-spaxel BPT diagrams. The empirical demarcation line between pure star formation and composite excitation is dashed (Kauffmann et al. 2003a). The solid curved line corresponds to the distinction between the excitation due to starbursts and that due to other mechanisms (Kewley et al. 2001). The empirical Seyfert-LI(N)ER line is the one from Schawinski et al. (2007). The colour coding indicates the distance to the centre, in units of Reff. |
|
In the text |
Fig. 18. Stellar age indicators for individual spaxels of the blue cloud and red sequence galaxies, represented in blue and red respectively, in different radial bins. The crosses at the bottom-left corner display the mean uncertainties on the spaxel measurements in the corresponding radial bin. The uncertainties on log[EW(Hα)] are 0.01 and 0.02 respectively. The brownish areas indicate regions where the galaxy can be identified as having undergone a burst in the past 2 Gyr. The darker shade denotes areas where galaxies are most likely currently experiencing or have recently experienced a burst that started within the last 0.1 Gyr (details in Kauffmann et al. 2003b). |
|
In the text |
Fig. 19. Same as Figure 18 for green valley galaxies. The uncertainties on log[EW(Hα)] are 0.01 and 0.02, respectively. |
|
In the text |
Fig. B.1. Example of a fitted spectrum in the MaNGA cube of G17 using our multi-component procedure. The Legacy snapshot is shown top-left, with the MaNGA footprint in magenta and the location of the bin as a turquoise dot. In each other panel, we the emission lines with their double-Gaussian fit. Below each line we show the fit residuals. |
|
In the text |
Fig. D.1. Balmer decrement maps for the DP/MaNGA galaxies of the blue cloud. The black ellipses represent one effective radius, Reff. |
|
In the text |
Fig. D.1. continued |
|
In the text |
Fig. D.2. Balmer decrement maps for the DP/MaNGA galaxies of the green valley and red sequence (these latter framed with a dark-red rectangle). The black ellipses represent one effective radius, Reff. |
|
In the text |
Fig. E.1. 69x69″ Legacy survey snapshots of the remaining blue cloud galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8< log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. |
|
In the text |
Fig. E.1. continued |
|
In the text |
Fig. E.2. 69x69″ Legacy survey snapshots of the remaining green valley galaxies. The corresponding MaNGA IFU footprint in magenta and the morphological type are shown for each source. The orange-framed galaxies are the ones lying in the transition zone, according to their sSFR (−11.8< log(sSFR) < − 10.8). The galaxies are sorted by redshift, from left to right, top to bottom. |
|
In the text |
Fig. F.1. Gini-M20 diagram, based on the r-band Legacy survey image. The orange line sets the division between merger candidates and normal Hubble types (Lotz et al. 2004). The black dotted line separates early-type (E, S0 and Sa) from late-type objects (Sb to Sd, as well as Irr) (Lotz et al. 2008). G49, a late-type galaxy, does not appear on this panel but has (-1.21,0.86) for coordinates, so lies in the “likely mergers” region. The DP/MaNGA galaxies are colour-coded according to their morphology: ⋆ETGs, whose ⋆ ellipticals and ⋆ S0; ⋆ mergers; ⋆ LTGs. |
|
In the text |
Fig. G.1. Dn4000 of the remaining blue cloud galaxies. The black ellipses represent one effective radius, Reff. |
|
In the text |
Fig. G.1. continued |
|
In the text |
Fig. G.2. Dn4000 of the remaining green valley galaxies. The black ellipses represent one effective radius, Reff. |
|
In the text |
Fig. H.1. 2D maps of the AGN fraction fAGN for the blue-cloud galaxies. The black ellipses represent one effective radius, Reff. |
|
In the text |
Fig. H.1. continued |
|
In the text |
Fig. H.2. Same as the previous figure but for the green-valley and red-sequence galaxies (these latter are framed by a dark-red rectangle). |
|
In the text |
Fig. I.1. BPT diagrams for the galaxies of the CS2 sample. Left: GV galaxies with and without AGN-like central emission, respectively. Right: Blue-cloud and red-sequence galaxies. The colour indicates the distance to the centre, in units of Reff. |
|
In the text |
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