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@ARTICLE{Yachmenev:639642,
      author       = {Yachmenev, Andrey and Vogt, Emil and Corral, Álvaro
                      Fernández and Saleh, Yahya},
      title        = {{T}aylor-mode automatic differentiation for constructing
                      molecular rovibrational {H}amiltonian operators},
      journal      = {The journal of chemical physics},
      volume       = {163},
      number       = {7},
      issn         = {0021-9606},
      address      = {Melville, NY},
      publisher    = {American Institute of Physics},
      reportid     = {PUBDB-2025-04599},
      pages        = {072501},
      year         = {2025},
      abstract     = {We present an automated framework for constructing Taylor
                      series expansions of rovibrational kinetic and potential
                      energy operators for arbitrary molecules, internal
                      coordinate systems, and molecular frame embedding
                      conditions. Expressing operators in a sum-of-products form
                      allows for computationally efficient evaluations of matrix
                      elements in product basis sets. Our approach uses automatic
                      differentiation tools from the Python machine learning
                      ecosystem, particularly the JAX library, to efficiently and
                      accurately generate high-order Taylor expansions of
                      rovibrational operators.},
      cin          = {FS-CFEL-CMI},
      ddc          = {530},
      cid          = {I:(DE-H253)FS-CFEL-CMI-20220405},
      pnm          = {631 - Matter – Dynamics, Mechanisms and Control
                      (POF4-631) / Quantum-mechanical modeling of the dissociation
                      of hydrogen bonds (101155136) / HIDSS-0002 - DASHH: Data
                      Science in Hamburg - Helmholtz Graduate School for the
                      Structure of Matter $(2019_IVF-HIDSS-0002)$},
      pid          = {G:(DE-HGF)POF4-631 / G:(EU-Grant)101155136 /
                      $G:(DE-HGF)2019_IVF-HIDSS-0002$},
      experiment   = {EXP:(DE-MLZ)NOSPEC-20140101},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1063/5.0287347},
      url          = {https://bib-pubdb1.desy.de/record/639642},
}