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@INPROCEEDINGS{Wasmer:1020055,
      author       = {Wasmer, Johannes and Mozumder, Rubel and Rüssmann, Philipp
                      and Assent, Ira and Blügel, Stefan},
      title        = {{B}enchmark study of symmetry-adapted {ML}-{DFT} models for
                      magnetically doped topological insulators},
      school       = {RWTH Aachen University},
      reportid     = {FZJ-2023-05856},
      year         = {2022},
      note         = {Abstract also available on the event website
                      https://www.psik2022.net/},
      abstract     = {We present a benchmark study of surrogate models for
                      impurities embedded into crystalline solids. Using the
                      Korringa-Kohn-Rostoker Green Function method [1], we have
                      built databases of several thousand calculations of single
                      impurities (monomers) embedded into different elemental
                      crystals, as well as of the topological insulator Bi2Te3,
                      magnetically co-doped with transition metal impurities
                      (dimers). We predict the converged monomer impurity electron
                      potential and the isotropic exchange interaction of the
                      impurity dimer in the classical Heisenberg model. From these
                      surrogates, we intend to build transferable models for
                      larger systems in the future, which will accelerate the
                      convergence of our DFT codes. The study compares various
                      recent E(3)-equivariant models such as ACE and NequIP [2] in
                      terms of performance and reproducible end-to-end
                      workflows.[1] P. Rüßmann et al., npj Comput Mater 7, 13
                      (2021)[2] I. Batatia et al., arXiv:2205.06643 (2022)},
      month         = {Aug},
      date          = {2022-08-22},
      organization  = {Psi-k 2022 Conference, Lausanne
                       (Switzerland), 22 Aug 2022 - 25 Aug
                       2022},
      subtyp        = {After Call},
      cin          = {IAS-1 / PGI-1},
      cid          = {I:(DE-Juel1)IAS-1-20090406 / I:(DE-Juel1)PGI-1-20110106},
      pnm          = {5211 - Topological Matter (POF4-521) / HDS LEE - Helmholtz
                      School for Data Science in Life, Earth and Energy (HDS LEE)
                      (HDS-LEE-20190612) / AIDAS - Joint Virtual Laboratory for
                      AI, Data Analytics and Scalable Simulation
                      $(aidas_20200731)$},
      pid          = {G:(DE-HGF)POF4-5211 / G:(DE-Juel1)HDS-LEE-20190612 /
                      $G:(DE-Juel-1)aidas_20200731$},
      typ          = {PUB:(DE-HGF)24},
      doi          = {10.34734/FZJ-2023-05856},
      url          = {https://juser.fz-juelich.de/record/1020055},
}