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SYGMA: Stellar Yields for Galactic Modeling Applications

Ritter, Christian and Coté, Benoit and Herwig, Falk and Navarro, Julio F and Fryer, Chris L (2018) SYGMA: Stellar Yields for Galactic Modeling Applications. ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES, 237 (2). ISSN 0067-0049

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Abstract

The Stellar Yields for Galactic Modeling Applications (SYGMA) code is an open-source module that models the chemical ejecta and feedback of simple stellar populations (SSPs). It is intended for use in hydrodynamical simulations and semi-analytic models of galactic chemical evolution. The module includes the enrichment from asymptotic giant branch (AGB) stars, massive stars, Type Ia supernovae (SNe Ia), and compact binary mergers. An extensive and extendable stellar yields library includes the NuGrid yields with all elements and many isotopes up to Bi. Stellar feedback from mechanic and frequency-dependent radiative luminosities are computed based on NuGrid stellar models and their synthetic spectra. The module further allows for customizable initial mass functions and SN Ia delay-time distributions to calculate time-dependent ejecta based on stellar yield input. A variety of r-process sites can be included. A comparison of SSP ejecta based on NuGrid yields with those from Portinari et al. and Marigo reveals up to factors of 3.5 and 4.8 less C and N enrichment from AGB stars at low metallicity, a result we attribute to NuGrid’s modeling of hot-bottom burning. Different core-collapse supernova explosions and fallback prescriptions may lead to substantial variations for the accumulated ejecta of C, O and Si in the first 10<SUP>7</SUP> years at Z = 0.001. An online interface of the open-source SYGMA module enables interactive simulations, analysis, and data extraction of the evolution of all species formed by the evolution of simple stellar populations.

Item Type: Article
Subjects: Q Science / természettudomány > Q1 Science (General) / természettudomány általában
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 24 Mar 2023 09:59
Last Modified: 24 Mar 2023 09:59
URI: http://real.mtak.hu/id/eprint/162755

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