Quantum Neural Networks - Quantum Computing: Studying quantum neural networks and their potential applications in leveraging quantum computing advantages for AI tasks
Keywords:
Quantum Neural Networks, Quantum Computing, Artificial IntelligenceAbstract
Quantum computing holds the promise of revolutionizing various fields, including artificial intelligence (AI), by offering unprecedented computational power. Quantum neural networks (QNNs) emerge at the intersection of quantum computing and neural networks, aiming to harness the advantages of quantum computation for AI tasks. This paper provides a comprehensive overview of QNNs, exploring their architecture, training methods, and potential applications. We discuss the principles of quantum computing relevant to QNNs, such as superposition, entanglement, and quantum gates. Moreover, we review the current state of research on QNNs, highlighting key developments and challenges. Finally, we discuss potential applications of QNNs in AI, including quantum-enhanced machine learning algorithms, quantum pattern recognition, and quantum optimization. Through this paper, we aim to provide a thorough understanding of QNNs and their role in leveraging quantum computing advantages for AI tasks.
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