Automated CR-39 pit detection for energy and angular characterization of laser-driven ion beams

Abstract

Accurate characterization of ion beams from sub-MeV to multi-MeV energies is essential for diagnostics in laser-driven ion acceleration and fusion research. CR-39 detectors are widely used to measure absolute ion yields, while ion energy and incidence angle can be inferred from etched-pit geometries. In this study, we present an automated CR-39 pit detection method that enables reliable extraction of pit geometries from two-dimensional optical micrographs, with improved discrimination of overlapping pits under high-flux conditions. This capability enables reliable analysis in high-density regimes where conventional methods are limited by significant track overlap. By integrating the detected pit shapes with a pit-formation model based on Monte Carlo simulations of restricted energy loss, energy and angular characterization of laser-driven proton beams is achieved with enhanced precision and computational efficiency. The proposed framework provides a robust and scalable approach for automated CR-39 analysis and is applicable to a broad range of ion-beam diagnostics and spectroscopy.