Quantum Gate Network Based on Adiabatic Theorem

Quantum neural network (QNN) is a young and outlying science built upon the combination of classical neural network and quantum computing. Making use of quantum gate, this paper presents time-dependent quantum gate network based on the adiabatic theorem, which has the initial quantum state that is the eigenstate of time-dependent Hamiltonian operator. Then Hamiltonian evolve in time and the eigenstate corresponding to the Hamiltonian is the target state of the network after the time T. Seeing from the macroscopy, this quantum target state can be considered to evolve from the initial state. Therefore, the proposed network is very different from the general quantum gate network that utilizes unitary operator to evolve quantum state. In addition, this paper validates the feasibility and validity of this network by constructing time-dependent NOT-gate and XOR-gate network.