Comparing Compact Object Distributions from Mass- and Presupernova Core Structure-based Prescriptions
Rachel A. Patton, Tuguldur Sukhbold, and J.J. Eldridge

TL;DR
This study compares different methods for predicting compact object remnants in binary star populations, highlighting how core structure-based prescriptions differ from traditional mass-based methods in remnant mass predictions.
Contribution
It introduces and compares three methods for predicting remnant masses, emphasizing the importance of presupernova core structure over simple mass-based prescriptions.
Findings
Mass-based prescriptions predict more low-mass remnants and a wider neutron star mass range.
Core structure-based methods favor higher mass remnants and produce a narrower neutron star mass distribution.
Mass gap black holes are predicted only above 3.5 solar masses in structure-based models.
Abstract
Binary population synthesis (BPS) employs prescriptions to predict final fates, explosion or implosion, and remnant masses based on one or two stellar parameters at the evolutionary cutoff imposed by the code, usually at or near central carbon ignition. In doing this, BPS disregards the integral role late-stage evolution plays in determining the final fate, remnant type, and remnant mass within the neutrino-driven explosion paradigm. To highlight differences between a popular prescription which relies only on the core and final stellar mass and emerging methods which rely on a star's presupernova core structure, we generate a series of compact object distributions using three different methods for a sample population of single and binary stars computed in BPASS. The first method estimates remnant mass based on a star's carbon-oxygen (CO) core mass and final total mass. The second method…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
