Compiling Single Round QCCP-X Quantum Circuits by Genetic Algorithm

被引:3
作者
Arufe, Lis [1 ]
Rasconi, Riccardo [2 ]
Oddi, Angelo [2 ]
Varela, Ramiro [1 ]
Angel Gonzalez, Miguel [1 ]
机构
[1] Univ Oviedo, Dept Comp Sci, Campus Gijon, Gijon 33204, Spain
[2] Consiglio Nazl Ric ISTC CNR, Ist Sci & Tecnol Cogniz, Via S Martino Battaglia 44, I-00185 Rome, Italy
来源
BIO-INSPIRED SYSTEMS AND APPLICATIONS: FROM ROBOTICS TO AMBIENT INTELLIGENCE, PT II | 2022年 / 13259卷
关键词
D O I
10.1007/978-3-031-06527-9_9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The circuit model is one of the leading quantum computing architectures. In this model, a quantum algorithm is given by a set of quantum gates that must be distributed on the quantum computer over time, subject to a number of constraints. This process gives rise to the Quantum Circuit Compilation Problem (QCCP), which is in fact a hard scheduling problem. In this paper, we consider a compilation problem derived from the general Quantum Approximation Optimization Algorithm (QAOA) applied to the MaxCut problem and consider Noisy Intermediate Scale Quantum (NISQ) hardware architectures, which was already tackled in some previous studies. Specifically, we consider the problem denoted QCCP-X (QCCP with crosstalk constraints) and explore the use of genetic algorithms to solve it. We performed an experimental study across a conventional set of instances showing that the proposed genetic algorithm, termed GAx , outperforms a previous approach.
引用
收藏
页码:88 / 97
页数:10
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