Focus and Scope
One of the rapidly advancing frontiers in contemporary science and technology is the convergence of quantum computing and artificial intelligence. Quantum computing introduces fundamentally new computational paradigms based on the principles of quantum mechanics, while artificial intelligence continues to revolutionize intelligent learning, reasoning, optimization, and autonomous decision-making across scientific, industrial, and societal domains. The integration of these technologies has created the emerging field of Quantum Artificial Intelligence (Quantum AI), offering unprecedented opportunities to solve computationally intensive problems beyond the capabilities of classical computing. However, challenges related to quantum hardware limitations, algorithm design, scalability, explainability, security, and practical deployment remain significant. Advancing rigorous, reproducible, and application-oriented research in these domains is therefore essential to accelerate the development of next-generation intelligent systems and quantum-enabled technologies.
The journal is a forum for the exchange of research findings, analysis, information, and knowledge in areas that include, but are not limited to:
Quantum Computing Models and Algorithms for Artificial Intelligence – The journal encourages research on quantum computing architectures, quantum algorithms, variational quantum algorithms, quantum optimization, quantum circuit design, quantum programming, quantum simulation, and computational models that improve the performance and efficiency of artificial intelligence systems.
Quantum Machine Learning and Intelligent Computing – The journal promotes research on quantum-enhanced machine learning, hybrid quantum-classical systems, quantum neural networks, quantum deep learning, reinforcement learning, generative AI, pattern recognition, intelligent data analytics, predictive modeling, and scalable learning frameworks that leverage quantum computing capabilities.
Explainable, Trustworthy, and Responsible Quantum Artificial Intelligence – The journal encourages research on explainability, interpretability, transparency, fairness, robustness, reliability, and ethical aspects of Quantum AI systems. Topics include explainable quantum machine learning, trustworthy intelligent systems, uncertainty estimation, model validation, bias mitigation, and responsible deployment of quantum-enabled artificial intelligence.
Quantum Security, Cryptography, and Information Theory – The journal supports research on secure quantum-enabled intelligent systems, including quantum cryptography, quantum key distribution, post-quantum cryptography, quantum communication, information theory, privacy-preserving computation, authentication, cybersecurity, and secure data processing in intelligent environments.
Quantum-Enhanced Optimization, Decision Support, and Simulation – The journal encourages research on quantum optimization methods, computational intelligence, decision support systems, combinatorial optimization, scheduling, resource allocation, simulation frameworks, digital twins, and quantum-assisted analytical models for solving complex real-world problems.
Quantum Computing Infrastructure and Software Systems – The journal welcomes research on quantum software engineering, quantum programming languages, compiler optimization, cloud-based quantum computing, distributed quantum systems, noisy intermediate-scale quantum (NISQ) computing, benchmarking, performance evaluation, and software frameworks that support Quantum AI applications.
Applications of Quantum Artificial Intelligence – The journal supports research on the practical implementation of Quantum AI across diverse application domains, including healthcare, drug discovery, finance, cybersecurity, smart manufacturing, robotics, autonomous systems, transportation, energy, climate science, smart cities, Internet of Things (IoT), scientific computing, and other emerging intelligent systems powered by quantum technologies.