New Analytic Solutions for Galaxy Evolution II: Wind Recycling, Galactic Fountains and Late-Type Galaxies

TL;DR

This paper develops generalized analytic models incorporating wind recycling and galactic fountains to study the evolution of gas, stars, metals, and dust in late-type galaxies, providing a fast tool for interpretation and modeling.

Contribution

It introduces a self-consistent analytic framework that includes wind recycling and galactic fountains, enhancing understanding of galaxy evolution processes.

Findings

Wind recycling and galactic fountains significantly extend star formation timescales.

Analytic solutions reproduce key statistical relationships of local late-type galaxies.

The models serve as benchmarks for more complex simulations and observations.

Abstract

We generalize the analytic solutions presented in Pantoni et al. (2019) by including a simple yet effective description of wind recycling and galactic fountains, with the aim of self-consistently investigating the spatially-averaged time evolution of the gas, stellar, metal, and dust content in disc-dominated late-type galaxies (LTGs). Our analytic solutions, when supplemented with specific prescriptions for parameter setting and with halo accretion rates from $N-$body simulations, can be exploited to reproduce the main statistical relationships followed by local LTGs; these involve, as a function of the stellar mass, the star formation efficiency, the gas mass fraction, the gas/stellar metallicity, the dust mass, the star formation rate, the specific angular momentum, and the overall mass/metal budget. Our analytic solutions allow to easily disentangle the diverse role of the main physical processes ruling galaxy formation in LTGs; in particular, we highlight the crucial relevance of wind recycling and galactic fountains in efficiently refurnishing the gas mass, extending the star-formation timescale, and boosting the metal enrichment in gas and stars. All in all, our analytic solutions constitute a transparent, handy, and fast tool that can provide a basis for improving the (subgrid) physical recipes presently implemented in more sophisticated semi-analytic models and numerical simulations, and can offer a benchmark for interpreting and forecasting current and future spatially-averaged observations of local and higher redshift LTGs.