Nuclear Data for the Next Decade

Session

Machine Learning for Nuclear Data

003

10 mars 2026, 09:00

Amphithéâtre Farabeuf, Campus des Cordeliers, Paris

Présidents de session

Machine Learning for Nuclear Data

• David Regnier (CEA, DAM, DIF)

18. Modeling Prompt Neutrons and Gamma Rays from Fission Fragments: CGMF and the Role of Machine Learning

Dr Amy Lovell (LANL)

10/03/2026 09:00

Challenges of Nuclear Data: Machine Learning

Fission event generators have become the state-of-the-art tool for studying correlations between the neutrons and  rays emitted from fission and how these observables depend on the initial conditions of the fission fragments that emit them. CGMF is one such Monte Carlo fission fragment event generator, developed at Los Alamos Laboratory. Phenomenological models are constructed for the fission...

19. Deep-learning nuclear cross sections

Dr Nicolas Schunck (LLNL)

10/03/2026 09:25

Challenges of Nuclear Data: Machine Learning

Beyond their many impacts in our societies, artificial intelligence and machine learning are also often seen as representing a paradigm shift in scientific research. Their unsurpassed ability to learn complex patterns in large datasets have found multiple applications ranging from designing powerful emulators of complex theories, to processing massive amounts of data to opening new ways to...