Study on the performance of neuromorphic adiabatic quantum computation algorithms

Aiko Ono, Shigeo Sato, Mitsunaga Kinjo, Koji Nakajima

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Quantum computation algorithms indicate possibility that non-deterministic polynomial time (NP-time) problems can be solved much faster than by classical methods. Farhi et al. [2], [3] have proposed an adiabatic quantum computation (AQC) for solving the three-satisfiability problem (3-SAT). 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 the probability of correct answers is not clear yet. In this paper, we study both of residual energy and the probability of finding solution as a function of computation time. The results show that the performance of the neuromorphic AQC depends on the characteristic of Hamiltonians.

本文言語English
ホスト出版物のタイトル2008 International Joint Conference on Neural Networks, IJCNN 2008
ページ2507-2511
ページ数5
DOI
出版ステータスPublished - 2008 11 24
イベント2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, China
継続期間: 2008 6 12008 6 8

Other

Other2008 International Joint Conference on Neural Networks, IJCNN 2008
国/地域China
CityHong Kong
Period08/6/108/6/8

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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