Lackadaisical quantum walks on triangular and honeycomb 2D grids

07/24/2020
by   Nikolajs Nahimovs, et al.
0

In the typical model, a discrete-time coined quantum walk search has the same running time of O(√(N)logN) for 2D rectangular, triangular and honeycomb grids. It is known that for 2D rectangular grid the running time can be improved to O(√(N logN)) using several different techniques. One of such techniques is adding a self-loop of weight 4/N to each vertex (i.e. making the walk lackadaisical). In this paper we apply lackadaisical approach to quantum walk search on triangular and honeycomb 2D grids. We show that for both types of grids adding a self-loop of weight 6/N and 3/N for triangular and honeycomb grids, respectively, results in O(√(N logN)) running time.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/16/2018

Finding a marked node on any graph by continuous time quantum walk

We provide a new spatial search algorithm by continuous time quantum wal...
research
03/08/2019

Distance Preserving Grid Layouts

Distance preserving visualization techniques have emerged as one of the ...
research
08/20/2022

Solving systems of linear equations through zero forcing set and application to lights out

Let 𝔽 be any field, we consider solving Ax=b repeatedly for a matrix A∈𝔽...
research
03/27/2022

Multimarked Spatial Search by Continuous-Time Quantum Walk

The quantum-walk-based spatial search problem aims to find a marked vert...
research
12/07/2021

Spatial Search on Johnson Graphs by Discrete-Time Quantum Walk

The spatial search problem aims to find a marked vertex of a finite grap...
research
06/07/2022

Walking on Vertices and Edges by Continuous-Time Quantum Walk

The quantum walk dynamics obey the laws of quantum mechanics with an ext...
research
12/01/2021

First Steps of an Approach to the ARC Challenge based on Descriptive Grid Models and the Minimum Description Length Principle

The Abstraction and Reasoning Corpus (ARC) was recently introduced by Fr...

Please sign up or login with your details

Forgot password? Click here to reset