2015 Data Science Workshop


Wed, April 29, 2015
Location: Fisher Conference Center, Arrillaga Alumni Center

"Physics Event Reconstruction at the Large Hadron Collider"


The aim of this proposal is to develop and apply data science techniques to address fundamental challenges of physics event reconstruction and classification at the Large Hadron Collider (LHC). The large and complex LHC dataset and its associated challenges are ideal for the application of novel data science techniques. The datasets of the LHC experiments are among the largest in all of science. They are rich in information, both in the detail of each event and in the sheer mass of events collected. Up until now, most of the methods used to extract useful information from the large datasets have been based on physics intuition built from existing models. By applying advanced data science methodology, we will develop tools for determining achievable classification performance for a variety of relevant physics processes and develop techniques for addressing one of the most important issues facing the longer term interpretation of LHC events -- many overlapping collisions in a single event. These developments will have important implications in extracting knowledge in high energy physics. The problem also provides a setting for more general exploration of tools to find subtle correlations embedded in a large dataset.