Quantum Information Processing - Hardware Technologies: Exploring hardware technologies for quantum information processing, including superconducting qubits, trapped ions, and photonic quantum devices
Keywords:
Quantum information processing, hardware technologies, superconducting qubitsAbstract
Quantum information processing (QIP) is a rapidly evolving field that promises to revolutionize computation, communication, and simulation. Hardware technologies play a crucial role in realizing these quantum systems. This paper provides an overview of the current state of hardware technologies for QIP, focusing on superconducting qubits, trapped ions, and photonic quantum devices. We discuss the principles behind these technologies, their current capabilities, and the challenges they face. Additionally, we highlight recent advances and future prospects, emphasizing the potential for scalability and fault tolerance. Understanding these hardware technologies is essential for the development of practical quantum computers and other quantum-enabled devices.
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References
Tatineni, Sumanth, and Anirudh Mustyala. "AI-Powered Automation in DevOps for Intelligent Release Management: Techniques for Reducing Deployment Failures and Improving Software Quality." Advances in Deep Learning Techniques 1.1 (2021): 74-110.
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.
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. "Towards Real-Time Automated Failure Detection and Self-Healing Mechanisms in Cloud Environments: A Comparative Analysis of Existing Systems." Journal of Artificial Intelligence Research and Applications 4.1 (2024): 136-158.
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. "Natural Language Processing for Automated Customer Support in E-Commerce: Advanced Techniques for Intent Recognition and Response Generation." Journal of AI-Assisted Scientific Discovery 2.1 (2022): 195-232.
Prabhod, Kummaragunta Joel. "Utilizing Foundation Models and Reinforcement Learning for Intelligent Robotics: Enhancing Autonomous Task Performance in Dynamic Environments." Journal of Artificial Intelligence Research 2.2 (2022): 1-20.
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.
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