Quantum Random Walk Simulation Using Dependent Random Walk

Date

2024-9-6

Author

Ceylan, Mert Kaşif

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Quantum computers have sparked significant interest in recent years due to their potential to revolutionize various fields. One area where quantum computing shows great promise is in the study of quantum walks, a quantum counterpart of the classical random walk algorithm that has been foundational in scientific research. While both quantum and classical random walks involve a "walker" moving through a space or graph, quantum walks differ fundamentally due to quantum principles such as superposition, leading to unique behaviors like linear spreading and localization. This thesis investigates the quantum walk simulation, with a particular focus on the Quantum-Walk-Replicating-Random-Walk (QWRW) model. Unlike traditional quantum walks, which sum over all possible paths with complex interference effects, the QWRW approach models the walk as a series of distinct, classical-like steps. This trajectory-based perspective offers a novel way to analyze the walker's position and movement, avoiding the complexities of quantum interference. The QWRW model is particularly valuable in understanding key phenomena of quantum walks, such as linear spreading and localization, by providing insights into the directional properties of quantum walkers. By defining transition probabilities in both space and time, the QWRW model offers a detailed framework for examining the spatial and temporal characteristics of quantum walks, enhancing our understanding of their behavior and potential applications. This study aims to bridge the gap between classical and quantum walks, contributing to the broader field of quantum computing and its practical implications.

Subject Keywords

Quantum Random Walk, Random Walk, Simulation, Quantum

URI

https://hdl.handle.net/11511/111351

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Graduate School of Natural and Applied Sciences, Thesis