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Nonlinear Physics Lab
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The lab uses mathematical models to unravel complex phenomena such as synchronization and fluctuations.
AboutAbout the lab
Understanding the world through modeling and theory building
The Nonlinear Physics Lab studies complex dynamical systems found in nature, living organisms, and artificial systems.
It describes the mechanisms that give rise to these phenomena with mathematical models that are as simple as possible, and uses them for understanding, prediction, control, and optimization.
The lab's research is based on the theory of dynamical systems (differential equations) and stochastic processes, as well as numerical simulation.
It collaborates with experimental researchers in engineering, biology, medicine, and chemistry, and aims to solve problems that society needs solved.
Key terms
- Dynamical systems
- A field of mathematics that studies how the state of a system changes over time, using tools such as differential equations
- Synchronization
- A phenomenon in which things that were moving independently influence one another and come to share the same rhythm
- Complex networks
- Networks of nodes and links with irregular connection patterns, with the kind of structure seen in social and biological systems
ResearchResearch themes
To understand complex dynamical systems found in nature, living organisms, and artificial systems, the lab develops fundamental theory and carries out mathematical modeling and analysis. Working closely with experimental researchers, it aims to solve problems that society needs solved.
*Illustrative imageAnalysis of complex phenomena and networks
The lab models and analyzes a variety of physical and biological phenomena, as well as dynamical phenomena involving complex networks. Its subjects include synchronization, self-organization, pattern formation, fluctuations, and chaos.
*Illustrative imageData analysis of biological phenomena
The lab analyzes time-series data from living organisms, such as gene expression data and behavioral data, to characterize phenomena and explore the mechanisms behind them. When needed, it performs deterministic or statistical model estimation.
*Illustrative imageTime-series modeling and data analysis
The lab develops analysis techniques that use time-series data measured from biological and social systems to understand the underlying mechanisms and to predict future activity. It uses point processes and machine learning.
*Illustrative imageModeling of nonlinear and nonequilibrium phenomena
The lab builds mathematical models of nonlinear oscillators and their networks, fluids, engines, energy harvesting, and more, and clarifies their properties through theoretical and numerical analysis and simulation.
MembersFaculty
The members of the Nonlinear Physics Lab include faculty, researchers, doctoral and master's students, undergraduates doing their graduation research, and secretaries.As of 2026
- ProfessorHiroshi KoriPublications ↗
- Associate ProfessorRyota Kobayashi
- Associate ProfessorYuki IzumidaPublications ↗
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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: “Vein skeleton of a leaf (de-ghosted)” Brocken Inaglory / CC BY-SA 3.0 (cropped)
- Analysis of complex phenomena and networks: “Fireflies and Star Trails - PGL57 - Tyler Savitski” Tyler Savitski / CC BY-SA 4.0 (cropped)
- Data analysis of biological phenomena: “DNA double helix 45” Jerome Walker,Dennis Myts / Public domain (cropped)
- Time-series modeling and data analysis: “Brow motion blue” Lbertolotti / CC BY-SA 4.0 (cropped)
- Modeling of nonlinear and nonequilibrium phenomena: “Kontax low temperature difference Stirling Engine on a Coffee cup” Michele M. F. from Milano, Italy / CC BY-SA 2.0 (cropped)
- Related lab (Mathematical Bioinformatics Lab): “Mouse Embryo Cerebellum ( )” NIH Image Gallery from Bethesda, Maryland, USA / Public domain (cropped)
- Related lab (Systems Pharmacology Lab): “Lab mouse mg 3263” Rama / CC BY-SA 2.0 fr (cropped)
- Related lab (Brain Mathematics and Information Collaboration Lab): “Synapsin and CamK2 positive neurons” ManuelSchottdorf / CC BY-SA 4.0 (cropped)
- Related lab (Systems and Control Lab): “Kilobot robot swarm” asuscreative / CC BY-SA 4.0 (cropped)
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