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mcstas_gisans: combining ray tracing with the distorted-wave Born approximation using McStas and BornAgain for virtual GISANS experiments

Milán Klausz*, Artur Glavic, Sebastian Köhler, Thomas Arnold*, Nicolò Paracini, Philipp Gutfreund, Marité Cárdenas, Max Wolff, Tommy Nylander*

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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Abstract

The mcstas_gisans framework is a collection of Python scripts and modules to facilitate the simulation of grazing-incidence small-angle neutron scattering (GISANS) experiments. This approach combines McStas instrument simulation with BornAgain sample modeling capabilities. The Monte Carlo Particle Lists format for particle trajectory allows exchange between simulations that enables seamless transition from instrument modeling to sample scattering analysis. The Python-based processing utilities handle data transformation, scaling to virtual experiment times for absolute intensities, and visualization. The required software environment is managed through Conda, ensuring reproducible deployments across platforms. This integrated approach facilitates accurate simulation and analysis and enables the comparison of the GISANS capability of different neutron scattering instruments.
OriginalsprogEngelsk
TidsskriftJournal of Applied Crystallography
Vol/bind59
Udgave nummer3
Sider (fra-til)827-836
ISSN0021-8898
DOI
StatusUdgivet - 2026

Bibliografisk note

This article is part of a collection of articles related to the International Conference on Neutron Scattering, ICNS2025.

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