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Ising models for binary clustering via adiabatic quantum computing

: Bauckhage, Christian; Brito, E.; Cvejoski, Kostadin; Ojeda,César; Sifa, Rafet; Wrobel, Stefan


Pelillo, M.:
Energy minimization methods in computer vision and pattern recognition. 11th International Conference, EMMCVPR 2017 : Venice, Italy, October 30 - November 1, 2017; Revised selected papers
Cham: Springer International Publishing, 2018 (Lecture Notes in Computer Science 10746)
ISBN: 978-3-319-78198-3 (Print)
ISBN: 978-3-319-78199-0 (Online)
ISBN: 3-319-78198-7
International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR) <11, 2017, Venice>
Fraunhofer IAIS ()

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.