11.5  The KDSource McStas Component

Distributional source, based on a MCPL-format particle list, on which the Kernel Density Estimation (KDE) method is applied.

Identification

• Author: O.I.Abbate, N.S.Schmidt, updates for McStas by T.Kittelmann and P.Willendrup

• Origin: Instituto Balseiro

• Date: Dec 2022 / May 2026

Description

Distributional source, based on a MCPL-format particle list, on which the Kernel Density Estimation (KDE) method is applied.

It allows sampling more particles than the number present in a virtual, previously generated virtual source, without repeating samples, controlled via the nloop input parameter.

To function, this component requires a KDSource installation v.2.0.2 or later, as distributed on conda-forge and pypi and included with (conda-based) McStas 3.7.0 or later.

As inputs the component needs access to all of: <ol> <li>The original MPCL file <li>Outputs of a KDSource-analyzed / optimized KDE source: <ul> <li>An XML parameter-file containing the needed configuration <li>A "bandwidth" file (source_bws) </ul> </ol> For information on performing KDSource analysis, please refer to the KDSource example notebooks and the KDSource online documentation (links below).

Input parameters

Parameters in boldface are required; the others are optional.

Links

• Component source code found in file KDSource.comp.

• N.S. Schmidt et. al Annals of Nuclear Energy, Volume 177, 2022, 109309

• Test_KDSource example instrument

• KDSource online documentation (not fully updated)

• KDSource verification notebooks