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@ARTICLE{Rodekamp:1008810,
      author       = {Rodekamp, Marcel and Gäntgen, Christoph},
      title        = {{M}itigating the {H}ubbard {S}ign {P}roblem. {A} {N}ovel
                      {A}pplication of {M}achine {L}earning},
      journal      = {Proceedings of Science / International School for Advanced
                      Studies},
      volume       = {LATTICE2022},
      issn         = {1824-8039},
      address      = {Trieste},
      publisher    = {SISSA},
      reportid     = {FZJ-2023-02484},
      pages        = {032},
      year         = {2022},
      abstract     = {Many fascinating systems suffer from a severe (complex
                      action) sign problem preventing us from calculating them
                      with Markov Chain Monte Carlo simulations. One promising
                      method to alleviate the sign problem is the transformation
                      of the integration domain towards Lefschetz Thimbles.
                      Unfortunately, this suffers from poor scaling originating in
                      numerically integrating of flow equations and evaluation of
                      an induced Jacobian. In this proceedings we present a new
                      preliminary Neural Network architecture based on
                      complex-valued affine coupling layers. This network performs
                      such a transformation efficiently, ultimately allowing
                      simulation of systems with a severe sign problem. We test
                      this method within the Hubbard Model at finite chemical
                      potential, modelling strongly correlated electrons on a
                      spatial lattice of ions.},
      organization  = {The 39th International Symposium on
                       Lattice Field Theory, Bonn (Germany)},
      keywords     = {Strongly Correlated Electrons (cond-mat.str-el) (Other) /
                      High Energy Physics - Lattice (hep-lat) (Other) / FOS:
                      Physical sciences (Other)},
      cin          = {JSC / IAS-4},
      ddc          = {530},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IAS-4-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / DFG project
                      196253076 - TRR 110: Symmetrien und Strukturbildung in der
                      Quantenchromodynamik (196253076) / SDS005 - Towards an
                      integrated data science of complex natural systems
                      (PF-JARA-SDS005)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(GEPRIS)196253076 /
                      G:(DE-Juel-1)PF-JARA-SDS005},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)16},
      doi          = {10.22323/1.430.0032},
      url          = {https://juser.fz-juelich.de/record/1008810},
}