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Context.Stars with initial mass above roughly 8M⊙will evolve to form a core made of iron group elements, at which point no further exothermic nuclear reactions between charged nuclei may prevent the core collapse. Electron capture, neutrino losses, and the photo-disintegration of heavy nuclei trigger the collapse of these stars. Models at the brink of core collapse are produced using stellar evolution codes, and these pre-collapse models may be used in the study of the subsequent dynamical evolution (including their explosion as supernovae and the formation of compact remnants such as neutron stars or black holes). Aims.We upgraded the physical ingredients employed by the GENeva stellar Evolution Code, GENEC, so that it covers the regime of high-temperatures and high-densities required to produce the progenitors of core-collapse. Our ultimate goal is producing pre-supernova models with GENEC, not only right before collapse, but also during the late phases (silicon and oxygen burning). Methods.We have improved GENEC in three directions: equation of state, the nuclear reaction network, and the radiative and conductive opacities adapted for the computation of the advanced phases of evolution. We produce a small grid of pre-supernova models of stars with zero age main sequence masses of 15 M⊙, 20 M⊙, and 25 M⊙at solar and less than half solar metallicities. The results are compared with analogous models produced with the MESA code. Results.The global properties of our new models, particularly of their inner cores, are comparable to models computed with MESA and pre-existing progenitors in the literature. Between codes the exact shell structure varies, and impacts explosion predictions. Conclusions.Using GENEC with state-of-the-art physics, we have produced massive stellar progenitors prior to collapse. These progenitors are suitable for follow-up studies, including the dynamical collapse and supernova phases. Larger grids of supernova progenitors are now feasible, with the potential for further dynamical evolution.
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Modules for Experiments in Stellar Astrophysics (MESA): Time-dependent Convection, Energy Conservation, Automatic Differentiation, and Infrastructure
Abstract We update the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics ( MESA ). The new auto _ diff module implements automatic differentiation in MESA , an enabling capability that alleviates the need for hard-coded analytic expressions or finite-difference approximations. We significantly enhance the treatment of the growth and decay of convection in MESA with a new model for time-dependent convection, which is particularly important during late-stage nuclear burning in massive stars and electron-degenerate ignition events. We strengthen MESA ’s implementation of the equation of state, and we quantify continued improvements to energy accounting and solver accuracy through a discussion of different energy equation features and enhancements. To improve the modeling of stars in MESA , we describe key updates to the treatment of stellar atmospheres, molecular opacities, Compton opacities, conductive opacities, element diffusion coefficients, and nuclear reaction rates. We introduce treatments of starspots, an important consideration for low-mass stars, and modifications for superadiabatic convection in radiation-dominated regions. We describe new approaches for increasing the efficiency of calculating monochromatic opacities and radiative levitation, and for increasing the efficiency of evolving the late stages of massive stars with a new operator-split nuclear burning mode. We close by discussing major updates to MESA ’s software infrastructure that enhance source code development and community engagement.
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- PAR ID:
- 10413164
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Date Published:
- Journal Name:
- The Astrophysical Journal Supplement Series
- Volume:
- 265
- Issue:
- 1
- ISSN:
- 0067-0049
- Page Range / eLocation ID:
- 15
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.3847/1538-4365/acae8d
