Department of Pure and Applied Physics
Faculty of Engineering Science
Exploring the essence of nature from elementary particlesto matter, life and the universe.
Physics is a discipline that covers everything from elementary particles to matter, life, and the entire universe. There are countless examples of research results and theories that elucidate the essence of natural phenomena bringing about major changes in society. Our department aims to cultivate engineers and researchers who can return such research results to society and contribute to the development of the world. Graduates are expected to be active in various fields including the information, electrical, mechanical, and chemical industries.
Students learn subjects that form the backbone of physics such as quantum mechanics and fluid dynamics to deepen their understanding of natural laws, and acquire the foundation to become researchers, engineers, and teachers through practical training in numerical simulation using computers.
Students learn deeply about light, ultrasound, or magnets (electron spin), and acquire knowledge and experimental techniques that lead to the development of more efficient solar cells, high-performance medical diagnostic equipment, or high-density memory.
Graduate School of Science and Engineering, Major in Engineering Science, Physics and Applied Physics Field, 2nd Year
Hitomi Kanatani
I am developing an "optical synapse device" that mimics the mechanism by which humans learn and memorize from visual information. The goal is to give it the function to change the ease of memorization depending on the repetition and intensity of information, just like the human brain. The material uses "two-dimensional materials" that are only a few atomic layers thick, obtained by "peeling off" crystals stacked in layers.
We have succeeded in developing a device that makes it easier for current to flow by repeatedly inputting optical signals, improving information transmission. We are currently designing a device that, conversely, makes it harder for current to flow by signal input, suppressing information transmission. I am thinking of applying this research to realize machine learning with lower power consumption.
