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Numerical Informatics Lab
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A numerical analysis lab that solves differential equations while preserving their properties.
AboutAbout the lab
Good numerical methods that preserve the properties of equations
The Numerical Informatics Lab studies numerical methods for solving differential equations on computers.
Problems in physics, chemistry, biology, finance, and other fields are often expressed as differential equations, and the challenge is how to discretize them and compute solutions.
Since the 1990s, the lab has been developing "structure-preserving numerical methods," which retain even the physical and mathematical structure behind an equation.
The lab also studies methods for approximating functions accurately, as tools that underpin numerical integration and the approximation of equations.
Key terms
- numerical analysis
- The field that devises ways to solve, by computer approximation, mathematical equations that cannot be solved by hand, and examines whether those methods are correct
- discretization
- Replacing continuously varying quantities with a finite number of values that a computer can handle
- function approximation
- Replacing a complicated function with a simpler form that is easy to compute, while keeping the error small
ResearchResearch themes
Many difficult problems in science and engineering cannot be solved by hand and have to be handled by computer calculation. Numerical analysis is the field that considers how to carry out such calculations and how to show that they are mathematically correct, and it forms the foundation of computational science, which relies on simulation.
*Illustrative imageStructure-preserving numerical methods
These are numerical methods designed by taking into account not only the equation itself but also the physics behind it and the abstract mathematical structure the equation has. They often yield algorithms that greatly outperform classical methods, and the lab has developed such methods for partial differential equations.
*Illustrative imageHigh-accuracy function approximation
For each type of function, the lab designs ways to approximate a function in an infinite-dimensional space by a finite-dimensional one that a computer can handle. It continues to study the Sinc method, which is based on the sinc function, and the DE-Sinc method, which combines it with the double exponential transformation.
MembersFaculty
The members of the Numerical Informatics Lab consist of faculty members, master's students, and undergraduate students.As of 2026
- ProfessorTakayasu MatsuoPublications ↗
- Assistant ProfessorHiroyuki Miyoshi
- Assistant ProfessorShinichi Ito
VoicesStudent voices
Compiled from answers by students who were in the lab. Ratings and reviews reflect individual students' experiences, not the lab's official views.
Students who take part in an interview may receive a thank-you gift worth ¥1,000, regardless of what they say.
On a 4-point scale, ● marks where students' answers fall
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Soliton hydro” Christophe.Finot et Kamal HAMMANI / CC BY-SA 2.5 (cropped)
- Structure-preserving numerical methods: “Joukowsky Karman Vortex Street s” T784303 at English Wikipedia / CC BY-SA 3.0 (cropped)
- High-accuracy function approximation: “Abs Sinc complex plot” Gisling / CC BY-SA 4.0 (cropped)
- Related lab (Computing Systems Lab (Nakamura-Takase)): “Pleiades two row” NASA Ames Research Center / Public domain (cropped)
- Related lab (Mathematical Planning and Informatics Lab): “Vierwies wind farm, seen from a hot air balloon, Zele, 2026” DimiTalen / CC0 (cropped)
- Related lab (Computational Informatics Lab): “SocialNetworkAnalysis” Martin Grandjean / CC BY-SA 4.0 (cropped)
- Related lab (Cryptography and Mathematical Informatics Lab): “Enigma-IMG 0487-black” Rama / CC BY-SA 2.0 fr (cropped)
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