arXiv subjects

Håvard Helstrup

Publications and source records attributed to Håvard Helstrup.

3 recordsLinked to original sources

arXiv2025

JENA Computing Initiative WP2 Report: Software and Heterogeneous Architectures

The scientific communities of nuclear, particle, and astroparticle physics are continuing to advance and are facing unprecedented software challenges due to growing data volumes, complex computing needs, and environmental considerations. As new experiments emerge, software and computing needs must be recognised and integrated early in design phases. This document synthesises insights from ECFA, NuPECC and APPEC, representing particle physics, nuclear physics, and astroparticle physics, and presents collaborative strategies for improving software, computing frameworks, infrastructure, and career development within these fields.

physics.comp-ph↗

arXiv2023

Exploration of Differentiability in a Proton Computed Tomography Simulation Framework

Objective. Algorithmic differentiation (AD) can be a useful technique to numerically optimize design and algorithmic parameters by, and quantify uncertainties in, computer simulations. However, the effectiveness of AD depends on how "well-linearizable" the software is. In this study, we assess how promising derivative information of a typical proton computed tomography (pCT) scan computer simulation is for the aforementioned applications. Approach. This study is mainly based on numerical experiments, in which we repeatedly evaluate three representative computational steps with perturbed input values. We support our observations with a review of the algorithmic steps and arithmetic operations performed by the software, using debugging techniques. Main results. The model-based iterative reconstruction (MBIR) subprocedure (at the end of the software pipeline) and the Monte Carlo (MC) simulation (at the beginning) were piecewise differentiable. Jumps in the MBIR function arose from the discrete computation of the set of voxels intersected by a proton path. Jumps in the MC function likely arose from changes in the control flow that affect the amount of consumed random numbers. The tracking algorithm solves an inherently non-differentiable problem. Significance. The MC and MBIR codes are ready for the integration of AD, and further research on surrogate models for the tracking subprocedure is necessary.

physics.med-ph↗

arXiv2017

A comparison of proton ranges in complex media using GATE/Geant4, MCNP6 and FLUKA

The Monte Carlo (MC) simulation method is a powerful tool for radiation physicists, and several general-purpose software packages are commonly applied in a myriad of different radiation physics fields today. In medical physics, charged particle detectors for proton Computed Tomography are under development, a modality introduced in order to increase the accuracy of proton radiation therapy. MC simulations are helpful during the development and optimization phase of such detector systems. In order to justify the usage of MC for such purposes, the simulation output must be validated against experimental or theoretical data, or even cross-checked between different MC software packages. In this study, we compare three general-purpose MC software packages (GATE/Geant4, MCNP6 and FLUKA) with respect to how they predict the spatial distribution of the stopping position of protons. They are compared to each other and to semi-empirical data, using the mean proton range, the longitudinal and lateral variation of individual proton ranges, and the fraction of primary protons lost to nuclear interactions. This comparison is performed in two homogeneous materials and in a detector geometry designed for proton Computed Tomography. The three MC software packages agree well, and sufficiently reproduce the semi-empirical data. Some discrepancies are observed, such as less lateral beam spreading in GATE/Geant4, and a small deficiency in the MCNP6 proton range in water: This is consistent with previously published data. Due to the general agreement, the choice of simulation framework may be made on personal preferences. It is important to note that the choice of physics packages, simulation parameter settings and material definitions are important aspects when performing MC simulations, both during the preparation, execution and interpretation of the simulation results.

physics.med-ph↗