QScatter: Numerical Framework for Fast Prediction of Particle Distributions in Electron-Laser Scattering

Introduction

The new generation of multi-PetaWatt laser facilities will allow tests of Strong Field QED, as well as provide an opportunity for novel photon and lepton sources. The first experiments are planned to study the (nearly) head-on scattering of intense, focused laser pulses with either relativistic electron beams or high-energy photon sources. In this work, we present a numerical framework that can provide fast predictions of the asymptotic particle and photon distributions after the scattering. The works presented in this manuscript includes multiple features such as spatial and temporal misalignment between the laser and the scattering beam, broadband electron beams, and beam divergence. The expected mean energy, energy spread, divergence or other observables are calculated by combining an analytical description and numerical integration. This method can provide results within minutes on a personal computer, which would otherwise require full-scale 3D QED-PIC simulations using thousands of cores. The model, which has been compiled into an open-source code QScatter, may be used to support the analysis of large-size data sets from high-repetition rate experiments, leveraging its speed for optimization or reconstruction of experimental parameters.

Journal paper: https://iopscience.iop.org/article/10.1088/1361-6587/ad2975

Pre-print: https://arxiv.org/abs/2308.09348

Attribution

QScatter (quick-scattering-toolkit) is a scientific project. If you present and/or publish scientific results that used QScatter, we ask you to set a reference to show your support. At present, the BibTeX formatted citation is

@misc{amaro2023qscatter,
      title={QScatter: Numerical Framework for Fast Prediction of Particle Distributions in Electron-Laser Scattering}, 
      author={Óscar Amaro and Marija Vranic},
      year={2023},
      eprint={2308.09348},
      archivePrefix={arXiv},
      primaryClass={physics.plasm-ph}
}

In alternative, add "Ó. Amaro, M. Vranic, arXiv:2308.09348, 2023" to the references' list of your work. Thank you for your understanding and support!

Related repositories

• Vranic et al 2014 PRL https://github.com/RePlasma/PhysRevLett.113.134801
• Vranic et al 2016 NJP https://github.com/RePlasma/Vranic_2016_New_J._Phys._18_073035
• Amaro et al 2021 NJP https://github.com/OsAmaro/distscalarfield

Active Developing Team

Maintainer and core developer

• Óscar Amaro

Supervision

• Prof. Marija Vranic

---