Normalizing flows for thermal scattering sampling

Forget, Benoit; Alhajri, Abdulla

doi:10.1016/j.anucene.2022.108974

Title: Normalizing flows for thermal scattering sampling

Journal Article · 01 June 2022 · Annals of Nuclear Energy

DOI: https://doi.org/10.1016/j.anucene.2022.108974 · OSTI ID:1842868

Forget, Benoit; Alhajri, Abdulla

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Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

OSTI ID:: 1842868

Journal Information:: Annals of Nuclear Energy, Journal Name: Annals of Nuclear Energy Journal Issue: C Vol. 170; ISSN 0306-4549

Publisher:: ElsevierCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (13)

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Algorithmic choices in WARP – A framework for continuous energy Monte Carlo neutron transport in general 3D geometries on GPUs Bergmann, Ryan M.; Vujić, Jasmina L. Annals of Nuclear Energy, Vol. 77 https://doi.org/10.1016/j.anucene.2014.10.039	journal	March 2015
Continuous-energy Monte Carlo neutron transport on GPUs in the Shift code Hamilton, Steven P.; Evans, Thomas M. Annals of Nuclear Energy, Vol. 128 https://doi.org/10.1016/j.anucene.2019.01.012	journal	June 2019
Optimization of neutron tracking algorithms for GPU-based continuous energy Monte Carlo calculation Choi, Namjae; Kim, Kyung Min; Joo, Han Gyu Annals of Nuclear Energy, Vol. 162 https://doi.org/10.1016/j.anucene.2021.108508	journal	November 2021
OpenMC: A State-of-the-Art Monte Carlo Code for Research and Development Romano, Paul K.; Horelik, Nicholas E.; Herman, Bryan R. SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo https://doi.org/10.1051/snamc/201406016	conference	June 2014
Targeted free energy estimation via learned mappings Wirnsberger, Peter; Ballard, Andrew J.; Papamakarios, George The Journal of Chemical Physics, Vol. 153, Issue 14 https://doi.org/10.1063/5.0018903	journal	October 2020
Gravitational-wave population inference with deep flow-based generative network Wong, Kaze W. K.; Contardo, Gabriella; Ho, Shirley Physical Review D, Vol. 101, Issue 12 https://doi.org/10.1103/PhysRevD.101.123005	journal	June 2020
Equivariant Flow-Based Sampling for Lattice Gauge Theory Kanwar, Gurtej; Albergo, Michael S.; Boyda, Denis Physical Review Letters, Vol. 125, Issue 12 https://doi.org/10.1103/PhysRevLett.125.121601	journal	September 2020
Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning Noé, Frank; Olsson, Simon; Köhler, Jonas Science, Vol. 365, Issue 6457 https://doi.org/10.1126/science.aaw1147	journal	September 2019
Neural Importance Sampling Müller, Thomas; Mcwilliams, Brian; Rousselle, Fabrice ACM Transactions on Graphics, Vol. 38, Issue 5 https://doi.org/10.1145/3341156	journal	November 2019
Development of Neural Thermal Scattering (NeTS) Modules for Reactor Physics Applications Hawari, A.; Manring, C. Tranactions - 2019 Winter Meeting, Transactions of the American Nuclear Society - Volume 121 https://doi.org/10.13182/T31027	conference	January 2019
The NJOY Nuclear Data Processing System, Version 2016 Macfarlane, Robert; Muir, Douglas W.; Boicourt, R. M. https://doi.org/10.2172/1338791	report	January 2017

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