Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

TL;DR

This paper uses a flexible one-zone chemical evolution model to explore how inflow, outflow, and stellar population mixing influence galaxy chemical signatures, revealing the importance of parameter trade-offs and model variations.

Contribution

It introduces a comprehensive analysis of parameter effects in chemical evolution models and demonstrates how mixing scenarios better reproduce observed stellar abundance bimodality.

Findings

One-zone models follow narrow abundance tracks unlike observed bimodality.

Mixing models with inflow and outflow variations better reproduce observed sequences.

Principal component analysis reveals dominant abundance correlations.

Abstract

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the Type Ia supernova delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]-[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]-[Fe/H] unlike the observed bimodality (separate high-alpha and low-alpha sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]-[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis (PCAA) to the simulations and existing data to reveal the main correlations amongst abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of alpha-elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.