# Prospects for statistical tests of strong-field quantum electrodynamics with high-intensity lasers

## TL;DR

This paper discusses using Bayesian methods to analyze high-intensity laser-electron collision experiments for testing strong-field quantum electrodynamics, addressing challenges in measurement and parameter control.

## Contribution

It introduces an approximate Bayesian computation approach to infer SFQED effects from experimental data despite uncertainties and experimental limitations.

## Key findings

- Demonstrates the feasibility of Bayesian inference in SFQED experiments
- Provides a methodology for handling uncertain collision parameters
- Shows potential for testing deviations from perturbative SFQED

## Abstract

Exploiting high-energy electron beams colliding into high-intensity laser pulses brings an opportunity to reach high values of the dimensionless rest-frame acceleration $\chi$ and thereby invoke processes described by strong-field quantum electrodynamics (SFQED). Measuring deviations from the results of perturbative SFQED at high $\chi$ can be valuable for testing the existing predictions, as well as for guiding further theoretical developments. Nevertheless such experimental measurements are challenging due to the probabilistic nature of the interaction processes, a strong background produced by low-$\chi$ interactions and limited capabilities to control and measure the alignment and synchronization in such collision experiments. Here we elaborate a methodology of using approximate Bayesian computations (ABC) for retrieving statistically justified inferences based on the results of many repeated experiments even in case of partially unknown collision parameters that vary from experiment to experiment. As a proof of principles, we consider the problem of inferring the effective mass change due to coupling with strong-field environment.