Microscopically-based energy density functionals for nuclei using the density matrix expansion: Full optimization and validation
R. Navarro Perez, N. Schunck, A. Dyhdalo, R.J. Furnstahl, S.K. Bogner

TL;DR
This paper develops and validates a microscopically-based nuclear energy density functional derived from chiral effective field theory, optimized for large-scale nuclear calculations, and demonstrates improved predictive accuracy over phenomenological models.
Contribution
It introduces a new functional form based on the density matrix expansion of chiral potentials, fully optimized and validated for nuclear and neutron matter, nuclear masses, and shell structure.
Findings
Functional performs better than Skyrme models in predicting nuclear properties.
Higher-order chiral terms systematically improve binding energy predictions.
Functional is validated on diverse nuclear and neutron matter calculations.
Abstract
We seek to obtain a usable form of the nuclear energy density functional that is rooted in the modern theory of nuclear forces. We thus consider a functional obtained from the density matrix expansion of local nuclear potentials from chiral effective field theory. We propose a parametrization of this functional carefully calibrated and validated on selected ground-state properties that is suitable for large-scale calculations of nuclear properties. The first component of this functional is a non-local functional of the density and corresponds to the direct part (Hartree term) of the expectation value of local chiral potentials on a Slater determinant. A second component is a local functional of the density and is obtained by applying the density matrix expansion to the exchange part (Fock term) of the expectation value of the local chiral potential. We apply the UNEDF2 optimization…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
