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Information Analysis Lab
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The lab connects information science with mathematics and physics to create new fields.
AboutAbout the lab
Connecting information science, mathematics, and physics as one
The Information Analysis Lab aims to build new fields by combining information science, applied mathematics, and physics.
Using mathematical methods, the lab investigates learning methods for quantum computation, collective motion such as the flocking of living organisms, and chemical reaction networks.
A weekly seminar is the core of the lab's activities, and third-year undergraduates begin with a reading group on statistics to build the foundation for moving on to research.
Research topics may be decided in consultation with the faculty, or students may find and propose their own.
Key terms
- Statistics
- Mathematics for reading overall trends, and how reliable they are, from data that vary
- Quantum natural gradient
- A method that efficiently optimizes the tunable parameters of a quantum circuit while taking the geometry of quantum states into account
- Vicsek model
- A simple model describing how individuals align their direction of movement with their neighbors, like flocks of birds or schools of fish
ResearchResearch themes
The lab aims to combine information science, applied mathematics, and physics to build new fields that span them. It works on learning algorithms for quantum computation, models of collective motion, and the speed limits of chemical reaction networks.
*Illustrative imageQuantum Natural Gradient
For the quantum natural gradient used in learning for quantum computation, the lab found that dropping the condition of monotonicity makes the computation faster.
*Illustrative imageModels of Collective Motion
The lab analyzed the Vicsek model of collective motion using DBSCAN, a clustering method, and discovered a previously unknown phase.
*Illustrative imageSpeed Limits of Chemical Reactions
Using ideas from information geometry and the natural gradient, the lab derived an upper bound on the speed at which chemical reaction networks proceed.
MembersFaculty
The members of the Information Analysis Lab consist of faculty and master's and undergraduate students.
- Associate ProfessorHideyuki Miyahara
VoicesStudent voices
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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: “Dilution Fridge with Quantum Processors Enclosed 008 8K” OJB Quantum / CC BY 4.0 (cropped)
- Quantum Natural Gradient: “Superconducting Metamaterial Chip 005” OJB Quantum / CC BY 4.0 (cropped)
- Models of Collective Motion: “Murmuration 11-2025” Skander zarrad / CC BY-SA 4.0 (cropped)
- Speed Limits of Chemical Reactions: “Belousov-Zhabotinsky reaction” Wiktor (Uncle Azane) / CC BY-SA 3.0 (cropped)
- Related lab (Algorithms Lab): “Sorting shellsort anim” Simpsons contributor / CC0 (cropped)
- Related lab (Integrated Nanosystems Lab): “Нейрон коры с множеством дендритных шипиков” Sergb95 / CC BY-SA 4.0 (cropped)
- Related lab (Structured Intelligence Lab): “Costa's Minimal Surface” Anders Sandberg / CC BY-SA 3.0 (cropped)
- Related lab (Photonic Information and Life Science Lab): “FluorescentCells” 作者不詳 / Public domain (cropped)
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