ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jul 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
September 2026
Nuclear Technology
August 2026
Fusion Science and Technology
Latest News
MIT professor develops method to verify compliance with Outer Space Treaty
Danagoulian
Areg Danagoulian of the Department of Nuclear Science and Engineering at the Massachusetts Institute of Technology is proposing a mechanism for verifying that Earth-orbiting satellites are in compliance with the Outer Space Treaty, which prohibits the placement of nuclear weapons in space. Danagoulian’s “concept and feasibility study,” titled “Verification of the Outer Space Treaty with cosmic protons,” was published recently in the journal Nature.
Gabriel Suau, Ansar Calloo, Rémi Baron, Romain Le Tellier
Nuclear Science and Engineering | Volume 199 | Number 1 | April 2025 | Pages S295-S311
Research Article | doi.org/10.1080/00295639.2024.2340173
Articles are hosted by Taylor and Francis Online.
This paper describes the implementation of efficient and portable vectorized sweep kernels as part of the resolution of the neutron transport equation on three-dimensional Cartesian grids using the discrete ordinates (Sn) method for the angular variable and the diamond differencing (DD) scheme for the spatial discretization. Vectorization is set up along the directions within the same octant and is independent of the spatial discretization order; therefore, the extension of this technique to high-order DD or discontinuous Galerkin schemes is immediate. Our implementation is written in C++17 and relies on the Kokkos performance portability framework. This library allows one to express shared-memory parallelism (including vectorization) in a machine-independent way and supports many backends including CUDA and OpenMP. Our vectorization procedure relies on the portable single instruction multiple data types provided by Kokkos. The method has been implemented for DD schemes up to order 2 and yields promising results on CPUs supporting standard vector instructions.