Quantum Algorithms - Design and Analysis: Investigating the design and analysis of quantum algorithms for solving computational problems with quantum speedup, including Shor's and Grover's algorithms
Keywords:
Quantum computingAbstract
Quantum computing represents a paradigm shift in computation, promising exponential speedup for certain problems over classical computers. Quantum algorithms play a pivotal role in harnessing this potential, with designs and analyses tailored to exploit quantum phenomena. This paper provides a comprehensive review of quantum algorithms, focusing on the design principles and analytical frameworks that underpin their efficiency. We delve into two seminal algorithms, Shor's and Grover's, illustrating their quantum advantage and exploring the theoretical and practical aspects of their implementation. Through this exploration, we aim to elucidate the intricate interplay between quantum mechanics and computer science, highlighting the transformative potential of quantum algorithms in addressing complex computational challenges.
Downloads
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. "Evolutionary Landscape of Battery Technology and its Impact on Smart Traffic Management Systems for Electric Vehicles in Urban Environments: A Critical Analysis." Advances in Deep Learning Techniques 1.1 (2021): 23-57.
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. "Serverless Computing in Cloud Environments: Architectural Patterns, Performance Optimization Strategies, and Deployment Best Practices." Journal of AI-Assisted Scientific Discovery 2.1 (2022): 23-43.
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.
Sharma, Kapil Kumar, Manish Tomar, and Anish Tadimarri. "Optimizing sales funnel efficiency: Deep learning techniques for lead scoring." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 261-274.
Abouelyazid, Mahmoud. "Adversarial Deep Reinforcement Learning to Mitigate Sensor and Communication Attacks for Secure Swarm Robotics." Journal of Intelligent Connectivity and Emerging Technologies 8.3 (2023): 94-112.
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 Jesu Narkarunai Arasu Malaiyappan. "Scalable Machine Learning Solutions for Heterogeneous Data in Distributed Data Platform." Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023 4.1 (2024): 299-309.