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Q: Fachverband Quantenoptik und Photonik
Q 68: Quantum Computing and Simulation II
Q 68.8: Talk
Friday, March 15, 2024, 16:15–16:30, HS 1199
Towards solving Computer Vision optimization problems on an ion-trap-based quantum computer — •Florian Köppen1, Sebastian Becker3, Marcel Seelbach Benkner2, Michael Möller2, and Christof Wunderlich1 — 1Dept. Physik, Naturwissenschaftlich-Technische Fakultät, Universität Siegen, Siegen, Germany — 2Dept. Informatik, Naturwissenschaftlich-Technische Fakultät, Universität Siegen, Siegen, Germany — 3Mathematisch-Naturwissenschaftliche Fakultät, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
Many problems in computer vision are optimization problems with quadratic cost functions - quadratic assignment problems (QAP) - which are NP-hard and are solved on classical computers by heuristics and relaxation algorithms. A QAP can be mapped onto an Ising-type Hamiltonian, which in turn could in principle be solved efficiently and exactly on a quantum computer by quantum annealing. With the help of magnetic gradient-induced coupling (MAGIC) between trapped ion-qubits, the long-range all-to-all interaction of the Ising Model is realized[1]. Here, we present an algorithm translating a QAP into the physical coupling between qubits and further into concrete parameter settings of a microstructured, segmented ion trap. This work is guided by using quantum annealing with trapped ions for solving pertinent problems in computer vision. [1] Pilz et al., Sci. Adv. 2 (7) 2016, e1600093
Keywords: Ion Trap; Computer Vision; Quantum Annealing