دانلود رایگان مقاله کد دمای محدود هارتری فوک برای پوسته مدل همیلتونی

Abstract

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 Kπ quantum numbers. This is particularly useful to resolve near-degeneracies among distinct minima.

7. Output

The principal outputs of the code, written to the terminal, are the number of iterations niter, the final energy E, and the expectation value of the quadrupole operator Q or other single-particle operator provided in the input data. The finitetemperature code also reports the entropy of the ensemble, S in Eq. (13). The code also writes to terminal a table of orbital properties. The columns are: (1) index for the orbital; (2) index of the block containing the orbital; (3) charge of the nucleon (0 or 1); (4) K quantum number; (5) parity π: 0 or 1 for even or odd parity respectively; (6) occupation number f , integer for zero temperature and floating-point for finite temperature; (7) single-particle energy. In addition, the code writes the final U matrix and f array to files u_new.dat and n_new.dat, respectively. In the zerotemperature code the second file has two lines. The first line gives the number of occupied orbitals in each block and can be used as an input file to HFgradZ. The second line gives the occupation number for each orbital in the format needed by HFgradT. Apart from that, the two files are in proper format to be used as input to rerun the minimization. If the minimization is converged, the rerun should only require one iteration step.