Julia is a modern programming language designed for high-performance scientific computing, offering the ease of dynamic languages with the efficiency of low-level languages. This hands-on session introduces Julia to scientists with prior programming experience (e.g. Python, C++, Fortran), focusing on its unique features such as multiple dispatch, just-in-time (JIT) compilation, and efficient...
Part 1: Motivation and Basic analysis setup
We introduce basic data operation and JuliaHEP analysis setup by going through the follow topics:
- use Open Data
- implement cut and count
- simple visualization
- write to Arrow or Parquet prepare for ML
Part 2: Basic ML and intro to MLJ
We demonstrate how to conduct the most common types of HEP analysis ML tasks in Julia,...
There are two main kinds of “fitting” in HEP – fitting function to data, and template fitting for statistical analysis. The two are linked, but each has enough depth to warrant a dedicated tutorial.
This tutorial connects familiar concept in HEP to best practices in Julia ecosystem. We go through the following topics:
• Simple curve fitting by minimizing Chi2, we use this as an opportunity...