12 citations · 20 across the 5 of their papers we have counts for
5 papers
Non-empirical shape dynamics of heavy nuclei with multi-task deep learning
N. Hizawa, K. Hagino
A microscopic description of nuclear fission represents one of the most challenging problems in nuclear theory. While phenomenological coordinates, such as multipole moments, have…
Analysis of a Skyrme energy density functional with deep learning
N. Hizawa, K. Hagino, K. Yoshida
Over the past decade, machine learning has been successfully applied in various fields of science. In this study, we employ a deep learning method to analyze a Skyrme energy densit…
Structural analysis of a collective subspace in the dynamical generator coordinate method
N. Hizawa
In nuclear theory, the generator coordinate method (GCM), a type of configuration mixing method, is often used for the microscopic description of collective motions. However, the G…
Applications of the dynamical generator coordinate method to quadrupole excitations
N. Hizawa, K. Hagino, K. Yoshida
We apply the dynamical generator coordinate method (DGCM) with a conjugate momentum to a nuclear collective excitation. To this end, we first discuss how to construct a numerically…
Generator coordinate method with a conjugate momentum: application to the particle number projection
N. Hizawa, K. Hagino, K. Yoshida
We discuss an extension of the generator coordinate method (GCM) by taking simultaneously a collective coordinate and its conjugate momentum as generator coordinates. To this end,…