We put forward an alternative quantum algorithm for finding ttamiltonian cycles in any N-vertex graph based on adiabatic quantum computing. With a yon Neumann measurement on the final state, one may determine whether ...We put forward an alternative quantum algorithm for finding ttamiltonian cycles in any N-vertex graph based on adiabatic quantum computing. With a yon Neumann measurement on the final state, one may determine whether there is a HamiRonian cycle in the graph and pick out a cycle if there is any. Although the proposed algorithm provides a quadratic speedup, it gives an alternative algorithm based on adiabatic quantum computation, which is of interest because of its inherent robustness.展开更多
We present two efficient quantum adiabatic algorithms for Bernstein–Vazirani problem and Simon’s problem.We show that the time complexities of the algorithms for Bernstein–Vazirani problem and Simon’s problem are ...We present two efficient quantum adiabatic algorithms for Bernstein–Vazirani problem and Simon’s problem.We show that the time complexities of the algorithms for Bernstein–Vazirani problem and Simon’s problem are O(1)and O(n),respectively,which are the same complexities as the corresponding algorithms in quantum circuit model.In these two algorithms,the adiabatic Hamiltonians are realized by unitary interpolation instead of standard linear interpolation.Comparing with the adiabatic algorithms using linear interpolation,the energy gaps of our algorithms keep constant.Therefore,the complexities are much easier to analyze using this method.展开更多
We present a quantum adiabatic algorithm for a set of quantum 2-satisfiability(Q2SAT)problem,which is a generalization of 2-satisfiability(2SAT)problem.For a Q2SAT problem,we construct the Hamiltonian which is similar...We present a quantum adiabatic algorithm for a set of quantum 2-satisfiability(Q2SAT)problem,which is a generalization of 2-satisfiability(2SAT)problem.For a Q2SAT problem,we construct the Hamiltonian which is similar to that of a Heisenberg chain.All the solutions of the given Q2SAT problem span the subspace of the degenerate ground states.The Hamiltonian is adiabatically evolved so that the system stays in the degenerate subspace.Our numerical results suggest that the time complexity of our algorithm is O(n^(3.9))for yielding non-trivial solutions for problems with the number of clauses m=dn(n-1)/2(d■0.1).We discuss the advantages of our algorithm over the known quantum and classical algorithms.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
文摘We put forward an alternative quantum algorithm for finding ttamiltonian cycles in any N-vertex graph based on adiabatic quantum computing. With a yon Neumann measurement on the final state, one may determine whether there is a HamiRonian cycle in the graph and pick out a cycle if there is any. Although the proposed algorithm provides a quadratic speedup, it gives an alternative algorithm based on adiabatic quantum computation, which is of interest because of its inherent robustness.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11504430,11805279,61501514,and 61502526)
文摘We present two efficient quantum adiabatic algorithms for Bernstein–Vazirani problem and Simon’s problem.We show that the time complexities of the algorithms for Bernstein–Vazirani problem and Simon’s problem are O(1)and O(n),respectively,which are the same complexities as the corresponding algorithms in quantum circuit model.In these two algorithms,the adiabatic Hamiltonians are realized by unitary interpolation instead of standard linear interpolation.Comparing with the adiabatic algorithms using linear interpolation,the energy gaps of our algorithms keep constant.Therefore,the complexities are much easier to analyze using this method.
基金Project supported by the National Key R&D Program of China(Grant Nos.2017YFA0303302 and 2018YFA0305602)the National Natural Science Foundation of China(Grant No.11921005)Shanghai Municipal Science and Technology Major Project,China(Grant No.2019SHZDZX01)。
文摘We present a quantum adiabatic algorithm for a set of quantum 2-satisfiability(Q2SAT)problem,which is a generalization of 2-satisfiability(2SAT)problem.For a Q2SAT problem,we construct the Hamiltonian which is similar to that of a Heisenberg chain.All the solutions of the given Q2SAT problem span the subspace of the degenerate ground states.The Hamiltonian is adiabatically evolved so that the system stays in the degenerate subspace.Our numerical results suggest that the time complexity of our algorithm is O(n^(3.9))for yielding non-trivial solutions for problems with the number of clauses m=dn(n-1)/2(d■0.1).We discuss the advantages of our algorithm over the known quantum and classical algorithms.
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.
