In our recent work we showed, by investigating the initialization of some unusual forms of assisted driving Hamiltonians, that the addition of an assisted driving Hamiltonian is not always useful in quantum adiabatic ...In our recent work we showed, by investigating the initialization of some unusual forms of assisted driving Hamiltonians, that the addition of an assisted driving Hamiltonian is not always useful in quantum adiabatic evolution. These unusual forms are those that are not the relatively fixed ones that are widely used in the literature. In this paper, we continue this study, providing further evidence for the validity of the conclusion above by researching some relatively more complex forms of assisted driving scheme, which generalize the ones studied in our previous work.展开更多
Quantum pattern recognition algorithm for two-qubit systems has been implemented by quantum adiabatic evolution. We will estimate required running time for this algorithm by means of an analytical solution of time- de...Quantum pattern recognition algorithm for two-qubit systems has been implemented by quantum adiabatic evolution. We will estimate required running time for this algorithm by means of an analytical solution of time- dependent Hamiltonian since the time complexity of adiabatic quantum evolution is a limitation on the quantum computing. These results can be useful for experimental implementation.展开更多
In this paper, we study a kind of nonlinear model of adiabatic evolution in quantum search problem. As will be seen here, for this problem, there always exists a possibility that this nonlinear model can successfully ...In this paper, we study a kind of nonlinear model of adiabatic evolution in quantum search problem. As will be seen here, for this problem, there always exists a possibility that this nonlinear model can successfully solve the problem, while the linear model can not. Also in the same setting, when the overlap between the initial state and the final stare is sufficiently large, a simple linear adiabatic evolution can achieve O(1) time efficiency, but infinite time complexity for the nonlinear model of adiabatic evolution is needed. This tells us, it is not always a wise choice to use nonlinear interpolations in adiabatic algorithms. Sometimes, simple linear adiabatic evolutions may be sufficient for using.展开更多
基金Project supported by the China Postdoctoral Science Foundation(Grant No.2017M620322)the National Natural Science Foundation of China(Grant No.61402188)+1 种基金Priority for the Postdoctoral Scientific and Technological Program of Hubei Province,China in 2017the Science and Technology Program of Shenzhen of China(Grant Nos.JCYJ 20170818160208570 and JCYJ 20170307160458368)
文摘In our recent work we showed, by investigating the initialization of some unusual forms of assisted driving Hamiltonians, that the addition of an assisted driving Hamiltonian is not always useful in quantum adiabatic evolution. These unusual forms are those that are not the relatively fixed ones that are widely used in the literature. In this paper, we continue this study, providing further evidence for the validity of the conclusion above by researching some relatively more complex forms of assisted driving scheme, which generalize the ones studied in our previous work.
文摘Quantum pattern recognition algorithm for two-qubit systems has been implemented by quantum adiabatic evolution. We will estimate required running time for this algorithm by means of an analytical solution of time- dependent Hamiltonian since the time complexity of adiabatic quantum evolution is a limitation on the quantum computing. These results can be useful for experimental implementation.
基金Supported by the National Natural Science Foundation of China under Grant Nos.61402188 and 61173050the support from the China Postdoctoral Science Foundation under Grant No.2014M552041
文摘In this paper, we study a kind of nonlinear model of adiabatic evolution in quantum search problem. As will be seen here, for this problem, there always exists a possibility that this nonlinear model can successfully solve the problem, while the linear model can not. Also in the same setting, when the overlap between the initial state and the final stare is sufficiently large, a simple linear adiabatic evolution can achieve O(1) time efficiency, but infinite time complexity for the nonlinear model of adiabatic evolution is needed. This tells us, it is not always a wise choice to use nonlinear interpolations in adiabatic algorithms. Sometimes, simple linear adiabatic evolutions may be sufficient for using.
