2017
DOI: 10.3847/1538-3881/153/2/85
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Chemical Evolution Library for Galaxy Formation Simulation

Abstract: We have developed a software library for chemical evolution simulations of galaxy formation under the simple stellar population (SSP) approximation. In this library, all of the necessary components concerning chemical evolution, such as initial mass functions, stellar lifetimes, yields from type II and Ia supernovae, asymptotic giant branch stars, and neutron star mergers, are compiled from the literature. Various models are pre-implemented in this library so that users can choose their favorite combination of… Show more

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Cited by 57 publications
(36 citation statements)
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References 194 publications
(380 reference statements)
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“…For these inputs the required galactic yield of h = 0.0025 is larger than the the IMF-weighted stellar magnesium yield of ∼0.001 (Saitoh 2017). Although numerical simulations do require that a significant fraction of the stellar yield is returned to the halo (Peeples et al 2014), it is still the case that a  M 10 8 stellar population produces too little MgIIto fill a halo to 90 kpc with observable MgII, by a factor of a few.…”
Section: Can Low-mass Galaxies Yield Enough Magnesium To Enrichmentioning
confidence: 95%
“…For these inputs the required galactic yield of h = 0.0025 is larger than the the IMF-weighted stellar magnesium yield of ∼0.001 (Saitoh 2017). Although numerical simulations do require that a significant fraction of the stellar yield is returned to the halo (Peeples et al 2014), it is still the case that a  M 10 8 stellar population produces too little MgIIto fill a halo to 90 kpc with observable MgII, by a factor of a few.…”
Section: Can Low-mass Galaxies Yield Enough Magnesium To Enrichmentioning
confidence: 95%
“…We adopt the initial mass function of Chabrier (2003) from 0.1 to 100 M ⊙ . Thermal and chemical feedback from SSP particles is computed using Chemical Evolution Library (celib, Saitoh 2016Saitoh , 2017. We adopt the reference feedback models in celib.…”
Section: Introductionmentioning
confidence: 99%
“…For metal diffusion, we have implemented turbulent metal mixing model in DISPH (Saitoh 2017) based on Smagorinsky (1963) and Shen et al (2010). The ith metal, Z i , diffuses to surrounding gas particles with the following equation,…”
Section: Introductionmentioning
confidence: 99%
“…The simulations start at an age of 2 Gyr; therefore, the SSP contributes metals only via AGB winds and SNIa's ejecta. The weakly time‐dependent metal input from AGB winds was calculated with “CELib,” an open‐source software library for chemical evolution (Saitoh ). The abundance of the SSP is Z ⋆ = 1.5Z ⊙ (where Z ⊙ = 0.0134, Asplund et al ), as appropriate for a massive elliptical such as the one modeled (Thomas et al ).…”
Section: Modeling the Ism Evolutionmentioning
confidence: 99%