CAREER: Physics at the Interplay between the Higgs Boson and the Top Quark

The start-up of the Large Hadron Collider (LHC) a decade ago ushered in a new era of research in hitherto inaccessible energy regimes. The discovery of the Higgs boson is the first major highlight of the LHC program, which established that the predicted particle content and interactions of the Standard Model (SM) are complete. Despite this success, the SM is widely believed to be an incomplete theory.

Ongoing studies must determine whether or not this new Higgs boson is that of the SM, and new experimental data are essential to discover if and how Nature has chosen to extend the SM. These studies include new measurements and searches for new physics, primarily using data recorded at the highest currently available center-of-mass energy. The physics analysis activities form a comprehensive program to extend characterization of Higgs boson properties.

This award will push the limits of this search for physics beyond the SM by employing new Machine Learning techniques. The innovation being developed by this award: using Graph Neural Networks (GNN) to analyze the massive amount of data being produced by the ATLAS experiment at the LHC, will push the discovery potential in the Higgs boson study. The award will also expand an education and outreach effort using data from the LHC and GNN techniques into local area high schools and the general public.

This award will search for Beyond the SM (BSM) physics in the Higgs boson channels involving top-quark-associated production (ttH and tH). It will also further study Higgs decay into two-photon and four-quark channels. These are rare processes and will require the new techniques being developed by this award.

These channels are expected to put strong constraints on BSM physics. The novel use of GNN is in a nascent state but involves re-classifying LHC data into a graph structure. This graph structure can then be fed into a neural network which can in effect select out the very rare events that are of interest, revealing BSM.

This award will also further develop the upgrade to the ATLAS detector currently in preparation for the High Luminosity LHC (HL-LHC). The work will focus on the Strip Tracker upgrade and the Data Acquisition system, which requires a new software framework in order to meet the stringent performance requirements of the HL-LHC.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.