A unifying primary framework for quantum graph neural networks from quantum graph states

arXiv:2402.13001v1 Announce Type: cross
Abstract: 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 show that they can be used either as a parameterized quantum circuits to represent neural networks or as an underlying structure to construct graph neural …

abstract arxiv computers cs.lg framework gates graph graph neural network graph neural networks graphs network networks neural network neural networks paper quant-ph quantum quantum computers quantum gates show through type