Ising Models for Binary Clustering via Adiabatic Quantum Computing

  • Christian BauckhageEmail author
  • E. Brito
  • K. Cvejoski
  • C. Ojeda
  • Rafet Sifa
  • S. Wrobel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10746)


Existing adiabatic quantum computers are tailored towards minimizing the energies of Ising models. The quest for implementations of pattern recognition or machine learning algorithms on such devices can thus be seen as the quest for Ising model (re-)formulations of their objective functions. In this paper, we present Ising models for the tasks of binary clustering of numerical and relational data and discuss how to set up corresponding quantum registers and Hamiltonian operators. In simulation experiments, we numerically solve the respective Schrödinger equations and observe our approaches to yield convincing results.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Fraunhofer IAISSankt AugustinGermany
  2. 2.B-ITUniversity of BonnBonnGermany

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