J/MNRAS/513/389 SF-S0 galaxies study with SDSS-MaNGA (Rathore+, 2022)
Star-forming S0 Galaxies in SDSS-MaNGA: fading spirals or rejuvenated S0s?
Rathore H., Kumar K., Mishra P.K., Wadadekar Y., Bait O.
<Mon. Not. R. Astron. Soc. 513, 389-404 (2022)>
=2022MNRAS.513..389R 2022MNRAS.513..389R (SIMBAD/NED BibCode)
ADC_Keywords: Galaxies, nearby ; Morphology ; Star Forming Region ; Photometry ;
Spectroscopy ; H I data ; Combined data ; Positional data ;
Redshifts ; Stars, masses ; Optical ; Infrared ; Ultraviolet
Keywords: galaxies: evolution - galaxies: star formation - galaxies: structure
Abstract:
We investigate the origin of rare star formation in an otherwise
red-and-dead population of S0 galaxies, using spatially resolved
spectroscopy. Our sample consists of 120 low redshift (z < 0.1)
star-forming S0 (SF-S0) galaxies from the SDSS-IV MaNGA DR15. We have
selected this sample after a visual inspection of deep images from the
DESI Legacy Imaging Surveys DR9 and the Subaru/HSC-SSP survey PDR3 to
remove contamination from spiral galaxies. We also construct two
control samples of star-forming spirals (SF-Sps) and quenched S0s
(Q-S0s) to explore their evolutionary link with the star-forming S0s.
To study star formation at resolved scales, we use dust-corrected
Hα luminosity and stellar density (Σ*) maps to construct
radial profiles of star formation rate (SFR) surface density
(ΣSFR) and specific SFR (sSFR). Examining these radial profiles,
we find that star formation in SF-S0s is centrally dominated as
opposed to disc- dominated star formation in spirals. We also compared
various global (size-mass relation, bulge-to-total luminosity ratio)
and local (central stellar velocity dispersion) properties of SF-S0s
to those of the control sample galaxies. We find that SF-S0s are
structurally similar to the quenched S0s and are different from
star-forming spirals. We infer that SF-S0s are unlikely to be fading
spirals. Inspecting stellar and gas velocity maps, we find that more
than 50 per cent of the SF-S0 sample shows signs of recent galaxy
interactions such as kinematic misalignment, counter-rotation, and
unsettled kinematics. Based on these results, we conclude that in our
sample of SF-S0s, star formation has been rejuvenated, with minor
mergers likely to be a major driver.
Description:
In this work, we study star-forming S0-type galaxies at low redshift
(z < 0.1), using Integral Field Spectroscopy (IFS) data from the Sloan
Digital Sky Survey's Mapping Nearby Galaxies at APO (SDSS-MaNGA; Bundy
et al. 2015ApJ...798....7B 2015ApJ...798....7B; Blanton et al. 2017AJ....154...28B 2017AJ....154...28B) survey
and and have been processed with the Pipe3D IFS data-processing
pipeline (Sanchez et al. 2016RMxAA..52...21S 2016RMxAA..52...21S, 2016RMxAA..52..171S 2016RMxAA..52..171S,
section 3 Data cube processing). The MaNGA survey provides us with
spatially resolved spectroscopy of a galaxy, thus enabling us to study
star formation in these galaxies in a spatially resolved fashion. This
will help us uncover the site and spatial extent of star formation in
these objects. We also compare the resolved and global properties of
star-forming S0s to a control sample of star-forming spirals SF-SPs
and the typical quenched population QSOs of S0s. Such a comparison
might connect this elusive class of objects to their progenitor
population, (i.e refer to section introduction section).
We provide one table peer sample, as explained in the section 2 Sample
selection and characterization, we select select the SF-S0s, SF-Sps,
and Q-S0s directly by using morphological types of each galaxies from
MaNGA DR15 deep-learning catalogue (ischer et al. 2019MNRAS.483.2057F 2019MNRAS.483.2057F,
Cat. J/MNRAS/483/2057; Dominguez Sanchez et al. 2018MNRAS.476.3661D 2018MNRAS.476.3661D,
Cat. J/MNRAS/476/3661) and with criteria based on the specific SFR
(which is defined as the SFR per unit stellar mass) obtained from
stellar population synthesis, instead of using colour as an
(imperfect) proxy for star formation (i.e equations 1 and 2 of the
section 2.1 Sample overview and basic selection criteria). For the
three galaxies groups, see respectively the three subsections 2.2
Sample of star-forming S0s (SF-S0s), 2.3 Control sample of quenched
S0s (Q-S0s) and 2.4 Control sample of star-forming spirals (SF-Sps).
Next, density maps, radial profiles and mean values of the three
samples were computed via data cube Pipe3D processing (i.e see section
3). Then in tableb1.dat (SF-S0s), tableb2.dat (Q-S0s) and tableb3.dat
(SF-Sps) we provide morphology, stellar mass, SFR and strucural
parameters. Refering to stellar velocity and Hα gas velocity
maps and kinematic analysis in sections 4 Results and 5.2 Kinematic
properties, we compute SF-S0 kinametics categories.
File Summary:
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FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
tableb1.dat 78 120 Star-forming lenticular S0 galaxy sample
tableb2.dat 76 227 Quenched lenticular S0 galaxy control sample
tableb3.dat 71 1468 Star-forming spirals galaxy control sample
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See also:
J/MNRAS/483/2057 : SDSS-IV MaNGA Morphological Catalogues (Fischer+, 2019)
J/MNRAS/476/3661 : Morphology of SDSS galaxies (Dominguez+, 2018)
J/ApJS/186/427 : Detailed morphology of SDSS galaxies (Nair+, 2010)
II/294 : The SDSS Photometric Catalog, Release 7
(Adelman-McCarthy+, 2009)
J/AJ/154/86 : MaNGA catalog, DR15 (Wake+, 2017)
VII/292 : DESI Legacy Imaging Surveys DR8 photometric redshifts
(Duncan, 2022)
https://www.legacysurvey.org/viewer/#IC 1572 : DESI Legacy surveys images
https://www.sdss4.org/dr16/manga/manga-data
/manga-pipe3d-value-added-catalog/ : Full MaNGA Pipe3D catalog
https://www.sdss4.org/dr15/manga/marvin/: SDSS-MaNGA web interface MARVIN
Byte-by-byte Description of file: tableb1.dat
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Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 10 A10 --- ID Plate ID and IFU bundle ID of the MaNGA
datacube (PLATEIFU)
12- 19 F8.4 deg RAdeg Right Ascension (J2000) (RA)
21- 27 F7.4 deg DEdeg Declination (J2000) (DEC)
29- 33 F5.2 --- TType Hubble TType value (TTYPE) (G1)
35- 38 F4.2 --- PS0 Measure of the probability of a galaxy being
an S0 as opposed to being an elliptical
(P_S0) (G1)
40- 45 F6.4 --- z SDSS redshift (z) (G2)
47- 52 F6.3 [Sun] logM* Logarithm of the stellar mass of the galaxy
relative to solar mass (log_M) (G2)
54- 58 F5.2 [Msun/yr] logSFR Logarithm of the star-formation rate of
the galaxy (logSFR) (G2)
60- 63 F4.2 arcsec Re Structural parameter half-light semi-major
axis (Re) (G3)
65- 68 F4.2 --- B/A Axis ratio semi-minor/semi-major (B/A) (G3)
70- 75 F6.2 deg PA [-88.37/88.98] Position angle (G3)
77- 78 I2 --- Class ? Kinematic classification of the galaxy
based on visual inspection of stellar and
Hα velocity maps (Kine_class) (1)
--------------------------------------------------------------------------------
Note (1): We inspect stellar velocity and Hα gas velocity maps of SF-S0s
using SDSS-MARVIN which a tool for visualizing MaNGA IFS data
(Cherinka et al. 2019AJ....158...74C 2019AJ....158...74C). Based on this visual
inspection, we divide the SF-S0s into four categories based on their
kinematic maps as follows:
0 = Regular means stellar and Hα velocity maps show clean
rotation and both maps are aligned, there are 48 such objects in
our sample
1 = Disturbed means either one or both of the stellar and Hα
velocity maps are disturbed, there are 56 such objects in our
sample
2 = Misaligned means stellar and Hα velocity maps show
rotation, but the axis of rotation of stars and gas seems
to be misaligned, there are three such objects in our sample
3 = Counter-rotating means stellar and Hα velocity maps show
rotation, but the axis of rotation of stars and gas seems
antialigned, there are 11 such objects in our sample
-1 = Bad velocity data, there are 2 such objects in our sample
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Byte-by-byte Description of file: tableb2.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 10 A10 --- ID Plate ID and IFU bundle ID of the MaNGA
datacube (PLATEIFU)
12- 19 F8.4 deg RAdeg Right Ascension (J2000) (RA)
21- 27 F7.4 deg DEdeg Declination (J2000) (DEC)
29- 33 F5.2 --- TType Hubble TType value (TTYPE) (G1)
35- 38 F4.2 --- PS0 Measure of the probability of a galaxy being
an S0 as opposed to being an elliptical
(P_S0) (G1)
40- 45 F6.4 --- z SDSS redshift (z) (G2)
47- 52 F6.3 [Sun] logM* Logarithm of the stellar mass of the galaxy
relative to solar mass (log_M) (G2)
54- 58 F5.2 [Msun/yr] logSFR Logarithm of the star-formation rate of
the galaxy (logSFR) (G2)
60- 64 F5.2 arcsec Re Structural parameter half-light semi-major
axis (Re) (G3)
66- 69 F4.2 --- B/A Axis ratio semi-minor/semi-major (B/A) (G3)
71- 76 F6.2 deg PA [-89.54/89.59] Position angle (G3)
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Byte-by-byte Description of file: tableb3.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 11 A11 --- ID Plate ID and IFU bundle ID of the MaNGA
datacube (PLATEIFU)
13- 20 F8.4 deg RAdeg Right Ascension (J2000) (RA)
22- 28 E7.4 deg DEdeg Declination (J2000) (DEC)
30- 33 F4.2 --- TType Hubble TType value (TTYPE) (G1)
35- 40 F6.4 --- z SDSS redshift (z) (G2)
42- 47 F6.3 [Sun] logM* Logarithm of the stellar mass of the galaxy
relative to solar mass (log_M) (G2)
49- 53 F5.2 [Msun/yr] logSFR Logarithm of the star-formation rate of
the galaxy (logSFR) (G2)
55- 59 F5.2 arcsec Re Structural parameter half-light semi-major
axis (Re) (G3)
61- 64 F4.2 --- B/A Axis ratio semi-minor/semi-major (B/A) (G3)
66- 71 F6.2 deg PA [-89.85/89.8] Position angle (G3)
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Global notes:
Note (G1): For obtaining the morphological type of each galaxy, we use the MaNGA
DR15 deep-learning catalogue (Fischer et al. 2019MNRAS.483.2057F 2019MNRAS.483.2057F,
Cat. J/MNRAS/483/2057; Dominguez Sanchez et al. 2018MNRAS.476.3661D 2018MNRAS.476.3661D,
Cat. J/MNRAS/476/3661), specifically the columns 'TType' and 'PS0'.
The former is the morphological Hubble TType (De Vaucouleurs
1963ApJS....8...31D 1963ApJS....8...31D; Nair & Abraham 2010ApJS..186..427N 2010ApJS..186..427N,
Cat. J/ApJS/186/427), and the latter is the probability of an object
being an S0 as opposed to being a pure elliptical. DL15
classifications of the MaNGA galaxies are based on SDSS DR15 images
(Aguado et al. 2019ApJS..240...23A 2019ApJS..240...23A). Their Convolutional Neural
Networks (CNNs) are trained on two galaxy visual classification
catalogues based on SDSS DR7 (Abazajian et al. 2009ApJS..182..543A 2009ApJS..182..543A,
Cat. II/294) images - Nair & Abraham (2010ApJS..186..427N 2010ApJS..186..427N,
Cat. J/ApJS/186/427) and Galaxy Zoo-2. DL15 claims a performance
of > 90 per cent on the classifications provided by the deep-learning
algorithm, (i.e refer to section 2.1 Sample overview and basic
selection criteria).
Note (G2): All the galaxies across the three samples we construct were observed
by the SDSS - MaNGA IFS survey (Bundy et al. 2015ApJ...798....7B 2015ApJ...798....7B;
Blanton et al. 2017AJ....154...28B 2017AJ....154...28B) and have been processed with the
Pipe3D IFS data-processing pipeline (Sanchez et al.
2016RMxAA..52...21S 2016RMxAA..52...21S, 2016RMxAA..52..171S 2016RMxAA..52..171S). For SFR, stellar mass, and
redshift z, we use the GSWLC-A2 (GALEX-SDSS-WISE LEGACY CATALOG,
Salim et al. 2016ApJS..227....2S 2016ApJS..227....2S; Salim et al. 2018ApJ...859...11S 2018ApJ...859...11S).
SFR and stellar mass are computed in the Salim catalogues by
modelling the ultraviolet UV, optical and mid infrared IR broad-band
spectral energy distribution. We use only those objects that have a
SED flag = OK in the Salim catalogue. This criterion excludes
galaxies that show broad emission lines, characteristic of
broad-line AGNs.
Since we are interested in studying nearby galaxies, we consider only
those galaxies that have z < 0.1, (i.e refer to section 2.1 Sample
overview and basic selection criteria). For SF-S0 sample, typical
errors (median across all galaxies) Δlog(M*/M☉) = 0.04,
Δlog(SFR) = 0.12. For Q-S0 sample, typical errors (median
across all galaxies) Δlog(M*/M☉) = 0.02,
Δlog(SFR) = 0.61. For SF-Sp sample, typical errors (median
across all galaxies) Δlog(M*/M☉) = 0.04,
Δlog(SFR) = 0.08.
Note (G3): For structural parameters as half light semimajor axis Re, axial
ratio B/A, and position angle PA, we use the r-band PyMorph
(Vikram et al. 2010MNRAS.409.1379V 2010MNRAS.409.1379V) single Sersic fits (Fischer et
al. 2019MNRAS.483.2057F 2019MNRAS.483.2057F, Cat. J/MNRAS/483/2057, PM15) for galaxies
belonging to SF-S0, SF-Sp, and Q-S0 samples. Fits are performed in
PM15 using SDSS DR15 images, (i.e refer to section 5.2 Kinematic
properties). For SF-S0 sample, typical errors (median across all
galaxies) ΔRe = 0.03 arcsec, ΔB/A = 0.004 and
ΔPA = 0.53 degrees. For Q-S0 sample, typical errors (median
across all galaxies) ΔRe = 0.04 arcsec, ΔB/A = 0.002
and ΔPA = 0.25 degrees. For SF-Sp sample, typical errors
(median across all galaxies) ΔRe = 0.05 arcsec,
ΔB/A = 0.002 and ΔPA = 0.28 degrees.
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History:
From electronic version of the journal
(End) Luc Trabelsi [CDS] 19-Nov-2024