Rapid early gas accretion for the inner Galactic disc

Owain Snaith,Paola Di Matteo,Misha Haywood,Sergey Khoperskov,David Katz,Matthew Lehnert

doi:10.1051/0004-6361/202039526

Abstract

Context. Recent observations of the Milky Way and galaxies at high redshifts suggest that galaxy discs were already in place soon after the Big Bang. While the gas infall history of the Milky Way in the inner disc has long been assumed to be characterised by a short accretion timescale, this has not been directly constrained using observations. Aims. Using data for the inner regions of the Milky Way recently produced by APOGEE and Gaia and of unprecedented quantity and quality, we aim to derive strong constraints on the infall history of the inner (< 6 kpc) Galaxy (with a focus on stars between 4 and 6 kpc, which we show is an appropriate proxy for the entire inner disc). Methods. We implemented gas infall into a chemical evolution model of the Galaxy disc, and used a Schmidt–Kennicutt law to connect the infall to the star formation. We explore a number of models, and two different formulations of the infall law. In one formulation, the infall is non-parametric, and in the other the infall has an explicitly exponential form. We fit the model parameters to the time–[Si/Fe] distribution of solar vicinity stars, and the metallicity and [Si/Fe] distribution function of stars with a galactocentric radius of between 4 and 6 kpc from APOGEE. Results. Our results point to a fast, early gas accretion, and an upper limit on the accretion timescale of around 2 Gyr in the inner disc of the Milky Way. This suggests that at least half the baryons were in place within 2−3 Gyr of the Big Bang, and that half the stars of the inner disc formed within the first 5 Gyr, during the thick disc formation phase. This implies that the stellar mass of the inner disc is dominated by the thick disc, supporting our previous work, and that the gas accretion onto the inner disc was rapid and early.

Highlights

Understanding the history of the Milky Way requires a combination of observations (e.g. Ahumada et al 2020; Hayden et al 2015; Adibekyan et al 2012; Queiroz et al 2020), simulations (e.g. Guedes et al 2011; Brook et al 2012, 2020; Roškar et al 2013; Buck 2020), models (e.g. Chiappini et al 1997; Côté et al 2017; Spitoni et al 2019), and statistical analysis (Ness et al 2019; Ciucaet al. 2021), because each approach offers different insights into its formation
Since we presented our model of the star formation history (SFH) of the Milky Way in Snaith et al (2014, 2015), new observations from APOGEE (Nidever et al 2014; Ahumada et al 2020; Hayden et al 2015) have been released, and have been studied in detail
A detailed calculation of the distribution functions is beyond the scope of this paper, but it must be noted that the results presented here, and the effects of the selection function, may not have been fully disentangled

Summary

Introduction

Understanding the history of the Milky Way requires a combination of observations (e.g. Ahumada et al 2020; Hayden et al 2015; Adibekyan et al 2012; Queiroz et al 2020), simulations (e.g. Guedes et al 2011; Brook et al 2012, 2020; Roškar et al 2013; Buck 2020), models (e.g. Chiappini et al 1997; Côté et al 2017; Spitoni et al 2019), and statistical analysis (Ness et al 2019; Ciucaet al. 2021), because each approach offers different insights into its formation. The long timescale for many astrophysical processes means that we usually cannot see them taking place directly, and so must rely on models and simulations, which can be compared to observations Recent surveys, such as Gaia (Gaia Collaboration 2016, 2018), APOGEE (Nidever et al 2014; Majewski et al 2017), GALAH (Buder et al 2018), LAMOST (Cui et al 2012), and local spectroscopic surveys such as the one carried out by Adibekyan et al (2012), have provided detailed information about the properties of stars. Since we presented our model of the SFH of the Milky Way in Snaith et al (2014, 2015), new observations from APOGEE (Nidever et al 2014; Ahumada et al 2020; Hayden et al 2015) have been released, and have been studied in detail These developments mean that our chemical evolution model must be compared to these newer data sets. Since its first publication, our ‘closed-box’ model has remained highly robust to comparisons with data (e.g. Haywood et al 2015, 2016a,b, 2018, 2019)

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Discussion

Conclusion