mardom/sledgehamr

Sledgehamr is an AMReX-based code package to simulate the dynamics of coupled scalar fields on a 3-dimensional adaptive mesh.

Sledgehamr: Simulating scalar fields with adaptive mesh refinement

Sledgehamr (ScaLar fiEld Dynamics Getting solvEd witH Adaptive Mesh Refinement) is an AMReX-based code to simulate the dynamics of coupled scalar fields on a 3-dimensional mesh. Adaptive mesh refinement (AMR) can boost performance if spatially localized regions of the scalar field require high resolution. Compatible with both GPU and CPU clusters, sledgehamr offers a flexible and customizable framework. This framework enables various applications, such as the generation of gravitational wave spectra.

For a detailed description of the code please consult the accompanying paper: https://arxiv.org/abs/arXiv:2404.02950

For questions, comments, or bug reports please use the GitHub issues feature, or contact me via email: [email protected]

Installation

Prerequisites

• AMReX (git clone https://github.com/AMReX-Codes/amrex)
• FFTW3
• Boost

Running the minimal examples

The minimal examples can be run by following the instructions in the Jupyter notebooks notebooks/MinimalExample.ipynb and notebooks/NextToMinimalExample.ipynb.

Create a project

Sledgehamr comes with a few different physics scenarios already implemented such as axion strings and a first-order phase transition of a single scalar field + gravitational waves, as well as two example projects MinimalExample and NextToMinimalExample. The accompanying paper describes in detail how other scenarios can be implemented.

Code documentation

• https://msabuschmann.github.io/sledgehamr/
• https://arxiv.org/abs/2404.02950

How to cite

If you use sledgehamr, please cite its accompanying paper:

• Malte Buschmann, "Sledgehamr: Simulation Scalar Fields with Adaptive Mesh Refinement", arXiv:2404.02950

BibTex:

@misc{buschmann2024sledgehamr,
      title={Sledgehamr: Simulating Scalar Fields with Adaptive Mesh Refinement}, 
      author={Malte Buschmann},
      year={2024},
      eprint={2404.02950},
      archivePrefix={arXiv},
      primaryClass={hep-ph}
}

Publications using this code

2022

• "Dark matter from axion strings with adaptive mesh refinement", M. Buschmann et al., Nature Commun. 13 (2022) 1, 1049, https://arxiv.org/abs/2108.05368

2024

• "Signatures of primordial energy injection from axion strings", J. Benabou et al., Phys.Rev.D 109 (2024) 5, 055005, https://arxiv.org/abs/2308.01334
• "Thick and Thin Wall Collisions with Adaptive Mesh Refinement", M. Buschmann et al., to appear
• "Axion Mass Prediction from adaptive mesh refinement cosmological lattice simulations", J. Benabou et al., to appear