Publications
Publication Information
| Title | Nuclei with up to A = 6 nucleons with artificial neural network wave functions |
| Authors | Alex Gnech, Corey Adams, Nicholas Brawand, Giuseppe Carleo, Alessandro Lovato, Noemi Rocco |
| JLAB number | JLAB-THY-21-3484 |
| LANL number | arXiv:2108.06836 |
| Other number | DOE/OR/23177-5307 |
| Document Type(s) | (Journal Article) |
| Associated with EIC: | No |
| Supported by Jefferson Lab LDRD Funding: | No |
| Funding Source: | Nuclear Physics (NP) |
|
Journal Compiled for Few Body Systems Volume 63 Page(s) 1 Refereed | |
| Publication Abstract: | The ground-breaking works of Weinberg have opened the way to calculations of atomic nuclei that are based on systematically improvable Hamiltonians. Solving the associated many-body Schr ?odinger equation involves non-trivial difficulties, due to the non-perturbative nature and strong spin-isospin dependence of nuclear interactions. Artificial neural networks have proven to be able to compactly represent the wave functions of nuclei with up to A = 4 nucleons. In this work, we extend this approach to 6Li and 6He nuclei, using as input a leading-order pionless effective field theory Hamiltonian. We successfully benchmark their binding energies, point-nucleon densities, and radii with the highly-accurate hyperspherical harmonics method. |
| Experiment Numbers: | |
| Group: | THEORY CENTER |
| Document: | |
| DOI: | https://doi.org/10.1007/s00601-021-01706-0 |
| Accepted Manuscript: | 2108.06836.pdf |
| Supporting Documents: | |
| Supporting Datasets: | |