The cosmic carbon footprint of massive stars stripped in binary systems

# Structure ## Overview The folder data/ contains the inlists and mod files used in this work. Intermediate data (like history or profile) files must be regenerated from the provided files. The folder plots/ contains a jupyter notebook set-up to remake all plots (assuming the data is saved in the data/ folder). There are also additional scripts and files needed to reproduce this work. The griffith.txt file is the data from https://ui.adsabs.harvard.edu/abs/2021arXiv210309837G/abstract and was accessed from https://github.com/giganano/VICE/blob/master/vice/yields/ccsne/S16/W18F/FeH0/v0/explosive/c.dat ## Data folders corehedep - Evolution from ZAMS to end of core helium burning coreodep - Evolution from end of core helium burning to end of core oxygen burning cc - Evolution from end of core oxygen burning up to core collapse ccsn - Evolution from core collapse to shock breakout engmc - Tests variations in the injection energy and mass cut of ccsn explosions spacetime - Test variations in space/time resolution of ccsn explosions ccsn_t_m - Test variations in injection time and injection mass of ccsn explosions ## Sub-folders corehedep/base - Base folder with inlists for this set of models corehedep/binary - Contains a folder for each mass for the binary-stripped stars (11-45) corehedep/single - Contains a folder for each mass for the single stars (11-45) corehedep/net/23 - A single star 23msun model ran with a larger nuclear network coreodep/base - Base folder with inlists for this set of models coreodep/binary - Contains a folder for each mass for the binary-stripped stars (11-45) coreodep/single - Contains a folder for each mass for the single stars (11-45) coreodep/mesh - Test variations with respect to space and time during carbon burning coreodep/overshoot - Test variations with respect to overshoot during carbon burning coreodep/net - A single star 23msun model ran with a larger nuclear network cc/base - Base folder with inlists for this set of models cc/binary - Contains a folder for each mass for the binary-stripped stars (11-45) cc/single - Contains a folder for each mass for the single stars (11-45) ccsn/base - Base folder with inlists for this set of models ccsn/binary - Contains a folder for each mass for the binary-stripped stars (11-45) ccsn/single - Contains a folder for each mass for the single stars (11-45) ccsn/laplace_binary - Contains core collapse explosions of the binary-stripped models from Laplace et al 2021 ccsn/laplace_single - Contains core collapse explosions of the single star models from Laplace et al 2021 spacetime/base - Base folder with inlists for this set of models spacetime/binary - Test variations in space/time resolution of ccsn explosions ccsn_t_m/base - Base folder with inlists for this set of models ccsn_t_m/binary - Test variations in injection time and injection mass of ccsn explosions engmc/base - Base folder with inlists for this set of models engmc/binary - Tests variations in the injection energy and mass cut of ccsn explosions ## Notes Folders with the name '_k' have enhanced profile output for use in Kippenhan plots. Folders with the name '_v' have enhanced profile output for use in the video of the shock explosion. Each numbered folder contains a set of inlists used (which usually only vary one or two parameters), the rest of the inlists are stored in the base/ folders (See the submit.sh files for how to get MESA to read these files). They also contain a initial.mod file (which is the starting point for this phase of evolution), this is a softlink to the final.mod file from the previous phase (thus coreodep soft links to files in corehedep, corehdep uses MESA's built in ZAMS models to start). The folders that handle the core collapse explosions have additional .mod files that handle each phase of the explosion. See the base/ folders for details on the order. ## Files cacheHist.py - Runs mesaplot code to turn history files into a python binary file for faster reading. plotKip.py - Does a quick kippenhan plot for diagnostics