A unifying primary framework for QGNNs from quantum graph states

被引:0
|
作者
Daskin, Ammar [1 ]
机构
[1] Istanbul Medeniyet Univ, Dept Comp Engn, TR-34700 Istanbul, Turkiye
来源
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS | 2024年
关键词
D O I
10.1140/epjs/s11734-024-01382-1
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Graph states are used to represent mathematical graphs as quantum states on quantum computers. They can be formulated through stabilizer codes, or directly quantum gates and quantum states. In this paper, we show that a quantum graph neural network model can be understood and realized based on graph states. We then show that the graph states can be used either as a parametrized quantum circuits to represent neural networks or as an underlying structure to construct graph neural networks on quantum computers.
引用
收藏
页数:10
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