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@ARTICLE{Wang:640691,
      author       = {Wang, Xiaoyang and Chai, Yahui and Feng, Xu and Guo, Yibin
                      and Jansen, Karl and Tueysuez, Cenk},
      title        = {{I}maginary {H}amiltonian variational {A}nsatz for
                      combinatorial optimization problems},
      journal      = {Physical review / A},
      volume       = {111},
      number       = {3},
      issn         = {2469-9926},
      address      = {Woodbury, NY},
      publisher    = {Inst.},
      reportid     = {PUBDB-2025-04831, arXiv:2408.09083. RIKEN-iTHEMS-Report-25},
      pages        = {032612},
      year         = {2025},
      note         = {24 pages, 17 figures},
      abstract     = {Obtaining exact solutions to combinatorial optimization
                      problems using classical computing is computationally
                      expensive. The current tenet in the field is that quantum
                      computers can address these problems more efficiently. While
                      promising algorithms require fault-tolerant quantum
                      hardware, variational algorithms have emerged as viable
                      candidates for near-term devices. The success of these
                      algorithms hinges on multiple factors, with the design of
                      the Ansatz being of the utmost importance. It is known that
                      popular approaches such as the quantum approximate
                      optimization algorithm (QAOA) and quantum annealing suffer
                      from adiabatic bottlenecks, which lead to either larger
                      circuit depth or evolution time. On the other hand, the
                      evolution time of imaginary-time evolution is bounded by the
                      inverse energy gap of the Hamiltonian, which is constant for
                      most noncritical physical systems. In this work we propose
                      an imaginary Hamiltonian variational Ansatz (iHVA) inspired
                      by quantum imaginary-time evolution to solve the MaxCut
                      problem. We introduce a tree arrangement of the parametrized
                      quantum gates, enabling the exact solution of arbitrary tree
                      graphs using the one-round iHVA. For randomly generated
                      D-regular graphs, we numerically demonstrate that the iHVA
                      solves the MaxCut problem with a small constant number of
                      rounds and sublinear depth, outperforming the QAOA, which
                      requires rounds increasing with the graph size. Furthermore,
                      our Ansatz solves the MaxCut problem exactly for graphs with
                      up to 24 nodes and D≤5, whereas only approximate solutions
                      can be derived by the classical near-optimal
                      Goemans-Williamson algorithm. We validate our simulated
                      results with hardware demonstrations on a graph with 67
                      nodes.},
      cin          = {CQTA},
      ddc          = {530},
      cid          = {I:(DE-H253)CQTA-20221102},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611)},
      pid          = {G:(DE-HGF)POF4-611},
      experiment   = {EXP:(DE-MLZ)NOSPEC-20140101},
      typ          = {PUB:(DE-HGF)16},
      eprint       = {2408.09083},
      howpublished = {arXiv:2408.09083},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2408.09083;\%\%$},
      doi          = {10.1103/PhysRevA.111.032612},
      url          = {https://bib-pubdb1.desy.de/record/640691},
}