Artificial Intelligence in Quantum Computing and Quantum Information
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 5
Special Issue Editors
Interests: quantum AI; privacy preserving machine learning; distributed computing; quantum computation; quantum information; machine learning; quantum machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: data science; FinTech; AI agent design; blockchain
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in quantum computing have opened new opportunities for integrating artificial intelligence (AI) techniques with quantum information processing. Beyond early demonstrations of quantum speedups, there is growing recognition that AI can play a fundamental role in the design, optimization, control and interpretation of quantum systems, while quantum computing offers new computational paradigms for learning and decision-making. This Special Issue focuses on Artificial Intelligence in Quantum Computing and Quantum Information, spanning both fundamental methodologies and real-world applications.
We invite contributions that address theoretical foundations, algorithmic innovations and practical implementations of Quantum AI, including quantum machine learning, quantum reinforcement learning, variational quantum algorithms, hybrid classical–quantum architectures, symmetry in quantum neural architecture and learning-based quantum control. Particular emphasis is placed on AI-assisted quantum system design, architecture search, noise mitigation and adaptive experiment optimization.
In addition to methodological advances, this Special Issue explicitly welcomes scientific and commercial applications of Quantum AI, such as quantum-enabled optimization and learning for finance and logistics, quantum-enhanced sensing and metrology, materials discovery, chemistry and drug design, communication networks and decision-making systems. By bridging theory, applications and deployment perspectives, this Special Issue aims to highlight how Quantum AI can transition from laboratory demonstrations to scalable, impactful technologies.
Dr. Samuel Yen-Chi Chen
Dr. Yun-Cheng Tsai
Guest Editors
Manuscript Submission Information
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Keywords
- quantum artificial intelligence
- quantum machine learning
- quantum reinforcement learning
- variational quantum algorithms
- hybrid classical–quantum systems
- quantum neural networks
- quantum optimization and control
- quantum information processing
- scientific applications of quantum computing
- commercial and industrial quantum AI
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