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particle physics, high-performance computing, programming, data analysis, modeling & simulation

WHAT WE DO

Key Points:

  • Computing-based experimental particle physics research 

  • Modeling & simulation of novel particle detectors

  • Data analysis and visualization

Detailed Description:

FIRE Simulating Particle Detection introduces undergraduate students to the field of experimental particle physics, concentrating on computing-based research using simulation of novel, high-energy particle detectors. It aims to apply analysis methods to investigate elementary particle detection in simulated data that could be used in improving the performance of detectors to be commissioned in the near future.

WHY IT MATTERS

Key Points:

  • Experimental particle physics aims at explaining the fundamental forces and particles.

  • Equipment at CERN needs to be modeled using state-of the-art simulation for an improved design and physics performance.

Detailed Description:

Experimental particle physics explores the building blocks of the universe, and aims at explaining the fundamental forces and particles. Large Hadron Collider at CERN is a high energy particle accelerator and collider designed and built for this aim. One of the experiments at the LHC, the CMS experiment, is going through an upgrade in the so-called endcap region, to address the issues of the increasing demands of its physics reach. This upgrade pushes the boundaries of technology to deal with the high amount of energetic particle data it will receive once commissioned. The upgraded CMS detector needs to be modeled using state-of the-art simulation for an improved design and physics performance that meets the expectations as defined by the goals of the experimental programme. In addition to answering fundamental questions of the universe, the scientific work performed at CERN has a direct positive effect on society and technology, globally.

WHAT YOU LEARN

Key Points:

  • Basic concepts of high energy particle physics detection and design

  • Monte Carlo simulation tools for particle detectors

  • Data analysis and visualization of large datasets using C++ and Python

  • Designing algorithms to perform detector performance studies

  • How to utilize computer clusters