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AIQxQIA 2023: AI for Quantum and Quantum for AI

The convergence of quantum computing and artificial intelligence (AI) has opened new possibilities where both fields mutually benefit from each other’s advancements and may open a vast and promising landscape for research. In particular, Quantum for Artificial Intelligence focuses on leveraging quantum computing techniques to enhance AI applications. Quantum machine learning, algorithms, and neural networks utilize the properties of quantum systems to tackle complex computational problems. Quantum data analysis, optimization, and pattern recognition offer promising avenues for unlocking the potential of quantum data processing in AI. On the other hand, Artificial Intelligence for Quantum explores the use of AI techniques to advance quantum research. AI-driven algorithms may help in quantum circuit compilation, quantum error correction, state reconstruction, and gate synthesis, thereby improving the reliability and efficiency of quantum computations. The present issue is mainly dedicated to the collection of the extended version of the best original results presented at the international Workshop on AI for Quantum and Quantum for AI (AIQxQIA 2023), organized as a satellite event of the 22nd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2023), on November, 7, 2023.

Topics include, but are not limited to:

Quantum machine learning algorithms

• Quantum data analysis and pattern recognition

• Quantum neural networks

• Quantum optimization algorithms

• Quantum natural language processing

• Quantum generative models

• Quantum reinforcement learning

• Quantum algorithm design for AI

• AI techniques for quantum error correction

• AI techniques for the compilation of quantum circuits

• Quantum simulation with AI

• Quantum control optimization using AI

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