Quantum Computing - Fundamentals and Applications: Analyzing the fundamentals of quantum computing and exploring its potential applications in cryptography, optimization, and machine learning

Authors

  • Dr. Ekaterina Vybornova Professor of Artificial Intelligence, ITMO University, Russia Author

Keywords:

Quantum computing, qubits

Abstract

Quantum computing represents a revolutionary approach to computation, harnessing the principles of quantum mechanics to perform operations that are infeasible for classical computers. This paper provides a comprehensive overview of the fundamentals of quantum computing, including qubits, quantum gates, and quantum algorithms. It then explores the potential applications of quantum computing in cryptography, optimization, and machine learning. The paper discusses how quantum computing can significantly impact these fields by offering unprecedented computational power and efficiency. Furthermore, it highlights the current challenges and future prospects of quantum computing, emphasizing its transformative potential in various industries.

Downloads

Download data is not yet available.

References

Tatineni, Sumanth, and Anirudh Mustyala. "Advanced AI Techniques for Real-Time Anomaly Detection and Incident Response in DevOps Environments: Ensuring Robust Security and Compliance." Journal of Computational Intelligence and Robotics 2.1 (2022): 88-121.

Biswas, A., and W. Talukdar. “Robustness of Structured Data Extraction from In-Plane Rotated Documents Using Multi-Modal Large Language Models (LLM)”. Journal of Artificial Intelligence Research, vol. 4, no. 1, Mar. 2024, pp. 176-95, https://thesciencebrigade.com/JAIR/article/view/219.

Bojja, Giridhar Reddy, Jun Liu, and Loknath Sai Ambati. "Health Information systems capabilities and Hospital performance-An SEM analysis." AMCIS. 2021.

Vemoori, Vamsi. "Comparative Assessment of Technological Advancements in Autonomous Vehicles, Electric Vehicles, and Hybrid Vehicles vis-à-vis Manual Vehicles: A Multi-Criteria Analysis Considering Environmental Sustainability, Economic Feasibility, and Regulatory Frameworks." Journal of Artificial Intelligence Research 1.1 (2021): 66-98.

Jeyaraman, Jawaharbabu, and Muthukrishnan Muthusubramanian. "Data Engineering Evolution: Embracing Cloud Computing, Machine Learning, and AI Technologies." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 1.1 (2023): 85-89.

Shahane, Vishal. "Investigating the Efficacy of Machine Learning Models for Automated Failure Detection and Root Cause Analysis in Cloud Service Infrastructure." African Journal of Artificial Intelligence and Sustainable Development2.2 (2022): 26-51.

Devan, Munivel, Ravish Tillu, and Lavanya Shanmugam. "Personalized Financial Recommendations: Real-Time AI-ML Analytics in Wealth Management." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online)2.3 (2023): 547-559.

Abouelyazid, Mahmoud. "YOLOv4-based Deep Learning Approach for Personal Protective Equipment Detection." Journal of Sustainable Urban Futures 12.3 (2022): 1-12.

Prabhod, Kummaragunta Joel. "Leveraging Generative AI and Foundation Models for Personalized Healthcare: Predictive Analytics and Custom Treatment Plans Using Deep Learning Algorithms." Journal of AI in Healthcare and Medicine 4.1 (2024): 1-23.

Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.

Althati, Chandrashekar, Manish Tomar, and Lavanya Shanmugam. "Enhancing Data Integration and Management: The Role of AI and Machine Learning in Modern Data Platforms." Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023 2.1 (2024): 220-232

Downloads

Published

10-07-2024

How to Cite

[1]
Dr. Ekaterina Vybornova, “Quantum Computing - Fundamentals and Applications: Analyzing the fundamentals of quantum computing and exploring its potential applications in cryptography, optimization, and machine learning”, Australian Journal of Machine Learning Research & Applications, vol. 4, no. 1, pp. 260–267, Jul. 2024, Accessed: Dec. 23, 2024. [Online]. Available: https://sydneyacademics.com/index.php/ajmlra/article/view/73

Similar Articles

1-10 of 33

You may also start an advanced similarity search for this article.