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Speaker: Elliot Reynolds (LBNL) – Title: Probing the associated production of the Higgs boson and charm quarks at ATLAS
August 29 @ 4:00 pm - 5:00 pm
Research Progress Meeting
Date: August 29, 2024
Time: 4:00- 5:00 pm
Location: Sessler Conference Room- 50A-5132 [In-Person and HYBRID]
Speaker: Elliot Reynolds (LBNL)
Title: Probing the associated production of the Higgs boson and charm quarks at ATLAS
Abstract: One of the most extraordinary discoveries about the universe is that the more of it we explain, the simpler the explanations become. The Standard Model (SM) of particle physics is the culmination of this journey, and explains most of our day-to-day world with just a handful of particles. We know, however, that the SM is incomplete, and because aspects of it still seem arbitrary, we suspect a deeper theory may lie beneath. One of the clearest examples of this is the masses of the fermions, which span many orders of magnitude, seem to have largely arbitrary values, and fall into a clear hierarchy, yet none of these facts are explained in the SM. To understand these things, we should explore how the masses of the fermions arise, which is thought to be due to their interactions with the Higgs boson. Measuring these interactions is therefore a major priority at the Large Hadron Collider, where they have already been measured for the third-generation fermions, and almost for the muon. These measurements remain elusive for the first- and second-generation quarks, though the charm quark is likely our best opportunity to remedy this. Measuring the interactions between the Higgs boson and the charm quark is proving highly challenging, however, and new methods will be needed. This talk presents the first inclusive search for the associated production of the Higgs boson and charm quarks, which uses the ATLAS detector. The search represents an unconventional avenue to probe their interaction strength, and introduces a new Higgs boson production measurement. This work also represents the first usage of Gaussian process regression for direct background estimation in a particle physics data analysis.
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