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: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table1.dat 113 219 *Global properties of AMUSING++ nearby galaxy sample -------------------------------------------------------------------------------- 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). -------------------------------------------------------------------------------- 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 -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 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) -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Luc Trabelsi [CDS] 01-Dec-2025
The document above follows the rules of the Standard Description for Astronomical Catalogues; from this documentation it is possible to generate f77 program to load files into arrays or line by line