2018
DOI: 10.1088/1367-2630/aad899
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Controlling quantum random walk with a step-dependent coin

Abstract: We report on the possibility of controlling quantum random walks (QWs) with a step-dependent coin (SDC). The coin is characterized by a (single) rotation angle. Considering different rotation angles, one can find diverse probability distributions for this walk including: complete localization, Gaussian and asymmetric likes. In addition, we explore the entropy of walk in two contexts; for probability density distributions over position space and walkerʼs internal degrees of freedom space (coin space). We show t… Show more

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Cited by 38 publications
(34 citation statements)
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References 75 publications
(133 reference statements)
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“…Initially, a space-dependent coin was introduced in the quantum walk 20 . Later, a quantum walk with time-dependent coins was studied [21][22][23][24][25] . The resulting probability distribution for the quantum walk changed significantly.…”
Section: Floquet-engineered Quantum Walksmentioning
confidence: 99%
“…Initially, a space-dependent coin was introduced in the quantum walk 20 . Later, a quantum walk with time-dependent coins was studied [21][22][23][24][25] . The resulting probability distribution for the quantum walk changed significantly.…”
Section: Floquet-engineered Quantum Walksmentioning
confidence: 99%
“…In previous study [33], we confirmed that by utilizing step-dependent coins [34] in splitstep quantum walk, we can simulate exotic cell-like structure for topological phenomena [33]. In this paper, we mainly focus on these cell-like structures and address the following issues.…”
mentioning
confidence: 79%
“…However, when either of these conditions are violated, a naive classical MCMC fails to produce the correct probability distribution over final states. While quantum walks with time/space dependence have been studied in the literature [4,[7][8][9][10] and there are some similarities to quantum algorithms for decision trees [11], our quantum tree requires a new approach.…”
Section: Introductionmentioning
confidence: 99%