Scalability of Hydrodynamic Simulations

TL;DR

This paper investigates the scalability of hydrodynamic simulations, identifying physical constraints that limit scalability, and demonstrates how scaling can efficiently explore parameter spaces using supernova remnants as examples.

Contribution

It introduces a scaling scheme for hydrodynamic simulations that enables efficient exploration of parameter spaces with minimal simulations, specifically applied to supernova remnants.

Findings

Scalability is limited by physical processes and initial conditions.

A new scaling scheme allows adaptive generation of supernova remnants.

The method reduces computational effort in simulating supernova-dominated media.

Abstract

Many hydrodynamic processes can be studied in a way that is scalable over a vastly relevant physical parameter space. We systematically examine this scalability, which has so far only briefly discussed in astrophysical literature. We show how the scalability is limited by various constraints imposed by physical processes and initial conditions. Using supernova remnants in different environments and evolutionary phases as application examples, we demonstrate the use of the scaling as a powerful tool to explore the interdependence among relevant parameters, based on a minimum set of simulations. In particular, we devise a scaling scheme that can be used to adaptively generate numerous seed remnants and plant them into 3D hydrodynamic simulations of the supernova-dominated interstellar medium.