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@INPROCEEDINGS{Wasmer:1020057,
      author       = {Wasmer, Johannes and Rüssmann, Philipp and Assent, Ira and
                      Blügel, Stefan},
      othercontributors = {Mozumder, Rubel},
      title        = {{B}enchmark study of symmetry-adapted {ML}-{DFT} models for
                      magnetically doped topological insulators},
      school       = {RWTH Aachen University},
      reportid     = {FZJ-2023-05858},
      year         = {2022},
      note         = {https://www.dpg-verhandlungen.de/year/2023/conference/skm/part/ma/session/10/contribution/1},
      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 magnetic transition metal impurity
                      dimers embedded in the topological insulator Bi2Te3. 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 MACE [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:2206.07697 (2022)},
      month         = {Mar},
      date          = {2023-03-26},
      organization  = {DPG SKM 2023, Dresden (Germany), 26
                       Mar 2023 - 31 Mar 2023},
      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) / 5111 -
                      Domain-Specific Simulation $\&$ Data Life Cycle Labs (SDLs)
                      and Research Groups (POF4-511) / AIDAS - Joint Virtual
                      Laboratory for AI, Data Analytics and Scalable Simulation
                      $(aidas_20200731)$ / HDS LEE - Helmholtz School for Data
                      Science in Life, Earth and Energy (HDS LEE)
                      (HDS-LEE-20190612) / DFG project 491111487 -
                      Open-Access-Publikationskosten / 2022 - 2024 /
                      Forschungszentrum Jülich (OAPKFZJ) (491111487)},
      pid          = {G:(DE-HGF)POF4-5211 / G:(DE-HGF)POF4-5111 /
                      $G:(DE-Juel-1)aidas_20200731$ / G:(DE-Juel1)HDS-LEE-20190612
                      / G:(GEPRIS)491111487},
      typ          = {PUB:(DE-HGF)6},
      doi          = {10.34734/FZJ-2023-05858},
      url          = {https://juser.fz-juelich.de/record/1020057},
}