J/MNRAS/518/286 Metallicity maps diagnostic in AMUSING++ galaxies (Li+, 2023)
Spatial metallicity distribution statistics at ≲100 pc scales in the AMUSING++
nearby galaxy sample.
Li Z., Wisnioski E., Mendel J.T., Krumholz M.R., Kewley L.J.,
Lopez-coba C., Sanchez S.F., Anderson J.P., Galbany L.
<Mon. Not. R. Astron. Soc. 518, 286 (2023)>
=2023MNRAS.518..286L 2023MNRAS.518..286L (SIMBAD/NED BibCode)
ADC_Keywords: Galaxies, nearby ; Interstellar medium ; Spectroscopy ; Optical ;
Positional data ; Combined data ; Galaxies, radius ;
Star Forming Region
Keywords: galaxies: abundances - galaxies: ISM
Abstract:
We analyse the spatial statistics of the 2D gas-phase oxygen abundance
distributions in a sample of 219 local galaxies. We introduce a new
adaptive binning technique to enhance the signal-to-noise ratio of
weak lines, which we use to produce well-filled metallicity maps for
these galaxies. We show that the two-point correlation functions
computed from the metallicity distributions after removing radial
gradients are in most cases well-described by a simple
injection-diffusion model. Fitting the data to this model yields the
correlation length lcorr, which describes the characteristic
interstellar medium (ISM) mixing length-scale. We find typical
correlation lengths lcorr ∼ 1 kpc, with a strong correlation between
lcorr and stellar mass, star formation rate (SFR), and effective
radius, and a weak correlation with Hubble type. Two galaxies in the
sample show significantly larger lcorr, and both prove to be
interacting or merging systems. We show that the trend of lcorr with
SFR can be reproduced by a simple transport + feedback model of ISM
turbulence at high SFR, and plausibly also at low SFR if dwarf galaxy
winds have large mass-loading factors. We also report the first
measurements of the injection width that describes the initial radii
over which supernova remnants deposit metals. Inside this radius the
metallicity correlation function is not purely the product of a
competition between injection and diffusion. We show that this size
scale is generally smaller than 60 pc.
Description:
In this paper, we extend the analysis techniques developed in Li et
al. (2021MNRAS.504.5496L 2021MNRAS.504.5496L) which basic statistical tool proposed in
Krumholz et al. (2018MNRAS.475.2236K 2018MNRAS.475.2236K, KT18) (i.e extracting more
information from metallicity maps with model based on stochastically
forced diffusion that predicts the two-point correlation functions of
metallicity fields caused by the competition between chemical mixing
and metal production). We focus on higher spatial resolution and
larger sample sizes, constrain shape of the metallicity correlation
and metal injection as well as transport through the ISM by studying
dwarf galaxies with low M* and SFR from AMUSING++ compilation
(Lopez-Coba et al. 2020AJ....159..167L 2020AJ....159..167L, Cat. J/AJ/159/167) providing
much higher spatial resolution than CALIFA but a much larger and more
diverse galaxy sample than PHANGS-MUSE.
As exposed in section 2, MUSE is an IFU at the VLT having a wavelength
coverage from 4650 to 9300 Å, and achieves a spectral resolution of
1750 (at 4650 Å) and 3750 (at 9300 Å). The combined spectral and
spatial resolution provides unique opportunities to explore the
elemental abundance distribution in galaxies. AMUSING++ comprises the
largest compilation of nearby galaxies (532 galaxies) observed by MUSE
where a majority of these come from AMUSING (Galbany et al.
2016MNRAS.455.4087G 2016MNRAS.455.4087G). (i.e data analysis/reduction pipeline details in
section 2). As explained in section 3, among the AMUSING++ full sample
we apply criteria allowing us to do accurate analysis, we are left
with a sample of 219 galaxies (i.e see figure 1 sect.2) out of the 447
with which we started.
As fully exposed in section 3 and 4, output of our analysis pipeline
is a set of posterior PDFs for the two-dimensional parameters that
characterize our parametric model such as injection width winj that
characterizes the size of the region into which metals are first
injected by supernovae (SNe) and the correlation length lcorr that
characterizes the strength of the mixing in the ISM that occurs after
the metals are injected. Results are presented in table1.dat with
compiled physical properties such as position angles, axis ratios,
distances, effectives radius, masses and SFRs, computed FMWH of PSF
and spatial resolution of maps for each 219 AMUSING++ nearby galaxies
in our sample (i.e see section 4 and 5).
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table1.dat 113 219 *Global properties of AMUSING++ nearby galaxy
sample
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Note on table1.dat: For cases where one of our fit parameters is not
well-constrained (see Section 4) we only report the 86th percentile value as
an upper limit (e.g. winj of NGC 1483). Columns (2)-(6) , (i.e PA, b/a, D, Re
, PSF) and (8) (i.e logM*) are from Lopez-Coba et al. (2020AJ....159..167L 2020AJ....159..167L,
Cat. J/AJ/159/167) and Sanchez et al. (2022ApJS..262...36S 2022ApJS..262...36S,
Cat. J/ApJS/262/36). The Re values are r-band half-light radii derived from an
isophotal analysis. The SFR values are derived from dust-corrected Hα
(Sanchez et al. 2021RMxAA..57....3S 2021RMxAA..57....3S).
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See also:
J/A+A/594/A36 : CALIFA Survey DR3 list of galaxies (Sanchez+, 2016)
J/ApJ/903/52 : MaNGA; parameters of 668 galaxies (Sanchez-Menguiano+, 2020)
J/ApJ/887/80 : Gas phase oxygen abundances for HII regions (Kreckel+, 2019)
J/ApJS/262/36 : SDSS-IV MaNGA: pyPipe3D data for 10000 galaxies (Sanchez+,2022)
J/ApJS/217/12 : S7 observations with WiFeS of active galaxies (Dopita+, 2015)
J/AJ/159/167 : AMUSING++ nearby galaxy compilation. I. Sample
(Lopez-Coba+, 2020)
J/AJ/136/2782 : Star formation efficiency in nearby galaxies (Leroy+, 2008)
J/AJ/136/2563 : HI Nearby Galaxy Survey, THINGS (Walter+, 2008)
Byte-by-byte Description of file: table1.dat
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Bytes Format Units Label Explanations
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1- 20 A20 --- Name AMUSING++ name (name)
22- 24 I3 deg PA Position angle (PA)
26- 30 F5.3 --- b/a Axial ratio (b2a)
32- 36 F5.1 Mpc D Distance (D)
38- 42 F5.2 kpc Re The r-band effective radius (Re)
44- 47 I4 pc PSF FWHM of physical PSF (PSF_pc)
49- 53 I5 pc ResMed Median spatial resolution of the binned
maps (resmedpc)
55- 60 F6.3 [Msun] log(M*) Stellar mass (logMstar)
62- 66 F5.3 [Msun] e_log(M*) Error of log (M*) (error_logMstar)
68- 73 F6.3 [Msun/yr] log(SFR) Hα star formation rate (logSFR)
75- 79 F5.3 [Msun/yr] e_log(SFR) Error of log (SFR) (error_logSFR)
81- 86 F6.3 kpc lcorr ? Median 50th percentile of the posterior
PDF correlation length (lcorr_50)
88- 93 F6.3 kpc b_lcorr ? 16th percentile of the posterior PDF
correlation length (lcorr_16)
95-100 F6.3 kpc B_lcorr 84th percentile of the posterior PDF
correlation length (lcorr_84)
102-104 I3 pc winj ? Median 50th percentile of the posterior
PDF injection width (w_inj50)
106-108 I3 pc b_winj ? 16th percentile of the posterior PDF
injection width (w_inj16)
110-113 I4 pc B_winj 84th percentile of the posterior PDF
injection width (w_inj84)
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History:
From electronic version of the journal
(End) Luc Trabelsi [CDS] 01-Dec-2025