Published December 6, 2024 | Version v1

MESA files for: "A grid of fast-rotating, chemically-homogeneous, supernova and/or long-GRB progenitors"

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Description

Single-star  rotationally-induced chemically-homogeneous low-metallicity models at the onset of core-collapse (v_infall<300km/s) with 128-isotope network from Renzo et al. 2026.

The tarball `grid.tar` contains the grid of MESA models computed with MESA r24.03.1, MESA SDK x86_64-linux-23.7.3, on a Rocky OS 8.

`template.tar.xz` contains a template setup: to run more models, you need to change the initial mass and initial `omega/omega_crit` (and you may want to edit the `./rn` script to avoid sending me emails when the run is done. (Use `tar tvf grid.tar` to list its content, `tar xvf grid.tar` to unpack it)

Inside `grid.tar.xz` each tarball containstarballs contain a successful model labeled by its initial mass and initial rotation. We consider a model successful if it reaches the onset of core collapse defined as infall velocity of >300km/s and does not exhibit spurious spikes in the HR diagram (this last condition is vetted by eye). The resolution tests are presented in the appendix of Gottlieb, Renzo et al. 2024. Only masses and rotation rates are varied here.

For each model, inside the folder `LOGS` there are several profiles when first `log_center_T>=8.95`, oxygen depletion, silicon depletion, and onset of core collapse, plus the `history.data` file for the run. Corresponding `*.mod` files are also provided to restart the runs from these evolutionary points. `output.txt` contains the terminal output for these runs.

`scripts.tar.xz` contains python scripts to reproduce the figures in the paper, see also https://github.com/mathren/CHE_lGRB_progenitors.

`build.sh` allows to build the manuscript, see also README at https://github.com/mathren/CHE_lGRB_progenitors.

Files

Files (8.0 GB)

Name Size
md5:70abd3471002d5d9ca1eb976a8178641
4.3 kB Download
md5:3c49b0daae0b2c40a4baba98317f95dc
8.0 GB Download
md5:e37e5d359a2ee6d90d9a2b9e3e21af5b
7.6 MB Download
md5:6e85fa4761ccfa80a0840cac436d9067
26.8 kB Download

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