Solving the Independent Domination Problem by Quantum Approximate Optimization Algorithm

TL;DR

This paper presents a quantum algorithm based on QAOA to solve the Independent Domination Problem, demonstrating potential advantages over classical methods in terms of computational complexity.

Contribution

It introduces a QAOA-based approach for IDP, showcasing its effectiveness using IBM's simulator and highlighting its potential to outperform classical algorithms.

Findings

QAOA can solve IDP with specific parameters.

Quantum approach shows lower computational complexity.

Demonstrated on IBM's qasm_simulator.

Abstract

In the wake of quantum computing advancements and quantum algorithmic progress, quantum algorithms are increasingly being employed to address a myriad of combinatorial optimization problems. Among these, the Independent Domination Problem (IDP), a derivative of the Domination Problem, has practical implications in various real-world scenarios. Despite this, existing classical algorithms for IDP are plagued by high computational complexity, and quantum algorithms have yet to tackle this challenge. This paper introduces a Quantum Approximate Optimization Algorithm (QAOA)-based approach to address the IDP. Utilizing IBM's qasm_simulator, we have demonstrated the efficacy of QAOA in solving IDP under specific parameter settings, with a computational complexity that surpasses that of classical methods. Our findings offer a novel avenue for the resolution of IDP.