<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Tal, Alexey</dc:creator> <dc:creator>Liu, Peitao</dc:creator> <dc:creator>Kresse, Georg</dc:creator> <dc:creator>Pasquarello, Alfredo</dc:creator> <dc:date>2020-09-11</dc:date> <dc:description>We investigate optical absorption spectra obtained through time-dependent density functional theory (TD-DFT) based on nonempirical hybrid functionals that are designed to correctly reproduce the dielectric function. The comparison with state-of-the-art GW calculations followed by the solution of the Bethe-Salpeter equation (BSE-GW) shows close agreement for both the transition energies and the main features of the spectra. We confront TD-DFT with BSE-GW by focusing on the model dielectric function and the local exchange-correlation kernel. The present TD-DFT approach achieves the accuracy of BSE-GW at a fraction of the computational cost.</dc:description> <dc:identifier>https://archive.materialscloud.org/record/2020.108</dc:identifier> <dc:identifier>doi:10.24435/materialscloud:gn-2p</dc:identifier> <dc:identifier>mcid:2020.108</dc:identifier> <dc:identifier>oai:materialscloud.org:444</dc:identifier> <dc:language>en</dc:language> <dc:publisher>Materials Cloud</dc:publisher> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>Optical absorption spectroscopy</dc:subject> <dc:subject>Bethe-Salpeter equation</dc:subject> <dc:subject>Hybrid-functionals</dc:subject> <dc:subject>GW</dc:subject> <dc:subject>Many-body techniques</dc:subject> <dc:subject>SNSF</dc:subject> <dc:subject>EPFL</dc:subject> <dc:title>Accurate optical spectra through time-dependent density functional theory based on screening-dependent hybrid functionals</dc:title> <dc:type>Dataset</dc:type> </oai_dc:dc>