Experimental high energy physics is a field taking place at the frontiers of knowledge. Its goal is to investigate in detail the fundamental constituent of the structure of the universe: its particles. Experiments in this field generate enormous amounts of data at very high rates which needs to be stored and analysed.
This line aims at facing the challenges related to the use of data in particle detection, by using advanced statistical analysis and artificial intelligence techniques, specifically in three aspects:
Event reconstruction, that is, to interpret the electronic signals produced by a detector to determine the original particles that passed through
Trigger precision and efficiency, which involves deciding which collision data is worth keeping for storage and future analysis
Physics analysis, to analyse reconstructed data to deliver precise measurements which enable the verification of the underlying physical theory.
The ultimate goal of this line of research is to contribute to have a real time analysis system that is able to conduct a physics analysis in real time, at a speed of several terabytes per second.
Topics: High Energy Physics (HEP) | Data analysis | Application of artificial intelligence techniques | Study of new data acquisition techniques (GPU vs. CPU).