Paper Info
Title
A method for synthesis and optimization for linear nearest neighbor quantum circuits by parallel processing.
Abstract
In order to realize the linear nearest neighbor(LNN) of the quantum circuits and reduce the quantum cost of linear reversible quantum circuits, a method for synthesizing and optimizing linear reversible quantum circuits based on matrix multiplication of the structure of the quantum circuit is proposed. This method shows the matrix representation of linear quantum circuits by multiplying matrices of different parts of the whole circuit. The LNN realization by adding the SWAP gates is proposed and the equivalence of two ways of adding the SWAP gates is proved. The elimination rules of the SWAP gates between two overlapped adjacent quantum gates in different cases are proposed, which reduce the quantum cost of quantum circuits after realizing the LNN architecture. We propose an algorithm based on parallel processing in order to effectively reduce the time consumption for large-scale quantum circuits. Experiments show that the quantum cost can be improved by 34.31% on average and the speed-up ratio of the CPU-based algorithm can reach 4 times compared with the CPU-based algorithm. The average time optimization ratio of the benchmark large-scale circuits in RevLib processed by the parallel algorithm is 95.57% comparing with the serial algorithm.
Year
Venue
Keywords
2018
QUANTUM INFORMATION & COMPUTATION
linear nearest neighbor(LNN),matrix representation,parallel processing
Field
DocType
Volume
k-nearest neighbors algorithm,Discrete mathematics,Quantum,Topology,Parallel processing,Electronic circuit,Mathematics
Journal
18
Issue
ISSN
Citations 
13-14
1533-7146
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Zongyuan Zhang100.34
Zhijin Guan201.01
Hong Zhang327626.98
Haiying Ma400.34
Weiping Ding527844.96