Massively parallel simulations of binary black holes with Dendro-GR

TL;DR

This paper introduces Dendro-GR, a new code for simulating binary black hole mergers using adaptive multi-resolution techniques, demonstrating good scalability, convergence, and validation against existing methods.

Contribution

The paper presents Dendro-GR, a novel simulation code employing wavelet-based adaptive grids for efficient and accurate binary black hole merger modeling.

Findings

Successfully simulated mergers with mass ratios up to 16

Demonstrated good scalability and convergence

Validated results against LazEv code

Abstract

We present results from the new Dendro-GR code. These include simulations of binary black hole mergers for mass ratios up to q=16. Dendro-GR uses Wavelet Adaptive Multi-Resolution (WAMR) to generate an unstructured grid adapted to the spacetime geometry together with an octree based data structure. We demonstrate good scaling, improved convergence properties and efficient use of computational resources. We validate the code with comparisons to LazEv.