---
OA_place: repository
OA_type: green
_id: '21272'
abstract:
- lang: eng
  text: 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.
acknowledgement: "P.J.E was partially funded by the German BMWK project QCHALLenge
  (Grant No. 01MQ22008B).\r\n"
article_processing_charge: No
arxiv: 1
author:
- first_name: Peter J.
  full_name: Eder, Peter J.
  last_name: Eder
- first_name: Aron
  full_name: Kerschbaumer, Aron
  id: ade85a9c-3200-11ee-973b-91c1eb240410
  last_name: Kerschbaumer
  orcid: 0009-0002-2370-8661
- first_name: Jernej Rudi
  full_name: Finžgar, Jernej Rudi
  last_name: Finžgar
- first_name: Raimel A
  full_name: Medina Ramos, Raimel A
  id: CE680B90-D85A-11E9-B684-C920E6697425
  last_name: Medina Ramos
  orcid: 0000-0002-5383-2869
- first_name: Martin J. A.
  full_name: Schuetz, Martin J. A.
  last_name: Schuetz
- first_name: Helmut G.
  full_name: Katzgraber, Helmut G.
  last_name: Katzgraber
- first_name: Sarah
  full_name: Braun, Sarah
  last_name: Braun
- first_name: Christian B.
  full_name: Mendl, Christian B.
  last_name: Mendl
citation:
  ama: 'Eder PJ, Kerschbaumer A, Finžgar JR, et al. Quantum-guided cluster algorithms
    for combinatorial optimization. In: <i>2025 IEEE International Conference on Quantum
    Computing and Engineering</i>. IEEE; 2025. doi:<a href="https://doi.org/10.1109/qce65121.2025.00033">10.1109/qce65121.2025.00033</a>'
  apa: 'Eder, P. J., Kerschbaumer, A., Finžgar, J. R., Medina Ramos, R. A., Schuetz,
    M. J. A., Katzgraber, H. G., … Mendl, C. B. (2025). Quantum-guided cluster algorithms
    for combinatorial optimization. In <i>2025 IEEE International Conference on Quantum
    Computing and Engineering</i>. Albuquerque, NM, United States: IEEE. <a href="https://doi.org/10.1109/qce65121.2025.00033">https://doi.org/10.1109/qce65121.2025.00033</a>'
  chicago: Eder, Peter J., Aron Kerschbaumer, Jernej Rudi Finžgar, Raimel A Medina
    Ramos, Martin J. A. Schuetz, Helmut G. Katzgraber, Sarah Braun, and Christian
    B. Mendl. “Quantum-Guided Cluster Algorithms for Combinatorial Optimization.”
    In <i>2025 IEEE International Conference on Quantum Computing and Engineering</i>.
    IEEE, 2025. <a href="https://doi.org/10.1109/qce65121.2025.00033">https://doi.org/10.1109/qce65121.2025.00033</a>.
  ieee: P. J. Eder <i>et al.</i>, “Quantum-guided cluster algorithms for combinatorial
    optimization,” in <i>2025 IEEE International Conference on Quantum Computing and
    Engineering</i>, Albuquerque, NM, United States, 2025.
  ista: 'Eder PJ, Kerschbaumer A, Finžgar JR, Medina Ramos RA, Schuetz MJA, Katzgraber
    HG, Braun S, Mendl CB. 2025. Quantum-guided cluster algorithms for combinatorial
    optimization. 2025 IEEE International Conference on Quantum Computing and Engineering.
    QCE: International Conference on Quantum Computing and Engineering.'
  mla: Eder, Peter J., et al. “Quantum-Guided Cluster Algorithms for Combinatorial
    Optimization.” <i>2025 IEEE International Conference on Quantum Computing and
    Engineering</i>, IEEE, 2025, doi:<a href="https://doi.org/10.1109/qce65121.2025.00033">10.1109/qce65121.2025.00033</a>.
  short: P.J. Eder, A. Kerschbaumer, J.R. Finžgar, R.A. Medina Ramos, M.J.A. Schuetz,
    H.G. Katzgraber, S. Braun, C.B. Mendl, in:, 2025 IEEE International Conference
    on Quantum Computing and Engineering, IEEE, 2025.
conference:
  end_date: 2025-09-05
  location: Albuquerque, NM, United States
  name: 'QCE: International Conference on Quantum Computing and Engineering'
  start_date: 2025-08-30
corr_author: '1'
date_created: 2026-02-17T08:00:17Z
date_published: 2025-09-01T00:00:00Z
date_updated: 2026-02-18T08:45:56Z
day: '01'
department:
- _id: MaSe
doi: 10.1109/qce65121.2025.00033
external_id:
  arxiv:
  - '2508.10656'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.48550/arXiv.2508.10656
month: '09'
oa: 1
oa_version: Preprint
publication: 2025 IEEE International Conference on Quantum Computing and Engineering
publication_identifier:
  eisbn:
  - '9798331557362'
publication_status: published
publisher: IEEE
quality_controlled: '1'
status: public
title: Quantum-guided cluster algorithms for combinatorial optimization
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...