WHAT WE DO

FIRE SPD 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

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 need to be also 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

Basic concepts of high energy particle physics detection; Monte Carlo simulation tools for particle detectors; basics of detector design; data analysis and visualization of large datasets; designing algorithms to perform detector performance studies; code development in a large software framework; utilizing computer clusters.

  • Dr. Muge Karagoz

    Research Educator

  • Dr. Sarah Eno

    Faculty Advisor

  • Dr. Alberto Belloni

    Faculty Advisor

University of Maryland

Office of the Senior Vice President and Provost

The First-Year Innovation & Research Experience

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Dr. Patrick Killion

Director of Discovery-Based Learning

Email: pkillion@umd.edu

Tel: 301-405-0057