Tokyo Tech's Data Science for Particle and Nuclear Physics 2021 (DSPN2021), a lecture and practical training series for high school students, was held online on six Saturdays between October 2 and December 4, 2021. Organized under the leadership of School of Science Assistant Professor Makoto Uchida and supported by Tokyo Tech's STEM Education for Younger Generations fund, the workshops attracted sixteen high schoolers from around Japan. Lectures and training sessions were provided by faculty and students of Tokyo Tech's School of Science and alumni of the Institute, all of whom specialize in particle and nuclear physics.
Group shot of DSPN2021 participants
Throughout each session, the students learned about cutting-edge particle and nuclear physics, and boosted their programming and data science skills by conducting physical analysis using open and pseudo-data. With the incorporation of topics such as the Higgs boson particle, neutrino oscillation, and other areas related to Nobel Prizes in Physics since 2000, the practical training sessions allowed students to experience components of physical analysis methods that have led researchers to groundbreaking discoveries in recent decades.
Day 1: Tokyo Tech alumnus and Asst. Prof. Nobuyuki Kobayashi from Research Center for Nuclear Physics, Osaka University explaining data analysis used in nuclear physics experiments
Day 2: Tokyo Tech Prof. Takashi Nakamura speaking about nuclear physics and stellar evolution
In particle and nuclear physics experiments involving a large particle accelerator, a target is irradiated with accelerated particles, or these particles are collided with each other, resulting in the creation of new exotic particles. With improved particle accelerator technology, the beam intensity of accelerated particles has increased, and it is now possible to generate a large number of scattering and collision events. By utilizing pattern recognition, machine learning, and other data science techniques, events from the enormous amount of data can be selected quickly and efficiently, and statistics on the physics phenomena of interest can be accumulated for measurement and analysis.
Day 3: Tokyo Tech Prof. Masahiro Kuze explaining properties of neutrinos
Day 4: Tokyo Tech alumnus and Asst. Prof. Ryo Nagai of Chiba University talking about IceCube, the world's largest neutrino detector in Antarctica
Practical training was conducted using Jupyter, a browser-based python development environment. A Jupyter server was set up on the Google Cloud platform to enable analysis using general data science packages and tools developed in the field of elementary particle experiments. This allowed the students to proceed with the practical training regardless of their individual PC environments.
Day 5: Tokyo Tech Prof. Osamu Jinnouchi providing details of ATLAS experiment at CERN
Day 6: Tokyo Tech Assoc. Prof. Hiroyuki Fujioka introducing hadron physics experiments conducted at J-PARC in Ibaraki Prefecture
Many of the participants appeared satisfied with the sessions. Comments from students after the completion of the workshops included the following:
- I was able to learn more about research topics that interest me.
- My knowledge regarding previously unknown research topics increased.
- I learned programming while learning about physics.
The second DSPN2021 provided high school students with another unique opportunity to enhance their knowledge about forefront physics, data science, and programming while experiencing the stimulating environment of university-level learning.
