Quantum Computing and Optimization: A Comparative Analysis of Classical and Quantum
Algorithms

Kawino Charles K.

Faculty of Engineering Kampala International University Uganda
ABSTRACT
Quantum computing is an emerging field that integrates principles of quantum mechanics with computer
science, mathematics, and electrical engineering to address complex computational problems. This paper
explores the potential of quantum computing in the realm of mathematical optimization, where classical
algorithms have traditionally been employed. By examining both classical and quantum optimization
algorithms, such as Quantum Annealing and the Quantum Approximate Optimization Algorithm
(QAOA), we highlight the current advancements and challenges in achieving quantum speedup. Although
no general quantum algorithm provides a speedup for global optimization problems, certain classes
benefit from quantum approaches. This paper discusses the foundational principles, recent developments,
and comparative performance of classical and quantum optimization techniques, emphasizing the
transformative potential of quantum computing.
Keywords: Quantum Computing, Mathematical Optimization, Quantum Annealing, Quantum
Approximate Optimization Algorithm (QAOA), Classical Algorithms, Global Optimization, Variation
Algorithms, NISQ Computers

CITE AS: Kawino Charles K. (2024). Quantum Computing and Optimization: A Comparative
Analysis of Classical and Quantum Algorithms. RESEARCH INVENTION JOURNAL OF
ENGINEERING AND PHYSICAL SCIENCES 3(1):42-51