On Using Julia in High-Energy Physics Data Analysis

By Yuan-Ru Lin

議題

On Using Julia in High-Energy Physics Data Analysis

TR 413-1 [[ new Date( '2023-07-29 02:00:00+00:00' ).toLocaleDateString('ja', {year: 'numeric', month: '2-digit', day: '2-digit'}) ]] [[ new Date( '2023-07-29 02:00:00+00:00' ).toLocaleTimeString('zh-Hant', {hour12: false, hour: '2-digit', minute:'2-digit'}) ]] ~ [[ new Date( '2023-07-29 02:30:00+00:00' ).toLocaleTimeString('zh-Hant', {hour12: false, hour: '2-digit', minute:'2-digit'}) ]] en
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In software development, there are often situations where it's difficult to balance execution efficiency and development efficiency. When physicists analyze a large amount of detector data, they often develop prototypes in Python during the early stages and rewrite them in C++ for high-performance versions in the later stages.

I will take the research I conducted during my master's program in the Department of Physics at National Taiwan University as a case study, comparing the original implementation using Python with C++, and a version replicated in Julia, and comment on the Julia packages that correspond to each function in ROOT, the original framework.

講者

Yuan-Ru Lin

Yuan-Ru Lin

I have been a graduate student at the Experimental High-Energy Physics Laboratory at National Taiwan University for nearly six years. In addition to applying machine learning techniques in the context of physics analysis, I also enjoy thinking about engineering problems that may arise in the context of experimental high-energy physics.

This September, I will be attending the Physics Department's doctoral program at the University of Washington in Seattle, USA.

Julia Language HP9F3Z general (30mins)