---
res:
  bibo_abstract:
  - Finding the ground state of Ising spin glasses is notoriously difficult due to
    disorder and frustration. Often, this challenge is framed as a combinatorial optimization
    problem, for which a common strategy employs simulated annealing, a Monte Carlo
    (MC)-based algorithm that updates spins one at a time. Yet, these localized updates
    can cause the system to become trapped in local minima. Cluster algorithms (CAs)
    were developed to address this limitation and have demonstrated considerable success
    in studying ferromagnetic systems; however, they tend to encounter percolation
    issues when applied to generic spin glasses. In this work, we introduce a novel
    CA designed to tackle these challenges by leveraging precomputed two-point correlations,
    aiming solve combinatorial optimization problems in the form of Max-Cut more efficiently.
    In our approach, clusters are formed probabilistically based on these correlations.
    Various classical and quantum algorithms can be employed to generate correlations
    that embody information about the energy landscape of the problem. By utilizing
    this information, the algorithm aims to identify groups of spins whose simultaneous
    flipping induces large transitions in configuration space with high acceptance
    probability - even at low energy levels - thereby escaping local minima more effectively.
    Notably, clusters generated using correlations from the Quantum Approximate Optimization
    Algorithm exhibit high acceptance rates at low temperatures. These acceptance
    rates often increase with circuit depth, accelerating the algorithm and enabling
    more efficient exploration of the solution space.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Peter J.
      foaf_name: Eder, Peter J.
      foaf_surname: Eder
  - foaf_Person:
      foaf_givenName: Aron
      foaf_name: Kerschbaumer, Aron
      foaf_surname: Kerschbaumer
      foaf_workInfoHomepage: http://www.librecat.org/personId=ade85a9c-3200-11ee-973b-91c1eb240410
    orcid: 0009-0002-2370-8661
  - foaf_Person:
      foaf_givenName: Jernej Rudi
      foaf_name: Finžgar, Jernej Rudi
      foaf_surname: Finžgar
  - foaf_Person:
      foaf_givenName: Raimel A
      foaf_name: Medina Ramos, Raimel A
      foaf_surname: Medina Ramos
      foaf_workInfoHomepage: http://www.librecat.org/personId=CE680B90-D85A-11E9-B684-C920E6697425
    orcid: 0000-0002-5383-2869
  - foaf_Person:
      foaf_givenName: Martin J. A.
      foaf_name: Schuetz, Martin J. A.
      foaf_surname: Schuetz
  - foaf_Person:
      foaf_givenName: Helmut G.
      foaf_name: Katzgraber, Helmut G.
      foaf_surname: Katzgraber
  - foaf_Person:
      foaf_givenName: Sarah
      foaf_name: Braun, Sarah
      foaf_surname: Braun
  - foaf_Person:
      foaf_givenName: Christian B.
      foaf_name: Mendl, Christian B.
      foaf_surname: Mendl
  bibo_doi: 10.1109/qce65121.2025.00033
  dct_date: 2025^xs_gYear
  dct_language: eng
  dct_publisher: IEEE@
  dct_title: Quantum-guided cluster algorithms for combinatorial optimization@
...