SFQEDtoolkit: a high-performance library for the accurate modeling of strong-field QED processes in PIC and Monte Carlo codes

TL;DR

SFQEDtoolkit is an open-source, high-performance library that enables accurate and efficient modeling of strong-field QED processes in particle-in-cell and Monte Carlo simulations, advancing research in extreme electromagnetic environments.

Contribution

It introduces a flexible function approximation approach for modeling SFQED processes, including photon emission and pair creation, with plans to extend capabilities beyond current models.

Findings

Provides high-accuracy probability rates and energy distributions for SFQED processes.

Enables straightforward integration into existing PIC and Monte Carlo codes.

Designed for future expansion to include angular, spin, and polarization effects.

Abstract

Strong-field quantum electrodynamics (SFQED) processes are central in determining the dynamics of particles and plasmas in extreme electromagnetic fields such as those present in the vicinity of compact astrophysical objects or generated with ultraintense lasers. SFQEDtoolkit is an open source library designed to allow users for a straightforward implementation of SFQED processes in existing particle-in-cell (PIC) and Monte Carlo codes. Through advanced function approximation techniques, high-energy photon emission and electron-positron pair creation probability rates and energy distributions are calculated within the locally-constant-field approximation (LCFA) as well as with more advanced models [Phys. Rev. A 99, 022125 (2019)]. SFQEDtoolkit is designed to provide users with high-performance and high-accuracy, and neat examples showing its usage are provided. In the near future, SFQEDtoolkit will be enriched to model the angular distribution of the generated particles, i.e., beyond the commonly employed collinear emission approximation, as well as to model spin and polarization dependent SFQED processes. Notably, the generality and flexibility of the presented function approximation approach makes it suitable to be employed in other areas of physics, chemistry and computer science.