WELCOME TO AIQxQIA

International Workshop on AI for Quantum and Quantum for AI

The convergence of quantum computing and artificial intelligence (AI) has opened up new possibilities for advancing both fields. This workshop aims at exploring the intersection of quantum computing and AI, encompassing two perspectives: quantum for artificial intelligence and artificial intelligence for
quantum.

“Quantum for Artificial Intelligence” focuses on leveraging quantum computing techniques to enhance AI applications. Quantum machine learning, algorithms, and neural networks utilize the unique 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. Additionally, quantum-inspired generative models and natural language processing also open new avenues for quantum-based AI advancements.

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. AI-based optimization and simulation techniques contribute to quantum algorithm design, resource estimation, and system identification.

The synergy between quantum computing and AI represents a frontier where both fields mutually benefit from each other’s advancements, and may open up a vast and promising landscape for research, paving the way for transformative developments in both realms.

Workshop Objectives

1. Foster Interdisciplinary Discussions: the workshop will serve as a platform for interdisciplinary discussions, bridging the gap between quantum computing and AI. Participants from diverse backgrounds, including computer science, physics, mathematics, and engineering, will exchange ideas and insights to explore novel approaches, methodologies, and applications at the intersection of these fields.

2. Share State-of-the-Art Research: researchers and practitioners in the field will present their latest research findings, highlighting recent breakthroughs and advancements in quantum and AI. Participants will gain insights into state-of-the-art techniques, methodologies, and applications through both a keynote talk and technical presentations.

3. Discuss Challenges and Opportunities: the workshop will facilitate in-depth discussions on the challenges and opportunities posed by the integration of quantum computing and AI. Participants will identify key research gaps, technical hurdles, and ethical considerations. A final panel discussion will foster a holistic understanding of the potential societal impact, limitations, and future directions of quantum and AI.

4. Foster Collaboration and Networking: the workshop will provide ample networking opportunities for participants to interact, forge new connections, and initiate collaborations. Researchers and practitioners from academia, industry, and government institutions will have the chance to discuss shared interests, exchange ideas, and explore potential partnerships.

Topics

Topics include, but are not limited to, the following:

• 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