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2024 MCATK Status.

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Title: 2024 MCATK Status.
Authors: Sweezy, Jeremy, Burke, Tim, Adams, Terry, Bolding, Simon, Giron, Jesse, Long, Alex, Nolen, Steven, Skinner, Corey, Tumulak, Aaron, Zukaitis, Tony, McCartney, Austin, Trahan, Travis
Source: EPJ Nuclear Sciences & Technologies; 2025, Vol. 11, p1-10, 10p
Subject Terms: MONTE Carlo method, PARALLEL programming, LABORATORIES, C++, PYTHON programming language
Company/Entity: LOS Alamos National Laboratory
Abstract: The Monte Carlo Application Toolkit (MCATK) is a C++ component-based Monte Carlo particle transport capability that has been in development by Los Alamos National Laboratory (LANL) since 2008. This paper presents an update on MCATK's current capabilities, focusing on notable advancements made since the previous status reports (T. Adams, S. Nolen, J. Sweezy, A. Zukaitis, J. Campbell, T. Goorley, S. Greene, R. Aulwes, Ann. Nucl. Energy 82, 41 (2015), T.J. Trahan, T.R. Adams, R.T. Aulwes, S.D. Nolen, J.E. Sweezy, C.J. Werner, Monte Carlo Application ToolKit (MCATK): Advances for 2017, in International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering (Jeju, Korea, 2017). Key enhancements include a Python interface, photon physics, expanded geometry modeling options, improved tallies, and a broader selection of source definitions. Additionally, MCATK now offers stochastic system solvers, shared memory parallelism, and GPU acceleration of ray-tracing tallies. These enhancements have significantly expanded MCATK's functionality. [ABSTRACT FROM AUTHOR]
Copyright of EPJ Nuclear Sciences & Technologies is the property of EDP Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: The Monte Carlo Application Toolkit (MCATK) is a C++ component-based Monte Carlo particle transport capability that has been in development by Los Alamos National Laboratory (LANL) since 2008. This paper presents an update on MCATK's current capabilities, focusing on notable advancements made since the previous status reports (T. Adams, S. Nolen, J. Sweezy, A. Zukaitis, J. Campbell, T. Goorley, S. Greene, R. Aulwes, Ann. Nucl. Energy 82, 41 (2015), T.J. Trahan, T.R. Adams, R.T. Aulwes, S.D. Nolen, J.E. Sweezy, C.J. Werner, Monte Carlo Application ToolKit (MCATK): Advances for 2017, in International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering (Jeju, Korea, 2017). Key enhancements include a Python interface, photon physics, expanded geometry modeling options, improved tallies, and a broader selection of source definitions. Additionally, MCATK now offers stochastic system solvers, shared memory parallelism, and GPU acceleration of ray-tracing tallies. These enhancements have significantly expanded MCATK's functionality. [ABSTRACT FROM AUTHOR]
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  Label:
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  Data: <i>Copyright of EPJ Nuclear Sciences & Technologies is the property of EDP Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1051/epjn/2025035
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      – SubjectFull: LOS Alamos National Laboratory
        Type: general
      – SubjectFull: MONTE Carlo method
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      – SubjectFull: PARALLEL programming
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      – SubjectFull: LABORATORIES
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              Text: 2025
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