The idea that the search efficiency can be increased with the help of a number of autonomous agents is often relevant in many situations, which is known among biologists and roboticists as a stigmergy. This is due to the fact that, in any probability-based search problem, adding information provides values for conditional prpbabilities. We report new findings of speed-up and suppression effects occuring in the quantum search problem through the study of quantum walk on a graph with floating vertices. This effect is a completely counterintuitive phenomenon in comparison to the classical counterpert, and may faciliate new insight in the future information search mechanisms that were never been perceived in classical picture. In order to understand the first passage probability, we also propose a method via ancillary model to bridge the measurement of the time dependence of the total probability of the complementary part and the first passage probability of the original model. This is expected to provide new ideas for quantum simulation by means of qubit chips.
The idea that the search efficiency can be increased with the help of a number of autonomous agents is often relevant in many situations, which is known among biologists and roboticists as a stigmergy. This is due to the fact that, in any probability-based search problem, adding information provides values for conditional prpbabilities. We report new findings of speed-up and suppression effects occuring in the quantum search problem through the study of quantum walk on a graph with floating vertices. This effect is a completely counterintuitive phenomenon in comparison to the classical counterpert, and may faciliate new insight in the future information search mechanisms that were never been perceived in classical picture. In order to understand the first passage probability, we also propose a method via ancillary model to bridge the measurement of the time dependence of the total probability of the complementary part and the first passage probability of the original model. This is expected to provide new ideas for quantum simulation by means of qubit chips.
Searching efficiency, which biologists and roboticists are ever concerned about, has become important in physics and information science nowadays. In classical probability-based searching problems, as stigmergy, the increase in graph complexity will decrease the searching efficiency. Here we study the searching efficiency based on the first-passage probability and find a counterintuitive phenomenon in quantum walk on a graph with floating vertices. Connecting one vertex in the floating layer to that in the base layer will speed up the searching rapidity, but such a speed-up effect will be suppressed at once if one more vertex is connected to the already connected vertex in the floating layer. This is a counterintuitive phenomenon in comparison to its classical counterpart, where additional vertices at the side chain will retard the searching rapidity. We also propose an ancillary model that bridges the measurement of the probability and the first-passage probability, which is expected to provide new ideas for quantum simulation by means of qubit chips.
We investigate the behavior of coherence in scattering quantum walk search on complete graph under the condition that the total number of vertices of the graph is significantly larger than the marked number of vertices we are searching, N ≫ v. We find that the consumption of coherence represents the increase of the success probability for the searching, also it is related to the efficiency of the algorithm in oracle queries. If no coherence is consumed or an incoherent state is utilized, the algorithm will behave as the classical blind search, implying that coherence is responsible for the speed-up in this quantum algorithm over its classical counterpart. The effect of noises, in particular of photon loss and random phase shifts, on the performance of algorithm is studied. Two types of noise are considered because they arise in the optical network used for experimental realization of scattering quantum walk. It is found that photon loss will reduce the coherence and random phase shifts will hinder the interference between the edge states, both leading to lower success probability compared with the noise-free case. We then conclude that coherence plays an essential role and is responsible for the speed-up in this quantum algorithm.
n this paper, we consider the problem of searching a marked vertex in a graph based on quantum walks. A very large body of research exists on this issue, from both theoretical and experimental studies, yet the existing quantum walk-based search algorithms require knowing exactly how many marked vertices there are before starting the search process. In addition, even if the precise knowledge of the number of marked vertices is known, the success probability of these algorithms could shrink dramatically when the number of search steps is greater than the right one. For avoiding these defects, in this paper we present a new quantum walk-based search algorithm which need not know any prior information about the marked vertices, but still keeps a quadratic speedup over classical ones and ensures that the error is bounded by a tunable parameter ϵ. More specifically, for an N-vertex complete bipartite graph with marked vertices but without knowing the number of marked vertices, if the number of search steps h satisfies h≥ln(ϵ2)N, then the algorithm will output a marked vertex with probability at least $ 1-\epsilon$ for any given ϵ∈(0,1]. This feature leads to quantum search algorithms with stronger robustness and a wider scope of application.
In this thesis two quantum search algorithms on two different graphs, a hypercube and a d-dimensional square lattice, are analysed and some applications of the lattice search are discussed.\nThe approach in this thesis generalises a picture drawn by Shenvi, Kempe and Whaley, which was later adapted by Ambainis, Kempe and Rivosh. It defines a one parameter family of unitary operators U_λ with parameter λ. It will be shown that two eigenvalues of U_λ form an avoided crossing at the λ-value where U_λ is equal to the old search operator.\nThis generalised picture opens the way for a construction of two approximate eigen- vectors at the crossing and gives rise to a 2×2 model Hamiltonian that is used to approximate the operator U_λ near the crossing. The thus defined Hamiltonian can be used to calculate the leading order of search time and success probability for the search. To the best of my knowledge only the scaling of these quantities has been known.\nFor the algorithm searching the regular lattice, a generalisation of the model Hamiltonian for m target vertices is constructed. This algorithm can be used to send a signal from one vertex of the graph to a set of vertices. The signal is transmitted between these vertices exclusively and is localised only on the sender and the receiving vertices while the probability to measure the signal at one of the remaining vertices is significantly smaller.\nHowever, this effect can be used to introduce an additional sender to search settings and send a continuous signal to all target vertices where the signal will localise. This effect is an improvement compared to the original search algorithm as it does not need to know the number of target vertices.
Using numerical simulation, we measured the performance of several potential quantum algorithms, based on quantum random walks, to solve Boolean satisfiability (SAT) problems. We develop the fundamentals of quantum computing and the theory of classical algorithms to indicate how these algorithms could be implemented. We also discuss the development of quantum random walks and the principles that go into creating them, presenting existing work on search algorithms using coined discrete-time quantum random walks. Although our quantum algorithms do not solve SAT problems faster than may be done classically, as a step toward that objective, we present the first example of a quantum walk on a directed graph that has a significant increase in speed over the analogous classical walk.