Summary
International Symposium on Nonlinear Theory and its Applications
2005
Session Number:1-2-5
Session:
Number:1-2-5-4
Artificial Neural Network-inspired Quantum Adiabatic Evolution Algorithm with Energy Dissipation
Mitsunaga Kinjo, Shigeo Sato, Yuuki Nakamiya, Koji Nakajima,
pp.198-201
Publication Date:2005/10/18
Online ISSN:2188-5079
DOI:10.34385/proc.40.1-2-5-4
PDF download (164.3KB)
Summary:
An ANN(artificial neural network)-inspired quantum adiabatic evolution algorithm, which is a new quantum computation algorithm based on both the ANNlike method and the adiabatic Hamiltonian evolution, has been proposed for solving a combinatorial optimization problem. However, it has been known that the adiabatic evolution algorithm can not be applied to a quantum system with degenerated states during the evolution of a Hamiltonian. In order to remove this limitation, we propose an improved ANN-inspired algorithm with energy dissipation and discuss how to use this algorithm for solving an optimization problem.