Quantum Computing and AI: Perspectives on Advanced Automation in Science and Engineering
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Abstract (arXiv)
Recent advances in artificial intelligence (AI) and quantum computing are accelerating automation in scientific and engineering processes, fundamentally reshaping research methodologies. This perspective highlights parallels between scientific automation and established Computer-Aided Engineering (CAE) practices, introducing Quantum CAE as a framework that leverages quantum algorithms for simulation, optimization, and machine learning within engineering design. Practical implementations of Quantum CAE are illustrated through case studies for combinatorial optimization problems. Further discussions include advancements toward higher automation levels, highlighting the critical role of specialized AI agents proficient in quantum algorithm design. The integration of quantum computing with AI raises significant questions about the collaborative dynamics among human scientists and engineers, AI systems, and quantum computational resources, underscoring a transformative future for automated discovery and innovation.
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References · 10
- 2021Quantum advantage in learning from experimentscited by 188
- 2018A quantum-inspired classical algorithm for recommendation systemscited by 70
- 2018Bayesian Optimization of Combinatorial Structurescited by 64
- 2022Application of QUBO solver using black-box optimization to structural design for resonance avoidancecited by 17
- 2025Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolvercited by 7
- 2022Quantum-enhanced Markov chain Monte Carlocited by 6
- 2022Lossy compression of matrices by black-box optimisation of mixed integer nonlinear programmingcited by 6
- 2025Automating quantum feature map design via large language modelscited by 5
- 2025A black-box optimization method with polynomial-based kernels and quadratic-optimization annealingcited by 4
- 2022Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimizationcited by 1
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