2016/03/31 by M. J. P. Hodgson, J. D. Ramsden, R. W. Godby · 3 citations
Materials Science · Mathematics · Physics and Astronomy · #Advanced Chemical Physics Studies #Artificial intelligence #Computer science #Correlation #Density functional theory #Electron #Geometry #Kohn–Sham equations #Machine Learning in Materials Science #Mathematics #Physics #Quantum #Quantum mechanics #Spectroscopy and Quantum Chemical Studies #Statistical physics #Theoretical physics #Variety (cybernetics) #cond-mat.str-el #physics.chem-ph
paper · pdf · doi:10.1103/physrevb.93.155146
published as Phys. Rev. B 93, 155146 (2016)
arxiv created 2016/04/19 · openalex publication_date 2016/04/25 · arxiv updated 2021/01/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The need for a reliable quantum description of the motion of interacting electrons in nanostructures is of ever-growing significance. The usual approximations for the exchange-correlation (xc) potential of density functional theory can prove inadequate, especially in the time-dependent regime and when correlation is strong. Spatial steps (and related features) in the xc potential, in particular, are known to be frequently crucial for the accurate description of electron densities, but present challenges for the common xc approximations. Using a variety of model systems, the authors exhibit the nature of these steps, and describe the principles that determine their properties, to inform the development of improved functionals.