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.