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Saito Lab
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A lab that uses computer simulation to explore the behavior of quantum fluids and the application of machine learning to physics.
AboutAbout the lab
Tackling quantum fluids and machine learning through computer simulation.
The Saito Lab uses computer simulation to study quantum fluid dynamics and the application of machine learning to physics.
Quantum fluids, such as superfluids and Bose-Einstein condensates, are unusual fluids that have no viscosity and form quantized vortices, in which each vortex line is discrete.
In its machine learning research, the lab uses neural networks and similar methods to solve problems in quantum mechanics.
The lab's website says it suits students who are good at programming, but that students who are motivated can achieve results even if they lack confidence.
Key terms
- Quantum fluid
- A fluid such as a superfluid or a Bose-Einstein condensate. It has no viscosity, and its vortices form as discrete, individual lines.
- Quantized vortex
- A vortex that forms in a quantum fluid, with each vortex line discrete.
- Neural network
- A method used in artificial intelligence techniques. This lab uses it to solve problems in quantum mechanics.
NewsLab news
Paper published in Physical Review A
Paper published in Physical Review Research
Paper published in Physical Review A
Paper published in Physical Review Letters
Undergraduate student wins Excellent Presentation Award at the senior thesis presentation
ResearchResearch themes
The Saito Lab studies two themes, quantum fluid dynamics and the application of artificial intelligence techniques to physics, using computer simulation as its main method. The lab aims to understand the essence of fluid phenomena by investigating the behavior of quantum fluids, and it also works on using machine learning to solve problems in quantum mechanics.
*Illustrative imageQuantum Fluid Dynamics
Quantum fluids have no viscosity, and their vortices are discrete, with each vortex line separate (quantized vortices). By investigating their behavior, the lab aims to understand the essence of fluid phenomena.
*Illustrative imageApplying Artificial Intelligence Techniques to Physics
This research uses neural networks and machine learning (deep learning) to solve problems in quantum mechanics. Research applying these techniques to many fields of physics is advancing rapidly around the world.
MembersFaculty
The members of the Saito Lab are faculty members, researchers, visiting researchers, and doctoral, master's, and undergraduate students.As of 2026
- Hiroki Saito
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: “Liquid helium lambda point transition” Alfred Leitner photographed this as part of his movie "Liquid Helium, Superfluid". / Public domain (cropped)
- Quantum Fluid Dynamics: “Liquid helium Rollin film” I, AlfredLeitner, took this photograph as part of my movie "Liquid Helium,Superfluid" / Public domain (cropped)
- Applying Artificial Intelligence Techniques to Physics: “Physics-informed nerural networks” Riccardo Munafò / CC BY-SA 4.0 (cropped)
- Related lab (Yamakita Lab): “X-ray Photoelectron Spectroscopy system based on JEOL-4610” Minovich / CC BY-SA 4.0 (cropped)
- Related lab (Endo Lab): “Atomic-nucleus-3435” Yasminperry2020 / CC BY-SA 4.0 (cropped)
- Related lab (Sogabe Lab): “High voltage switchgear” Novoklimov / CC0 (cropped)
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