A finite-temperature Hartree-Fock code for shell-model Hamiltonians

作者：Bertsch G F^*; Mehlhaff J M

来源：Computer Physics Communications, 2016, 207: 518-523.

DOI：10.1016/j.cpc.2016.06.023

• Hartree-Fock
• Shell model
• Gradient method
• Nuclear levels
• Nuclear structure

The codes HFgradZ.py and HFgradT.py find axially symmetric minima of a Hartree-Fock energy functional for a Hamiltonian supplied in a shell model basis. The functional to be minimized is the Hartree-Fock energy for zero-temperature properties or the Hartree-Fock grand potential for finite temperature properties (thermal energy, entropy). The minimization may be subjected to additional constraints besides axial symmetry and nucleon numbers. A single-particle operator can be used to constrain the minimization by adding it to the single-particle Hamiltonian with a Lagrange multiplier. One can also constrain its expectation value in the zero-temperature code. Also the orbital filling can be constrained in the zero-temperature code, fixing the number of nucleons having given K-pi quantum numbers. This is particularly useful to resolve near-degeneracies among distinct minima.
Program summary
Program title: HFgradZ.py, HFgradT.py
Catalogue identifier: AFAX_v1_0
Program summary URL: http://cpc.cs.qub.ac.ukisummaries/AFAX_v1_0.html
Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland
Licensing provisions: GNU General Public License, version 3
No. of lines in distributed program, including test data, etc.: 9547
No. of bytes in distributed program, including test data, etc.: 80195
Distribution format: tar.gz
Programming language: Python (2.7).
Computer: PCs.
Operating system: Unix, Apple OSX.
RAM: 10 MBy
Classification: 4.9, 17.22.
External routines: Numpy (1.6)
Nature of problem:
Find Hartree-Fock minima of shell-model Hamiltonians
Solution method:
Gradient method with a preconditioner
Running time:
A few minutes Published by Elsevier B.V.

• 出版日期2016-10