MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence
Over the past decade, Artificial Intelligence (AI) has provided enormous new possibilities and opportunities, but also new demands and requirements for software systems. In particular, Machine Learning (ML) has proven useful in almost every vertical application domain. In the decade ahead, an unprecedented paradigm shift from classical computing towards Quantum Computing (QC), with perhaps a quantum-classical hybrid model, is expected. We argue that the Model-Driven Engineering (MDE) paradigm can be an enabler and a facilitator, when it comes to the quantum and the quantum-classical hybrid applications. This includes not only automated code generation, but also automated model checking and verification, as well as model analysis in the early design phases, and model-to-model transformations both at the design-time and at the runtime. In this paper, the vision is focused on MDE for Quantum AI, particularly Quantum ML for the Internet of Things (IoT) and smart Cyber-Physical Systems (CPS) applications.
Code (0)
등록된 구현이 없습니다.
Tasks
Code GenerationSimilar Papers 제목 키워드 기반
Quantum computing and artificial intelligence: status and perspectives
This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could support the development of innovative AI sol…
Quantum Computing and AI: Perspectives on Advanced Automation in Science and Engineering
Recent advances in artificial intelligence (AI) and quantum computing are accelerating automation in scientific and engineering processes, fundamentally reshaping research methodologies. This perspective highlights paral…
Combinatorial OptimizationEvaluating Verified Autonomy in Quantum Engineering
Reliable quantum engineering is essential for turning quantum phenomena into practical technologies. As quantum platforms grow in scale and complexity, their characterization and operation require increasing human effort…
Quantum Artificial Intelligence for Mission-Critical Systems: Foundations, Architectural Elements, and Future Directions
Mission critical (MC) applications such as defense operations, energy management, cybersecurity, and aerospace control require reliable, deterministic, and low-latency decision making under uncertainty. Although the clas…
Quantum Machine LearningDecision MakingArtificial intelligence for artificial materials: moiré atom
Moir\'e engineering in atomically thin van der Waals heterostructures creates artificial quantum materials with designer properties. We solve the many-body problem of interacting electrons confined to a moir\'e superlatt…