September 24, 2025 Dataset Open Access

Shah, Karan; Cangi, Attila

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  <dc:creator>Shah, Karan</dc:creator>
  <dc:creator>Cangi, Attila</dc:creator>
  <dc:date>2025-09-24</dc:date>
  <dc:description>This repository contains the dataset supporting the paper "Machine Learning Time Propagators for Time-Dependent Density Functional Theory Simulations" by Karan Shah and Attila Cangi. It comprises time-dependent density functional theory (TDDFT) simulations of one-dimensional diatomic molecules under laser excitation. The data is used to train and evaluate autoregressive Fourier Neural Operator (FNO) models that serve as ML time propagators for electron density evolution.</dc:description>
  <dc:identifier>https://rodare.hzdr.de/record/3994</dc:identifier>
  <dc:identifier>10.14278/rodare.3994</dc:identifier>
  <dc:identifier>oai:rodare.hzdr.de:3994</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>doi:10.48550/arXiv.2508.16554</dc:relation>
  <dc:relation>url:https://www.hzdr.de/publications/Publ-41882</dc:relation>
  <dc:relation>doi:10.14278/rodare.3993</dc:relation>
  <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Physics-informed machine learning</dc:subject>
  <dc:subject>TDDFT</dc:subject>
  <dc:subject>RT-TDDFT</dc:subject>
  <dc:subject>Fourier Neural Operators</dc:subject>
  <dc:title>Dataset for Machine Learning Time Propagators for Time-Dependent Density Functional Theory Simulations</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
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