Data Science for Particle and Nuclear Physics 2021 (DSPN2021), a lecture and practical training series for high school students hosted by Tokyo Tech, was offered online on six Saturdays between October 2 and December 4, 2021. The sessions, organized by School of Science Assistant Professor Makoto Uchida and funded by Tokyo Tech’s STEM Education for Younger Generations initiative, drew sixteen high school students from throughout Japan. Faculty and students from Tokyo Tech’s School of Science, as well as Institute alumni, delivered lectures and training courses in particle and nuclear physics.

During each session, the students learnt about cutting-edge particle and nuclear physics while also honing their programming and data science abilities via physical analysis utilizing open and pseudo-data. Since 2000, the practical training workshops have enabled students to experience components of physical analytical techniques that have led researchers to important discoveries, such as the Higgs boson particle, neutrino oscillation, and other areas connected to Nobel Prizes in Physics.

In particle and nuclear physics studies employing a big particle accelerator, a target is bombarded with accelerated particles or these particles clash, resulting in the formation of new exotic particles. The beam intensity of accelerated particles has grown due to better particle accelerator technology, and it is now feasible to create a significant number of scattering and collision events. Pattern recognition, machine learning, and other data science methods may be used to rapidly and effectively identify events from massive amounts of data, and statistics on physics phenomena of interest can be amassed for measurement and study.

Jupyter, a browser-based Python coding environment, was used for hands-on teaching. On the Google Cloud platform, a Jupyter server was set up to allow analysis using generic data science packages and technologies created in the area of elementary particle studies. This enabled the students to continue with their practical instruction independent of their own PC setups.

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The seminars looked to be well received by the majority of the attendees. Following the conclusion of the sessions, students provided the following feedback:

I was able to have a better understanding of study issues that are of interest to me.

My understanding of previously undiscovered study subjects has grown.

I learnt to program while studying physics.

The second DSPN2021 offered high school students another once-in-a-lifetime chance to expand their understanding of cutting-edge physics, data science, and programming while immersing themselves in the stimulating atmosphere of university-level study.

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