Machine Learning in Nuclear Physics

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8-9 December 2025

 

PROGRAM    ProjectESNTnuclMLdec2025.pdf

Machine Learning in Nuclear Physics: Integrative Approaches Across Disciplinary Boundaries

Organizers: D. Regnier (CEA DAM DIF, contact [at] cea.fr), J.-P. Ebran (CEA DAM, DIF), A. Pastore (CEA DES IRESNE)

 

 

Nuclear physics research confronts increasingly complex computational and analytical challenges characterized by (i) high-dimensional, non-linear systems, (ii) massive experimental datasets, (iii) computational limitations in traditional modeling approaches and (iv) increasing complexity of theoretical frameworks.

Machine learning (ML) and artificial intelligence (AI) represent a paradigm shift in addressing these fundamental challenges, offering transformative methodological innovations across multiple research domains.

This workshop will focus on fostering collaborations between experts from the CEA DAM, DRF, and DES, as well as external specialists in AI and nuclear physics. By uniting diverse expertise, we aim to identify key challenges in nuclear physics where AI can provide transformative solutions, establish methodological frameworks for integrating AI into existing research pipelines and define a strategic roadmap for future research and collaborations in this field.

In summary, the goal of the workshop is to bring together practitioners of machine learning in nuclear physics to explore:
• Nuclear structure modeling
• Fission dynamics
• Nuclear data evaluation
• Experimental data analysis

 

 

Talks

 

Alice Bernard (CEA, DAM, DIF) Learning smooth ensembles of Bogoliubov vacua

 

David Regnier (CEA, DAM, DIF)  An overview of machine learning for nuclear physics

 

Chlöe Fougères (CEA, DAM, DIF) On the use of genetic algorithms towards prompt emission properties in fission

 

Dunstan Becht (CEA, DAM, DIF) Accelerating full CI calculations with ML

 

Marc Verriere (CEA, DAM, DIF) Building surrogate models of nuclear density functional theory with Gaussian processes and autoencoders

 

Enzo Thiriont-Bernolle (CEA, DAM, DIF) Eigenvector continuation of PGCM states for nuclear structure

 

Abdel Chebboubi (CEA, DES, IRESNE, DER, SPRC)  Machine learning and prompt neutron/gamma emission from fission

 

Jean-Marc Palau (CEA, DES, IRESNE, DER, SPRC) Bayesian inference in the context of neutronic calculations

 

Stavros Bofos (CEA, DES, IRESNE, DER, SPRC) Emulating the PGCM approach to nuclear structure

 

Thomas Duguet (CEA DRF, IRFU, DPhN) Reduced basis method for the many-body problem

 

Jérôme Bobin (CEA DRF, IRFU, Dedip) 
Automatic identification and quantification of y-emitting radionuclides with spectral variability using a hybrid Machine, Learning unmixing method

 

Olivier Limousin (CEA DRF, IRFU, DAp)
Artificial gamma ray spectra simulation using Generative Adversarial Networks (GANs) and Supervised Generative Networks (SGNs)

 

Diego Ramos (GANIL) Particle identification at VAMOS++ with machine learning techniques

 

Clément Besnard-Vauterin (CEA LIST LNE-LNHB)
Experimental data-driven modeling and prediction of (γ,n) cross-sections with physics-informed neural networks and gradient boosted decision trees

 

Mathieu Thevenin (CEA IRAMIS SPEC)
A methodology for alpha particles identification in liquid scintillation using a cost-efficient Artificial Neural Network

 

Antonin Valente (ENSICAEN CNRS LPC)
Toward a better characterization of the nuclear EOS using central collisions around Fermi energy

 

Guillaume Scamps (CNRS L2IT-IN2P3) Skyrme-Hartree-Fock-Bogoliubov mass models on a 3D mesh: effect of triaxial shape

 

Mohammed Nejmi (CNRS L2IT-IN2P3) Machine learning time-dependent mean-field simulations of heavy-ion collisions

 

Denis Lacroix (CNRS/IN2P3, IJCLab) Reinforcement learning on quantum computers

 

Olivier Stezowski (CNRS/IN2P3, IP2I Lyon) Machine learning approaches to unfold the NEDA detector array
 

 

 

 

Preliminary program 

 

	Monday  8th Dec.	Tuesday 9
9h30	Talk	Talk
10h	Talk	Talk
10h30	Talk	Talk
11h30	Talk	Talk
11h	Talk	Talk
11h30	Talk	Talk
12h	Talk	Talk
12h30	Lunch	Lunch
14h	Talk	Talk
14h30	Talk	Talk
15h	Talk	Talk
15h30	Break	Break
16h	Talk	Talk
16h30	Talk	Talk
17h	End	End

 

 

 

 

 

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