Optimization on Large Interconnected Graphs and Networks Using Adiabatic Quantum Computation

Fuente: arXiv
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Autores principales: Padmasola, Venkat, Chatterjee, Rupak
Formato: Preprint
Publicado: 2022
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author Padmasola, Venkat
Chatterjee, Rupak
author_facet Padmasola, Venkat
Chatterjee, Rupak
contents In this paper, we demonstrate that it is possible to create an adiabatic quantum computing algorithm that solves the shortest path between any two vertices on an undirected graph with at most 3V qubits, where V is the number of vertices of the graph. We do so without relying on any classical algorithms, aside from creating a (V x V) adjacency matrix. The objective of this paper is to demonstrate the fact that it is possible to model large graphs on an adiabatic quantum computer using the maximum number of qubits available and random graph generators such as the Barabasi-Albert and the Erdos-Renyi methods which can scale based on a power law.
format Preprint
id arxiv_https___arxiv_org_abs_2202_02774
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Optimization on Large Interconnected Graphs and Networks Using Adiabatic Quantum Computation
Padmasola, Venkat
Chatterjee, Rupak
Quantum Physics
In this paper, we demonstrate that it is possible to create an adiabatic quantum computing algorithm that solves the shortest path between any two vertices on an undirected graph with at most 3V qubits, where V is the number of vertices of the graph. We do so without relying on any classical algorithms, aside from creating a (V x V) adjacency matrix. The objective of this paper is to demonstrate the fact that it is possible to model large graphs on an adiabatic quantum computer using the maximum number of qubits available and random graph generators such as the Barabasi-Albert and the Erdos-Renyi methods which can scale based on a power law.
title Optimization on Large Interconnected Graphs and Networks Using Adiabatic Quantum Computation
topic Quantum Physics
url https://arxiv.org/abs/2202.02774