Quantum-enhanced Optimization - Applications and Challenges: Analyzing applications and challenges of quantum-enhanced optimization algorithms for solving large-scale optimization problems in various domains
Keywords:
Quantum ComputingAbstract
Quantum computing represents a revolutionary approach to solving complex optimization problems that are intractable for classical computers. Quantum-enhanced optimization algorithms leverage quantum phenomena such as superposition and entanglement to explore solution spaces more efficiently, promising significant speedups over classical methods. This paper provides an overview of the applications and challenges of quantum-enhanced optimization algorithms across various domains. We discuss how these algorithms can be applied to tackle large-scale optimization problems in fields such as finance, logistics, machine learning, and materials science. Additionally, we explore the key challenges and limitations faced by quantum-enhanced optimization, including noise, error rates, and qubit connectivity. Understanding these applications and challenges is crucial for realizing the full potential of quantum computing in optimization.
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, and Jun Liu. "Impact of it investment on hospital performance: a longitudinal data analysis." (2020).
Vemoori, Vamsi. "Human-in-the-Loop Moral Decision-Making Frameworks for Situationally Aware Multi-Modal Autonomous Vehicle Networks: An Accessibility-Focused Approach." Journal of Computational Intelligence and Robotics 2.1 (2022): 54-87.
Tillu, Ravish, Muthukrishnan Muthusubramanian, and Vathsala Periyasamy. "Transforming regulatory reporting with AI/ML: strategies for compliance and efficiency." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.1 (2023): 145-157.
Bayani, Samir Vinayak, Ravish Tillu, and Jawaharbabu Jeyaraman. "Streamlining Compliance: Orchestrating Automated Checks for Cloud-based AI/ML Workflows." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 413-435.
Tomar, Manish, and Vathsala Periyasamy. "Leveraging advanced analytics for reference data analysis in finance." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.1 (2023): 128-136.
Abouelyazid, Mahmoud. "Comparative Evaluation of SORT, DeepSORT, and ByteTrack for Multiple Object Tracking in Highway Videos." International Journal of Sustainable Infrastructure for Cities and Societies 8.11 (2023): 42-52.
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.
Shahane, Vishal. "Security Considerations and Risk Mitigation Strategies in Multi-Tenant Serverless Computing Environments." Internet of Things and Edge Computing Journal 1.2 (2021): 11-28.
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.
