On May 15, 2025, Dr. Tadashi Kadowaki published a preprint titled "Quantum Computing and AI: Perspectives on Advanced Automation in Science and Engineering" on arXiv. In this paper, he introduces "Quantum Computer-Aided Engineering" (Quantum CAE), a framework that integrates quantum computing and artificial intelligence (AI) to enhance automation in scientific and engineering processes.

Dr. Kadowaki's work explores how Quantum CAE can improve simulation, optimization, and machine learning within engineering design, potentially transforming industries by enabling more efficient and scalable solutions to complex problems. He emphasizes the role of specialized AI agents proficient in quantum algorithm design, suggesting that their integration could revolutionize automated discovery and innovation across various fields.

Dr. Kadowaki is a prominent figure in quantum computing. In 1998, as a postgraduate student at the Tokyo Institute of Technology, he co-authored a seminal paper with Professor Hidetoshi Nishimori, proposing quantum annealing as a method for solving combinatorial optimization problems. This work laid the foundation for practical quantum computing applications. After earning his PhD in Physics in 1999, Kadowaki's career spanned various roles, including developing field-programmable gate arrays (FPGAs) at ROHM Semiconductor and engaging in bioinformatics and AI applications in drug discovery at Eisai. In May 2018, he joined DENSO to focus on quantum computer applications, aiming to harness quantum computing to address complex challenges in the automotive industry.

The integration of quantum computing and AI holds significant promise for advancing automation in scientific and engineering domains. Quantum computing's ability to process complex computations at unprecedented speeds can enhance AI algorithms, leading to more efficient data analysis, optimization, and machine learning processes. This integration could revolutionize fields such as drug discovery, materials science, and complex system modeling by enabling simulations and analyses that are currently infeasible with classical computing methods.

Several companies are actively exploring the integration of quantum computing into engineering simulations. For instance, Ansys and IonQ have partnered to enhance engineering simulation through advanced quantum computing. Their collaboration aims to accelerate simulation, expand high-fidelity design exploration, and reduce product development timelines, enabling faster market entry for innovative products. This partnership seeks to make simulation accessible to both quantum experts and non-experts, with the goal of enhancing enterprise value and streamlining product development processes.

The fusion of quantum computing and AI is poised to drive significant advancements in automation, potentially transforming industries by enabling more efficient problem-solving and innovation. However, this rapid technological progress also raises ethical considerations, including concerns about job displacement due to increased automation and the need for responsible development and deployment of these technologies to ensure equitable benefits across society.

The concept of quantum annealing, introduced by Kadowaki and Nishimori in 1998, has been instrumental in the development of practical quantum computing applications. Companies like D-Wave Systems have commercialized quantum annealing technology, offering quantum processors that address complex optimization problems. The ongoing research and development in this area continue to build upon these foundational concepts, pushing the boundaries of computational capabilities.

Dr. Kadowaki's introduction of Quantum CAE represents a significant step forward in the integration of quantum computing and AI within engineering design. As industries continue to explore and adopt these advanced technologies, the potential for transformative change in automation and problem-solving becomes increasingly tangible.