The Impact of Modeling Assumptions in Galactic Chemical Evolution Models

Abstract

We use the OMEGA galactic chemical evolution code to investigate how the assumptions used for the treatment of galactic inflows and outflows impact numerical predictions. The goal is to determine how our capacity to reproduce the chemical evolution trends of a galaxy is affected by the choice of implementation used to include those physical processes. In pursuit of this goal, we experiment with three different prescriptions for galactic inflows and outflows and use OMEGA within a Markov Chain Monte Carlo code to recover the set of input parameters that best reproduces the chemical evolution of nine elements in the dwarf spheroidal galaxy Sculptor. This provides a consistent framework for comparing the best-fit solutions generated by our different models. Despite their different degrees of intended physical realism, we found that all three prescriptions can reproduce in an almost identical way the stellar abundance trends observed in Sculptor. This result supports the similar conclusions originally claimed by Romano & Starkenburg (2013) for Sculptor. While the three models have the same capacity to fit the data, the best values recovered for the parameters controlling the number of Type Ia supernovae and the strength of galactic outflows, are substantially different and in fact mutually exclusive from one model to another. For the purpose of understanding how a galaxy evolves, we conclude that only reproducing the evolution of a limited number of elements is insufficient and can lead to misleading conclusions. More elements or additional constraints such as the galaxy's star formation efficiency and the gas fraction are needed in order to break the degeneracy between the different modeling assumptions. Our results show that the successes and failures of chemical evolution models are predominantly driven by the input stellar yields, rather than by the complexity of the galaxy model itself. Simple models such as OMEGA are therefore sufficient to test and validate stellar yields. OMEGA is part of the NuGrid chemical evolution package and is publicly available online at http://nugrid.github.io/NuPyCEE.

Mass and metallicity requirement in stellar models for galactic chemical evolution applications

“…We use OMEGA, our One-zone Model for the Evolution of GAlaxies code (Côté et al 2016b), to follow the chemical evolution of the Milky Way. The input parameters of the closed-box version and the treatment of SSPs using SYGMA, which stands for Stellar Yields for Galactic Modeling Applications (C. Ritter et al, in prep.…”

“…To calculate the time evolution of η, the mass-loading factor, we use the MA prescription described in Côté et al (2016b),…”

JINA-NuGrid Galactic Chemical Evolution Pipeline

“…OMEGA [3] (One-zone Model for the Evolution of GAlaxies) is a classical one-zone GCE code that includes several prescriptions for galactic inflows and outflows. Using an input star formation history, it follows the contribution of several stellar populations, all created by SYGMA.…”

“…Using an input star formation history, it follows the contribution of several stellar populations, all created by SYGMA. While OMEGA is not explicitly designed to provide direct insight into galaxy evolution, it is ideal to test modeling assumptions and uncertainties in stellar models [3]. As an example, panels a and b of Figure 2 show the impact of using different approaches for calculating the explosive yields of massive stars.…”

Chemical Evolution Library for Galaxy Formation Simulation

“…Thus, when parameters change, e.g., the functional form and the mass range of IMF, the reconstruction of the yields table is necessary. The NuGrid collaboration 5 has developed a Python code, SYGMA, which can deal with the yields of the NuGrid project and can be used in chemical evolution of galaxies (Côté et al 2016). Since this is implemented as an iPython notebook, users need to pre-generate yields in order to use the outcomes from SYGMA.…”