54 citations · 54 across the 2 of their papers we have counts for
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Generative deep-learning reveals collective variables of Fermionic systems
Raphaël-David Lasseri, David Regnier, Mikaël Frosini +2
Complex processes ranging from protein folding to nuclear fission often follow a low-dimension reaction path parameterized in terms of a few collective variables. In nuclear theory…
Microscopic Calculation of Fission Product Yields with Particle Number Projection
Marc Verriere, David Regnier, Nicolas Schunck
Fission fragments' charge and mass distribution is an important input to applications ranging from basic science to energy production or nuclear non-proliferation. In simulations o…
The time-dependent generator coordinate method in nuclear physics
Marc Verriere, David Regnier
The emergence of collective behaviors and the existence of large amplitude motions are both central features in the fields of nuclear structure and reactions. From a theoretical po…
Future of Nuclear Fission Theory
Michael Bender, Remi Bernard, George Bertsch +30
There has been much recent interest in nuclear fission, due in part to a new appreciation of its relevance to astrophysics, stability of superheavy elements, and fundamental theory…
Combining phase-space and time-dependent reduced density matrix approach to describe the dynamics of interacting fermions
Thomas Czuba, Denis Lacroix, David Regnier +2
The possibility to apply phase-space methods to many-body interacting systems might provide accurate descriptions of correlations with a reduced numerical cost. For instance, the s…
Taming nuclear complexity with a committee of multilayer neural networks
R. -D. Lasseri, D. Regnier, J. -P. Ebran +1
We demonstrate that a committee of deep neural networks is capable of predicting the ground-state and excited energies of more than 1800 atomic nuclei with an accuracy akin to the…