Monte Carlo Simulation and Data Analysis with ROOT in Particle Physics
by
N260/3.13
Description
This one-day hands-on workshop introduces the simulation and analysis workflows used in modern particle and nuclear physics. Examples are drawn from the analysis pipelines of the CBM experiment and reflect real research practice in the study of heavy-ion collisions.
Participants will learn how Monte Carlo simulations generate collision events with transport models such as PHSD. They will also see how reconstruction algorithms, including the Kalman Filter Particle Finder (KFPF), turn detector signals into physics observables. The practical part focuses on data processing, visualization and statistical analysis with the CERN ROOT framework.
The workshop is self-contained. It also provides the foundation for the follow-up workshop "Neural Networks for Scientific Data Analysis in Particle Physics", where the datasets and concepts introduced here are used as input for machine learning applications.
Learning Goals
Participants will learn how to:
- Understand Monte Carlo simulation workflows for heavy-ion collisions
- Work with reconstructed detector data
- Use ROOT for data visualization and statistical analysis
- Extract physics observables from collision events
Program
Morning
- Introduction to heavy-ion collision simulations
- PHSD transport model overview
- Monte Carlo event generation
- Detector reconstruction and the KFPF workflow
Afternoon
- Introduction to CERN ROOT
- Event data structure and storage
- Data visualization and statistical analysis
- Hands-on ROOT exercises
Target audience: Students and researchers in physics or related fields who want a practical introduction to simulation and data analysis. Basic programming experience (C++ or Python) is helpful.
NHR-SW@Goethe University Frankfurt