Summary
International Symposium on Nonlinear Theory and its Applications
2010
Session Number:A1L-C
Session:
Number:A1L-C2
Performance of Adiabatic Quantum Computation using Neuron-like Interconnections
Shigeo Sato, Aiko Ono, Mitsunaga Kinjo, Koji Nakajima,
pp.39-42
Publication Date:2010/9/5
Online ISSN:2188-5079
Summary:
Quantum computation algorithms indicate possibility that non-deterministic polynomial time problems can be solved much faster than classical methods. Farhi et al. have proposed an adiabatic quantum computation (AQC) for solving the three-satisfiability (3-SAT) problem. We have proposed a neuromorphic quantum computation algorithm based on AQC, in which an analogy to an artificial neural network (ANN) is considered in order to design a Hamiltonian. However, in the neuromorphic AQC, the relation between its computation time and success rate has not been clear. In this paper, we study residual energy and the probability of correct answers as a function of computation time. The residual energy behaves as expected from the adiabatic theorem. On the other hand, the success rate strongly depends on energy level crossings of excited states during Hamiltonian evolution. The results indicate that computation time must be adjusted according to a target problem.