Physics & Astronomy Colloquium – Spring 2019 – Gleyzer

Speaker: Sergei Gleyzer

Title: Opportunities for New Physics with Modern Deep Learning Methods for the CMS Experiment

Abstract: The Large Hadron Collider (LHC) has achieved unprecedented levels of
sensitivity to new particles at the TeV scale with on-going searches for new
physics, including dark matter. This sensitivity trend is expected to continue
during the next run beginning in 2021 and with the High-Luminosity Large
Hadron Collider (HL-HLC), anticipated to start data taking in 2026. Additional
complexity arises from a significant increase in pile-up, or extra particle collisions
of protons traveling in the same bunch, leading to far more complicated event
signatures at the HL-LHC. New ideas for event reconstruction and data analysis
are required to address the experimental challenges posed by the rarity and
unknown properties of the sought-after new physics signals, such as dark matter,
and the complex experimental environment at the HL-LHC. In my talk, I will
discuss the application of new state-of-the-art data science methods, such as
modern deep learning networks, to Higgs Boson physics, new physics searches
at the LHC and HL-LHC, detector reconstruction, particle identification and realtime
event filtering for the CMS experiment, including new detector technology
developed today. I will conclude by presenting significant new opportunities in the
field of particle physics enabled by data science.

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