Colloquium: Machine learning in nuclear physics
Advances in machine learning methods provide tools that have broad applicability in
scientific research. These techniques are being applied across the diversity of nuclear …
scientific research. These techniques are being applied across the diversity of nuclear …
AI for nuclear physics
P Bedaque, A Boehnlein, M Cromaz… - The European Physical …, 2021 - Springer
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Menu Find a journal Publish with us Search Cart 1.Home 2.The European Physical Journal A …
Menu Find a journal Publish with us Search Cart 1.Home 2.The European Physical Journal A …
Bayesian evaluation of incomplete fission yields
Fission product yields are key infrastructure data for nuclear applications in many aspects. It
is a challenge both experimentally and theoretically to obtain accurate and complete energy …
is a challenge both experimentally and theoretically to obtain accurate and complete energy …
Verification of neutron-induced fission product yields evaluated by a tensor decompsition model in transport-burnup simulations
Neutron-induced fission is an important research object in basic science. Moreover, its
product yield data are an indispensable nuclear data basis in nuclear engineering and …
product yield data are an indispensable nuclear data basis in nuclear engineering and …
[PDF][PDF] Artificial intelligence and machine learning in nuclear physics
This review represents a summary of recent work in the application of artificial intelligence
(AI) and machine learning (ML) in nuclear science, covering topics in nuclear theory …
(AI) and machine learning (ML) in nuclear science, covering topics in nuclear theory …
Prediction of neutron-induced fission product yields by a straightforward -nearest-neighbor algorithm
L Tong, R He, S Yan - Physical Review C, 2021 - APS
Machine learning as a very powerful tool has recently been applied in many nuclear
aspects. In this paper, a straightforward k-nearest-neighbor algorithm (KNN) combined with …
aspects. In this paper, a straightforward k-nearest-neighbor algorithm (KNN) combined with …
A tensor decomposition model for evaluating isotopic yield in neutron-induced fission
Q Song, L Zhu, J Su, H Guo - arxiv preprint arxiv:2208.11815, 2022 - arxiv.org
After constructing yield tensors with three dimensions for 851 fission products and filling the
tensors with the independent yield data from the ENDF/B-VIII. 0 database, the tensor …
tensors with the independent yield data from the ENDF/B-VIII. 0 database, the tensor …
Conservative covariance for general-purpose nuclear data evaluation
P Tamagno - The European Physical Journal A, 2021 - Springer
General-purpose evaluated nuclear data libraries requires the production of covariance data
that can be safely used for any applications. Propagated uncertainty must be conservative …
that can be safely used for any applications. Propagated uncertainty must be conservative …
Report from the ai for nuclear physics workshop
P Bedaque, A Boehnlein, M Cromaz… - arxiv preprint arxiv …, 2020 - arxiv.org
This report is an outcome of the workshop" AI for Nuclear Physics" held at Thomas Jefferson
National Accelerator Facility on March 4-6, 2020. The workshop brought together 184 …
National Accelerator Facility on March 4-6, 2020. The workshop brought together 184 …
Group Structure Machine Learning Proposal
T Saller, AT Till, NA Gibson - 2020 - osti.gov
Nuclear data is the linchpin underwriting several fundamental capabilities and mission
needs at LANL. New techniques such as machine learning can be brought to bear to solve …
needs at LANL. New techniques such as machine learning can be brought to bear to solve …