Session I03: LHC Results and Techniques

Using Machine Learning to Break the Unnaturalness of Nature

Despite decades of searching and the discovery promise of the LHC era, we’ve found no direct evidence that our world is supersymmetric. Without any direct Beyond-the-Standard-Model (BSM) discovery at the LHC, we ask if there are any ways that a low mass, natural supersymmetry (SUSY) may have evaded our searching. In this talk, I’ll cover how R-Parity-violating SUSY could still be hiding at the LHC, and how a new approach to machine learning is needed to find it.   

Implicit quantile networks for jet reconstruction and mapping

We used Implicit Quantile Networks (IQNs) for successful jet simulation and correction using the tools and simulated data from the Compact Muon Solenoid (CMS) Open Data portal. Jets that are created post-hadronization ({\em gen-jets}) are subject to detector effects and are observed as {\em raw reco-jets}. Often, corrections are applied to raw reco-jets based on knowledge of the detector response. These corrected jets are {\em reco-jets}. We consider two tasks: first, given the four-momentum of a gen-jet $\bm{g}$, we model the conditional density of the four-momenta of the corresponding reco-jets (i.e., $p(\bm{r}|\bm{g})$). Second, we consider the inverse problem: given a raw reco-jet $\bm{\hat{r}}$, we output the conditional density of the four-momenta of the gen-jets that are consistent with $\bm{\hat{r}}$ (i.e., $p(\bm{g}|\bm{\hat{r}})$). In this talk, we present the methodology of IQNs and present our results from this work.   

Studies with the Pixel Luminosity Telescope of CMS

For the upcoming Run-3 of the LHC, the CMS experiment has installed a pixel luminosity telescope (PLT) that is made of three layers of pixel sensors that count charged particles from each bunch crossing of the LHC beam. The rate of triple-coincidences between layers is translated into a luminosity value that is published about every 1.3 seconds. In addition, at a lower rate, particle trajectories are reconstructed for systematic studies of beam backgrounds and efficiencies. I will present such studies based on Run-2 data and their application to monitor the beam conditions and detector status during Run-3 data taking.   

Rare Higgs Decays into Z Boson and Upsilon Meson

Rare decays of the Higgs boson are promising laboratories to search for physics beyond the standard model (BSM). Such BSM physics might alter Yukawa couplings to lighter quarks and add loop diagrams, possibly resulting in higher decay rates than predicted by the standard model. For the first time the decay of the Higgs boson into a Z boson and Upsilon states are searched, where the Y(1S), Y(2S) and Y(3S) states are combined. A data sample of proton-proton collisions collected at a center-of-mass energy of 13 TeV with the Compact Muon Solenoid detector at the Large Hadron Collider that corresponds to an integrated luminosity of about 137 fb$-$1 is used. I will present the search and implications for future searches of BSM signatures at high luminosity.   

Search for Exotic Long-Lived Particles in the Compact Muon Solenoid (CMS)

\begin{abstract} With increasing center-of-mass energy, high-energy physics has seen enormous development in the past decades. Discovery of the Higgs Boson at Large Hadron Collider (LHC) in CERN, led to discovery of all constituents in the standard model (SM). In spite of its success, the SM suffers from the naturalness problem. To solve the issue, one needs to look for physics Beyond Standard Model (BSM). Among the various particles postulated by multiple BSM models, long-lived neutral scalar particles are investigated. The analysis looks for Displaced Vertices (DV) in LHC data, which are signatures of long-lived scalar particles due to its neutral electric charge and tracker lifetime. In this analysis, the DV candidates are constructed in the form of the Regions Of Interest (ROIs) in the tracker. The ROIs are then scored by Machine-Learning (ML) tools, which are trained with the Monte-Carlo (MC) simulated events. The analysis uses data obtained from the Compact Muon Solenoid (CMS), one of the general detectors of LHC located in CERN. \end{abstract}