Quantum Entanglement - Generation and Applications: Exploring methods for generating and characterizing quantum entanglement and investigating its applications in quantum communication and computing
Keywords:
Quantum entanglement, Generation, CharacterizationAbstract
Quantum entanglement is a phenomenon in quantum mechanics where two or more particles become correlated in such a way that the quantum state of each particle cannot be described independently of the others, even when separated by large distances. This paper provides a comprehensive overview of the generation, characterization, and applications of quantum entanglement. We first discuss various methods for generating entanglement, including spontaneous parametric down-conversion, quantum dots, and ion traps. We then explore techniques for characterizing entanglement, such as Bell tests and quantum state tomography. Finally, we investigate the applications of entanglement in quantum communication, including quantum teleportation and quantum key distribution, as well as in quantum computing, such as quantum gates and quantum algorithms. Through this paper, we aim to provide a thorough understanding of quantum entanglement and its significance in modern quantum technologies.
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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.
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