Are galactic star formation and quenching governed by local, global, or environmental phenomena?

Abstract

We present an analysis of star formation and quenching in the SDSS-IV MaNGA-DR15, utilising over 5 million spaxels from ∼3500 local galaxies. We estimate star formation rate surface densities (Σ SFR ) via dust corrected Hα flux where possible, and via an empirical relationship between specific star formation rate (sSFR) and the strength of the 4000Å break (D4000) in all other cases. We train a multi-layered 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 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 Σ SFR values directly via regression in star forming regions. Local/ spatially resolved parameters are collectively the most predictive at estimating Σ SFR 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.

The ALMaQUEST survey – III. Scatter in the resolved star-forming main sequence is primarily due to variations in star formation efficiency

“…Two other works have also recently used complementary machine learning methods to quantify the primary driver of SFR . First, Bluck et al (2019b) have applied the same ANN approach used herein to MaNGA data and find several conclusions in common with us: that is the most important parameter in determining SFR , and that R and O/H play a negligible role. However, Bluck et al (2019b) do not have direct measurements of gas surface densities amongst their available parameters.…”

“…To complement the correlation analysis, we also apply a machine learning approach, which has the benefit of being able to recognize more complex patterns in the data than can be captured by ρ. Specifically, we perform a non-linear regression with an artificial neural network (ANN), utilizing MLPregresser from the scikit-learn package (Pedregosa et al 2011), adopting an identical architecture as in Bluck et al (2019b). To test the stability of the network, we train on five randomly selected input samples (containing 50 per cent of the data) and validate on the remainder of the sample in each case.…”

“…There is clear evidence that there can be significant internal variations in SFE within a given galaxy (e.g. Leroy et al 2013;Utomo et al 2017;Tomicic et al 2019), and that the regulation of star formation happens on local, not global scales (Bluck et al 2019b;Dey et al 2019). Studies that investigate correlations in global data will average over these internal differences, blurring the underlying physical relationships.…”

A panchromatic spatially resolved analysis of nearby galaxies – I. Sub-kpc-scale main sequence in grand-design spirals

“…Rodighiero et al 2014). In this Section, we thus compare our panchromatic results with the spatially resolved MS relations obtained with data from CALIFA (Cano-Díaz et al 2016), MaNGA (Hsieh et al 2017;Cano-Díaz et al 2019;Bluck et al 2019), and SAMI (Medling et al 2018). For completeness, we also compare our results with the MS relations of Abdurro'uf & Akiyama (2017), that perform pixel-bypixel SED fitting to GALEX and SDSS photometry of local (0.01 < z < 0.02) massive spiral galaxies selected in the MPI-JHU (Max Planck Institute for Astrophysics-Johns Hopkins University), and of Hall et al (2018), obtained for a sample of 355 nearby galaxies, with spatially resolved observations of Hα and mid-IR emission.…”

The impact of disturbed galaxy clusters on the kinematics of active galactic nuclei

“…Despite these determined relationships between galactic properties and density they are not the dominant cause for the observed galaxy evolution since field populations are generally mixed, indicative of natural galactic evolution (e.g. see Kauffmann et al 2004;Blanton et al 2005;Lemaux et al 2019;Bluck et al 2020).…”