TY - JOUR
T1 - Small angle neutron scattering in McStas
T2 - Optimization for high-throughput virtual experiments
AU - Robledo, José Ignacio
AU - Lieutenant, Klaus
AU - Willendrup, Peter
PY - 2024
Y1 - 2024
N2 - In this work, we present the development of small-angle scattering components in McStas that describe the neutron interaction with 70 different form and structure factors. We describe the considerations taken into account for the generation of these components, such as the incorporation of polydispersity and orientational distribution effects in the Monte Carlo simulation. These models can be parallelized by means of multi-core simulations and graphical processing units. The acceleration schemes for the aforementioned models are benchmarked, and the resulting performance is presented. This allows the estimation of computation times in high-throughput virtual experiments. The presented work enables the generation of large datasets of virtual experiments that can be explored and used by machine learning algorithms.
AB - In this work, we present the development of small-angle scattering components in McStas that describe the neutron interaction with 70 different form and structure factors. We describe the considerations taken into account for the generation of these components, such as the incorporation of polydispersity and orientational distribution effects in the Monte Carlo simulation. These models can be parallelized by means of multi-core simulations and graphical processing units. The acceleration schemes for the aforementioned models are benchmarked, and the resulting performance is presented. This allows the estimation of computation times in high-throughput virtual experiments. The presented work enables the generation of large datasets of virtual experiments that can be explored and used by machine learning algorithms.
U2 - 10.1177/10238166251313936
DO - 10.1177/10238166251313936
M3 - Journal article
SN - 1023-8166
VL - 26
SP - 173
EP - 185
JO - Journal of Neutron Research
JF - Journal of Neutron Research
IS - 4
ER -