Publication | Open Access
Adiabatic condition and the quantum hitting time of Markov chains
27
Citations
12
References
2010
Year
Quantum DynamicEngineeringComputational ComplexityAdiabatic ConditionQuantum ComputingAbstract ProblemQuantum Optimization AlgorithmQuantum Machine LearningQuantum Mechanical PropertyQuantum SimulationQuantum EntanglementQuantum MatterMarkov ChainQuantum SciencePhysicsAdiabatic Quantum AlgorithmQuantum AlgorithmQuantum InformationTheory Of ComputingGraph TheoryNatural SciencesMarkov KernelQuantum SystemQuantum ChaosQuantum Algorithms
We present an adiabatic quantum algorithm for the abstract problem of searching marked vertices in a graph, or spatial search. Given a random walk (or Markov chain) $P$ on a graph with a set of unknown marked vertices, one can define a related absorbing walk ${P}^{'}$ where outgoing transitions from marked vertices are replaced by self-loops. We build a Hamiltonian $H(s)$ from the interpolated Markov chain $P(s)=(1\ensuremath{-}s)P+{\mathit{sP}}^{'}$ and use it in an adiabatic quantum algorithm to drive an initial superposition over all vertices to a superposition over marked vertices. The adiabatic condition implies that, for any reversible Markov chain and any set of marked vertices, the running time of the adiabatic algorithm is given by the square root of the classical hitting time. This algorithm therefore demonstrates a novel connection between the adiabatic condition and the classical notion of hitting time of a random walk. It also significantly extends the scope of previous quantum algorithms for this problem, which could only obtain a full quadratic speedup for state-transitive reversible Markov chains with a unique marked vertex.
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