The current investigation focuses on detailed analysis of the anchor-based optimization approach (ABOA), its comparison with alternative global fitting protocols and on the global analysis of the truncation of basis effects in the calculation of binding energies. It is shown that ABOA provides a solution which is close to that obtained in alternative approaches but at small portion of their computational time. The application of a softer correction function after few initial iterations of ABOA stabilizes and speeds up its convergence. The numerical errors in the calculation of binding energies related to the truncation of bosonic and fermionic bases have been globally investigated with respect of asymptotic values corresponding to the infinite basis in the framework of covariant density functional theory (CDFT). These errors typically grow with the increase of the mass and deformation of the nuclei. To reduce such errors in bosonic sector below 10 keV for almost all nuclei with proton number $Z<120$ one should truncate the bosonic basis at $N_B=28$ instead of presently used $N_B=20$. The reduction of the errors in binding energies due to the truncation of the fermionic basis in CDFT is significantly more numerically costly. For the first time it is shown that the pattern and the speed of the convergence of binding energies as a function of the size of fermionic basis given by $N_F$ depend on the type of covariant energy density functional. The use of explicit density dependence of the meson-nucleon coupling constants or point couplings slows substantially the speed of convergence of binding energies as a function of $N_F$. The present paper clearly indicates the need for accounting of infinite basis corrections for accurate calculation of binding energies and for fitting more precise next-generation covariant energy density functionals: note that such corrections are neglected in the present generation of the functionals. A procedure for finding the asymptotic values of binding energies is suggested in the present paper: it allows better control of numerical errors.

• Received 30 October 2023
• Accepted 26 January 2024

DOI:https://doi.org/10.1103/PhysRevC.109.024321