AN INTRODUCTION TO QUANTUM COMPUTING ALGORITHMS

Authors

  • Mr. Gajendra K. Shirsale Research Scholar, Management G. H. Raisoni Institute of Business Management, Jalgaon. Maharashtra
  • Dr. Deepak S. Sharma Research Guide, & Deputy Director, Datta Meghe Institute of Higher Education and Research Deemed to be University, Sawangi, Wardha
  • Dr. Yogita D. Patil Research Co-Guide, Asst. Professor, Management G. H. Raisoni Institute of Business Management, Jalgaon. Maharashtra

Keywords:

Quantum Computing, Quantum Computing Algorithm

Abstract

With the increasing accessibility of quantum computers to the wider population, there is a growing demand for the education and training of a group of quantum programmers. This cohort predominantly consists of individuals who have primarily focused on the development of classical computer programs throughout their professional careers. Although existing quantum computers currently possess fewer than 100 qubits, it is widely anticipated that the quantum computing hardware will experience significant advancements in terms of qubit quantity, quality, and connectivity. The objective of this review is to elucidate the fundamental principles of quantum programming, which diverge significantly from classical programming. This will be achieved through the utilization of concise algebraic expressions, allowing for an optional comprehension of the captivating underlying principles of quantum mechanics. This paper provides an overview of quantum computing algorithms and their practical implementation on physical quantum hardware. In this study, we undertake a comprehensive examination of various quantum algorithms, with the objective of providing concise and self-contained descriptions for each. In this study, we demonstrate the practical implementation of the aforementioned algorithms on IBM's quantum computer. For each algorithm, we thoroughly analyze and compare the outcomes obtained from the implementation on the quantum computer with those obtained from the simulator. This analysis focuses on identifying and discussing any disparities that arise between the results obtained from the simulator and the actual hardware runs. This article serves as an introduction to quantum algorithms for computer scientists, physicists, and engineers, offering a comprehensive guide for their practical implementation. 

Downloads

Download data is not yet available.

References

J., A., Adedoyin, A., Ambrosiano, J., Anisimov, P., Casper, W., Chennupati, G., Coffrin, C., Djidjev, H., Gunter, D., Karra, S., Lemons, N., Lin, S., Malyzhenkov, A., Mascarenas, D., Mniszewski, S., Nadiga, B., O’Malley, D., Oyen, D., Pakin, S., . . . Lokhov, A. Y. (2018, April 10). Quantum Algorithm Implementations for Beginners. arXiv.org. https://doi.org/10.1145/3517340

Quantum Machine Learning and Optimisation in Finance. (2022, October 1). O’Reilly Online Learning. https://www.oreilly.com/library/view/quantum-machine

learning/9781801813570/

Applied Quantum Computers. BPB. Dr. Patanjali Kashyap. (2023, January 27). ISBN: 9789355510105

Umer, M. J., & Sharif, M. I. (n.d.). A Comprehensive Survey on Quantum Machine

Learning and Possible Applications. A Comprehensive Survey on Quantum Machine Learning and Possible Applications: Medicine & Healthcare Journal Article | IGI Global. https://doi.org/10.4018/IJEHMC.315730

Downloads

Published

08-03-2024

How to Cite

[1]
Mr. Gajendra K. Shirsale, Dr. Deepak S. Sharma, and Dr. Yogita D. Patil, “AN INTRODUCTION TO QUANTUM COMPUTING ALGORITHMS”, IEJRD - International Multidisciplinary Journal, vol. 9, no. GHRIEBM, p. 6, Mar. 2024.