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@ARTICLE{Cuzzocrea:877891,
      author       = {Cuzzocrea, Alice and Scemama, Anthony and Briels, Willem
                      and Moroni, Saverio and Filippi, Claudia},
      title        = {{V}ariational {P}rinciples in {Q}uantum {M}onte {C}arlo:
                      {T}he {T}roubled {S}tory of {V}ariance {M}inimization},
      journal      = {Journal of chemical theory and computation},
      volume       = {16},
      number       = {7},
      issn         = {1549-9626},
      address      = {Washington, DC},
      reportid     = {FZJ-2020-02496},
      pages        = {4203-4212},
      year         = {2020},
      abstract     = {We investigate the use of different variational principles
                      in quantum Monte Carlo, namely, energy and variance
                      minimization, prompted by the interest in the robust and
                      accurate estimation of electronic excited states. For two
                      prototypical, challenging molecules, we readily reach the
                      accuracy of the best available reference excitation energies
                      using energy minimization in a state-specific or
                      state-average fashion for states of different or equal
                      symmetry, respectively. On the other hand, in variance
                      minimization, where the use of suitable functionals is
                      expected to target specific states regardless of the
                      symmetry, we encounter severe problems for a variety of wave
                      functions: as the variance converges, the energy drifts away
                      from that of the selected state. This unexpected behavior is
                      sometimes observed even when the target is the ground state
                      and generally prevents the robust estimation of total and
                      excitation energies. We analyze this problem using a very
                      simple wave function and infer that the optimization finds
                      little or no barrier to escape from a local minimum or local
                      plateau, eventually converging to a lower-variance state
                      instead of the target state. For the increasingly complex
                      systems becoming in reach of quantum Monte Carlo
                      simulations, variance minimization with current functionals
                      appears to be an impractical route.},
      cin          = {IBI-4},
      ddc          = {610},
      cid          = {I:(DE-Juel1)IBI-4-20200312},
      pnm          = {551 - Functional Macromolecules and Complexes (POF3-551)},
      pid          = {G:(DE-HGF)POF3-551},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32419451},
      UT           = {WOS:000607532300019},
      doi          = {10.1021/acs.jctc.0c00147},
      url          = {https://juser.fz-juelich.de/record/877891},
}