Functional renormalization group and Kohn–Sham scheme in density functional theory
- 1. Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo 113-0033 (Japan)
- 2. Nishina Center, RIKEN, Wako 351-0198 (Japan)
- 3. ELI-NP, "Horia Hulubei" National Institute for Physics and Nuclear Engineering, RO-077125 Bucharest-Magurele (Romania)
- 4. iTHEMS Program and iTHES Research Group, RIKEN, Wako 351-0198 (Japan)
Description
Deriving accurate energy density functional is one of the central problems in condensed matter physics, nuclear physics, and quantum chemistry. We propose a novel method to deduce the energy density functional by combining the idea of the functional renormalization group and the Kohn–Sham scheme in density functional theory. The key idea is to solve the renormalization group flow for the effective action decomposed into the mean-field part and the correlation part. Also, we propose a simple practical method to quantify the uncertainty associated with the truncation of the correlation part. By taking the theory in zero dimension as a benchmark, we demonstrate that our method shows extremely fast convergence to the exact result even for the highly strong coupling regime.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.physletb.2018.02.034Additional details
Identifiers
- DOI
- 10.1016/j.physletb.2018.02.034;
- arXiv
- arXiv:1710.00650v2;
- PII
- S0370269318301369;
Publishing Information
- Journal Title
- Physics Letters. Section B
- Journal Volume
- 779
- Journal Page Range
- p. 436-440
- ISSN
- 0370-2693
- CODEN
- PYLBAJ
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 51013215
- Subject category
- S72: PHYSICS OF ELEMENTARY PARTICLES AND FIELDS;
- Descriptors DEI
- BENCHMARKS; CONVERGENCE; CORRELATIONS; DENSITY FUNCTIONAL METHOD; ENERGY DENSITY; MEAN-FIELD THEORY; RENORMALIZATION; STRONG-COUPLING MODEL
- Descriptors DEC
- CALCULATION METHODS; MATHEMATICAL MODELS; PARTICLE MODELS; VARIATIONAL METHODS
Optional Information
- Copyright
- Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.