Speeding up of symbolic computation and its application to solving industrial problems 3
| Reference No. | 2025a012 |
|---|---|
| Type/Category | Grant for Young Researchers and Students-Short-term Joint Research |
| Title of Research Project | Speeding up of symbolic computation and its application to solving industrial problems 3 |
| Principal Investigator | Yuki Ishihara（Nihon University, College of Science and Technology, Department of Mathematics・Assistant Professor） |
| Research Period |
November 10,2025. -
November 14,2025. |
| Keyword(s) of Research Fields | Symbolic Computation (Computer Algebra), Groebner Basis, Quantifier Elimination, Mathematical Optimization, Real Algebraic Geometry, Primary Decomposition, Symbolic-Numeric Computation, Nonlinear Control Theory, Mathematical Modeling |
| Abstract for Research Report |
Symbolic Computation is a type of computational method for working with mathematical expressions and mathematical objects. While numerical computation is often compared to symbolic computation, symbolic computation excels at analyzing mathematical structures based on exact calculations. On the other hand, however, it is computationally expensive, and many of them are exponential in computational complexity, such as the Groebner basis and the quantifier elimination (QE) algorithms. As a continuation of the FY2024 Joint Research Project “Speeding up of symbolic computation and its application to solving industrial problems 2,” this research aims to solve problems that appear in industry by improving various existing algorithms for symbolic computation. In FY2024, experts from various fields such as computer algebra, cryptography, statistics, optimization theory, machine learning, control theory, and mathematical modeling participated and discussed recent trends in symbolic computation and industrial issues. In FY2025, research will be conducted on the issues that have emerged so far from the perspective of speeding up computation and developing new methods. For example, one of the results presented in the joint research until FY2024 is a method for speeding up symbolic computation using machine learning, which can be applied to specific industrial issues such as robot control and system simulation. In addition, we plan to develop algorithms specialized for symbolic computation in specific fields, such as control theory and optimization theory. We also plan to invite experts from industry to give invited lectures, with the aim of connecting the developed algorithms to real-world applications. One of the goals of the research after FY2026 is to disseminate the results of the research both domestically and internationally through papers and research presentations, leading to breakthroughs in academia and industry. The expected results of this research are mainly the following two points. (1) Speed-up of symbolic computation specialized for solving specific problems (2) Development of a new approach to symbolic computation for industrial problems |
| Organizing Committee Members (Workshop) Participants (Short-term Joint Usage) |
Yuki Ishihara（Nihon University, College of Science and Technology・Assistant Professor） Ryoya Fukasaku（Kyushu University, Faculty of Mathematics・Assistant Professor） Yasuhiko Ikematsu（Kyushu University, Institute of Mathematics for Industry・Associate Professor） Yuta Kambe（Mitsubishi Electric Information Technology R&D Center・Research Associate） Hidenao Iwane（Reading Skill Test, Inc.・Employee） Masaru Ito（Nihon University, College of Science and Technology・Assistant Professor） Munehiro Kobayashi（Schilf Institute Co., Ltd.・Representative Director） Tsuyoshi Yuno（Kyushu University, Faculty of Information Science and Electrical Engineering・Assistant Professor） Hiroshi Kera（Chiba University, Graduate School of Informatics・Assistant Professor） Tomoyuki Iori（Japan Aerospace Exploration Agency, Space Tracking and Communications Center・Researcher） Mizuka Komatsu（Kobe University, Graduate School of System Informatics・Assistant Professor） |