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Quantum Random Walk via Classical Random Walk With Internal States

Robert Main Burton, Yevgeniy Kovchegov, Thinh P. Nguyen

Published Apr 26, 2010• 3 citations
OpenAlex

Abstract

In recent years quantum random walks have garnered much interest among quantum information researchers. Part of the reason is the prospect that many hard problems can be solved efficiently by employing algorithms based on quantum random walks, in the same way that classical random walks have played a central role in many hugely successful randomized algorithms. In this paper we introduce a new representation for the quantum random walks via the classical random walk with internal states. This new representation allows for a systematic approach to finding closed form expressions for the n-step distributions for a variety of quantum random walk models, and lends itself naturally to large deviation analysis. As an example, we show how to use the new representation to arrive at the same closed form expression for the Hadamard quantum random walk on a line, previously obtained by others. We assert the proposed method works in the most general settings.

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In recent years quantum random walks have garnered much interest among quantum information researchers. Part of the reason is the prospect that many hard problems can be solved efficiently by employing algorithms based on quantum random walks, in the same way that classical random walks have played a central role in many hugely successful randomized algorithms. In this paper we introduce a new representation for the quantum random walks via the classical random walk with internal states. This new representation allows for a systematic approach to finding closed form expressions for the n-step distributions for a variety of quantum random walk models, and lends itself naturally to large deviation analysis. As an example, we show how to use the new representation to arrive at the same closed form expression for the Hadamard quantum random walk on a line, previously obtained by others. We assert the proposed method works in the most general settings.
In this paper we address the quantum random walk on the real line. Specifically, we utilize a dynamical system formulation of the walk, which leads to a momentum space expression of the probability amplitude that is a function of only the initial condition. Our focus is, for the most part, limited to the Hadamard walk. As such, this closed form expression is not as general as that given by [1]. This lack of generality is offset by the ease with which we obtain the expression, and the insight offered by it. Our closed form expression allows us to easily compute the walk pdf, hence the cdf (cumulative distribution function). It is shown that the cdf converges to its limiting form relatively quickly. We push the simple mathematics in an to attempt to obtain a closed form expression for this form. But it becomes too involved to take it to completion in this paper, without running the risk of losing appreciation for the simplicity of our approach.
Motivated by the immense success of random walk and Markov chain methods in the design of classical algorithms, we consider_quantum_ walks on graphs. We analyse in detail the behaviour of unbiased quantum walk on the line, with the example of a typical walk, the ``Hadamard walk''. We show that after t time steps, the probability distribution on the line induced by the Hadamard walk is almost uniformly distributed over the interval [-t/sqrt(2),t/sqrt(2)]. This implies that the same walk defined on the circle mixes in_linear_ time. This is in direct contrast with the quadratic mixing time for the corresponding classical walk. We conclude by indicating how our techniques may be applied to more general graphs.
Motivated by the immense success of random walk and Markov chain methods in the design of classical algorithms, we consider {\em quantum\/} walks on graphs. We analyse in detail the behaviour of unbiased quantum walk on the line, with the example of a typical walk, the ``Hadamard walk''''. In particular, we show that after~ttt time steps, the probability distribution on the line induced by the Hadamard walk is almost uniformly distributed over the interval~[−t/2,  t/2][-t/\sqrt{2},\;t/\sqrt{2}][−t/2​,t/2​]. This implies that the same walk defined on the circle mixes in {\em linear\/} time. This is in direct contrast with the quadratic mixing time for the corresponding classical walk. We conclude by indicating how our techniques may be applied to more general graphs.
In this paper, a study on discrete-time coined quantum walks on the line is presented. Clear mathematical foundations are still lacking for this quantum walk model. As a step toward this objective, the following question is being addressed: Given a graph, what is the probability that a quantum walk arrives at a given vertex after some number of steps? This is a very natural question, and for random walks it can be answered by several different combinatorial arguments. For quantum walks this is a highly non-trivial task. Furthermore, this was only achieved before for one specific coin operator (Hadamard operator) for walks on the line. Even considering only walks on lines, generalizing these computations to a general SU(2) coin operator is a complex task. The main contribution is a closed-form formula for the amplitudes of the state of the walk (which includes the question above) for a general symmetric SU(2) operator for walks on the line. To this end, a coin operator with parameters that alters the phase of the state of the walk is defined. Then, closed-form solutions are computed by means of Fourier analysis and asymptotic approximation methods. We also present some basic properties of the walk which can be deducted using weak convergence theorems for quantum walks. In particular, the support of the induced probability distribution of the walk is calculated. Then, it is shown how changing the parameters in the coin operator affects the resulting probability distribution.
This article aims to provide an introductory survey on quantum random walks. Starting from a physical effect to illustrate the main ideas we will introduce quantum random walks, review some of their properties and outline their striking differences to classical walks. We will touch upon both physical effects and computer science applications, introducing some of the main concepts and language of present day quantum information science in this context. We will mention recent developments in this new area and outline some open questions. 1. Overview Ever since the discovery of quantum mechanics people have been puzzled by the counter-intuitive character of the laws of nature. Over time we have learned to accept more and more effects that are unimaginable in a classical Newtonian world. Modern technology exploits quantum effects both to our benefit and detriment—among the memorable examples we should cite laser technology and not omit the atomic bomb. In recent years interest in quantum information theory has been generated by the prospect of employing its laws to design devices of surprising power [1]. New ideas include quantum cryptography [2, 3] and quantum computation. In 1994 Shor [4] discovered a quantum algorithm to factor numbers efficiently (that is in time that grows only polynomically with the length of the number to be factored). This has unleashed a wave of activity across a broad range of disciplines: physics, computer science, mathematics and engineering. This fruitful axis of research has uncovered many new effects that are strikingly different from their classical counterparts, both from the physical point of view as well as from a computer science and communication theory perspective. Over time these communities have gained a greater understanding of the concepts and notions of the other. The idea that information cannot be separated from
Quantum walks are a powerful tool for developing efficient algorithms in quantum computing. This research explores two discrete-time one-dimensional quantum walks where the coin operator varies along even and odd positions on the line. We find closed-form expressions for the coefficients of the wave function for both walks and also arrive at a formula for the probability distribution for one of the walks. A significant discovery is a way to model the well-known Hadamard walk using two alternating coins.