3D Synthetic Convective Velocity Fields to Initialise Core-Collapse Supernova Simulations from 1D Progenitors
Vishnu Varma, Bernhard Mueller, Raphael Hirschi

TL;DR
This paper introduces a method to generate synthetic 3D convective velocity fields from 1D stellar models, enabling more accessible initial conditions for core-collapse supernova simulations without costly hydrodynamic progenitor modeling.
Contribution
The authors develop a novel vector spherical harmonics-based approach to create physically consistent 3D velocity fields from 1D data, facilitating widespread use in supernova research.
Findings
Method accurately reproduces typical convective scales and velocities.
Respects physical constraints like near-anelasticity and zero net angular momentum.
Provides a publicly available Python tool for the community.
Abstract
Core-collapse supernovae (CCSNe) are among the most energetic and complex astrophysical phenomena, requiring threedimensional (3D) simulations to capture their intricate explosion mechanisms. One of the key ingredients for such simulations is the 3D pre-collapse structure, which can impact the development and geometry of the subsequent explosion. While stellar convection simulations can provide such 3D initial conditions, these remain too expensive and demanding for widespread use. In this work, we present a method to generate synthetic 3D velocity fields for convective zones from 1D initial conditions, creating initial conditions for CCSN simulations using a vector spherical harmonics expansion without the need for expensive hydrodynamic progenitor simulations. The synthetic velocity field is designed to capture the typical scales and velocities of the convective flow as the most…
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