In:
Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP), Vol. 492, No. 1 ( 2020-02-11), p. 96-139
Abstract:
We present an analysis of star formation and quenching in the SDSS-IV MaNGA-DR15, utilizing over 5 million spaxels from ∼3500 local galaxies. We estimate star formation rate surface densities (ΣSFR) via dust corrected H α flux where possible, and via an empirical relationship between specific star formation rate (sSFR) and the strength of the 4000 Å break (D4000) in all other cases. We train a multilayered artificial neural network (ANN) and a random forest (RF) to classify spaxels into ‘star-forming’ and ‘quenched’ categories given various individual (and groups of) parameters. We find that global parameters (pertaining to the galaxy as a whole) perform collectively the best at predicting when spaxels will be quenched, and are substantially superior to local/spatially resolved and environmental parameters. Central velocity dispersion is the best single parameter for predicting quenching in central galaxies. We interpret this observational fact as a probable consequence of the total integrated energy from active galactic neucleus (AGN) feedback being traced by the mass of the black hole, which is well known to correlate strongly with central velocity dispersion. Additionally, we train both an ANN and RF to estimate ΣSFR values directly via regression in star-forming regions. Local/spatially resolved parameters are collectively the most predictive at estimating ΣSFR in these analyses, with stellar mass surface density at the spaxel location (Σ*) being by far the best single parameter. Thus, quenching is fundamentally a global process but star formation is governed locally by processes within each spaxel.
Type of Medium:
Online Resource
ISSN:
0035-8711
,
1365-2966
DOI:
10.1093/mnras/stz3264
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2020
detail.hit.zdb_id:
2016084-7
SSG:
16,12
