Experimental Particle Physics Seminars in 2024

Wednesday January 31 2024 at 3:30pm  in DRL 3W2
Yi-Mu Chen (University of Maryland)
Search for Emerging Jets at CMS

I present the search for emerging jets produced in proton-proton collisions at a center-of-mass energy of 13 TeV performed using data collected by the CMS experiment corresponding to an integrated luminosity of 138 fb-1. This search examines a hypothetical dark QCD sector that couples to the standard model (SM) through a scalar mediator. The scalar mediator decays into a standard model quark and a dark sector quark. As the dark sector quark showers and hadronizes, it produces long-lived dark mesons that subsequently decay into SM particles, resulting in a jet with multiple displaced vertices, known as an emerging jet. This search looks for pair production of the scalar mediators at the LHC, yielding events with two SM jets and two emerging jets at leading order. This presentation discusses the CMS sensitivity to the such dark sector phenomenons using novel jet tagging techniques using graph-neural networks with the background estimated via a fully data based technique.

Wednesday February 7 2024 at 3:30pm  in DRL 3W2
Kaito Sugizaki (Tokyo University)
Muon trigger system and search for supersymmetry
The ATLAS experiment, consisting of over 3,000 members, explores new frontiers in physics with high-energy proton-proton collisions at the LHC. In such a large collaboration, it is crucial to devote oneself to multiple topics to grasp the big picture of the experiment, from detector operation to physics analysis.
The seminar will focus on two topics from the speaker’s experience in ATLAS. Part 1 highlights the development, commissioning, and operation of the Level-1 muon trigger system for the ongoing LHC Run 3. The Level-1 muon trigger system has been significantly upgraded for Run 3 to process inputs from new inner muon detectors. Stable operation and data-taking have been achieved; particular emphases will be put on the developments of systematic control softwares, monitoring and recovery procedures, and a new software-based readout system. Part 2 highlights the search analysis for supersymmetry with full Run 2 data. MSSM models having higgsinos with compressed mass spectra are viable candidates of physics beyond the Standard Model. Dedicated low-momentum lepton identification and neural network based event selection methods have been developed to ameliorate the sensitivity to higgsinos. As the search analysis is still in progress, tentative results will be presented.

Wednesday February 28 2024 at 3:30pm  in DRL 3W2
Tae Min Hong (University of Pittsburgh)
Exotic Higgs decays & AI triggers at the LHC (ATLAS)
Data at the LHC allows us to probe whether the Higgs boson communicates with unknown and/or undiscovered sectors beyond the Standard Model. I will discuss ATLAS results on the searches for Higgs decays to dark matter candidates [2202.07953, 2109.00925] as well as MC studies of exotic Higgs decays to pseudoscalars in the 4b [2306.01901] and 2γ2b final states. I will also describe the technical challenges of triggering on such events using missing energy and/or jets, including novel approaches to ML in real-time FPGA-based trigger systems [2104.03408, 2207.05602], including unsupervised AI via anomaly detection using decision-tree-based autoencoders [2304.03836].

Tuesday March 19 2024 at 12:30pm  in DRL 3C4
Ho Fung Tsoi (University of Wisconsin-Madison)
Search for exotic Higgs boson decays with CMS and fast machine learning solutions for the LHC
There is still room for BSM physics in the scalar sector, which could manifest as Higgs boson decays to a pair of light pseudoscalars. I will present a search for such decay in final states with two b quarks and two muons or two tau leptons, using the LHC Run 2 data of proton-proton collisions collected by the CMS detector. On enhancing the overall experimental sensitivity at a lower level, I will introduce a novel machine learning-based trigger algorithm that uses anomaly detection technique to search for new physics in a model-agnostic way as close to the raw collision data as possible, i.e. the CMS Level-1 trigger, which filters collision events of 40 MHz at real time at a latency of O(100) ns on FPGAs. Symbolic regression for further accelerating machine learning inference at nanoseconds on FPGAs is also discussed.

Wednesday March 20 2024 at 3:30pm  in DRL 3W2
Daisy Kalra (Columbia University)
Searching for Exotic and Rare Physics Processes
with Liquid Argon Time Projection Chamber Detectors

Neutrinos are some of the most abundant but elusive particles in the universe. The
groundbreaking discovery of neutrino oscillations, recognized by the 2015 Nobel Prize, revealed
the existence of non-zero neutrino masses, providing compelling evidence for new physics
beyond the Standard Model (BSM). This discovery has sparked up a wealth of fascinating
questions, including the hypothesized presence of additional neutrino states, the connection
between neutrinos and cosmology, and the connection of neutrinos and astrophysics. This has
prompted a wealth of neutrino experiments aiming to improve our understanding of neutrinos. At
the same time, experiments designed with unparalleled precision to test neutrino properties can
enable searches for other rare and exotic physics processes, such as neutron-antineutron
transition, proton decay, or neutrinos from Supernova bursts.
This talk will highlight the capabilities of the current-generation Liquid Argon Time Projection
Chamber (LArTPC)-based neutrino detectors in searching for BSM physics. Among various
BSM physics processes, I will focus on recent results from a deep learning-based analysis of
MicroBooNE data, making use of a sparse convolutional neural network and event topology
information to search for argon-bound neutron-antineutron transition-like signals. This analysis
demonstrates the capability of LArTPCs to achieve high signal efficiency and strong background
rejection when leveraging advances in image analysis techniques. Furthermore, this talk will
discuss ongoing research and development (R&D) aimed at developing data-driven data
selection for LArTPC detectors—a major challenge particularly for large-scale detectors such as
the future Deep Underground Neutrino Experiment (DUNE) due to its exorbitant data rate. The
objective of this effort is to develop real-time data selection schemes as well as offline data
analysis for rare signals with very high accuracy and computational performance. Drawing from
my own research experience, I will describe how these required advancements will enable
sensitive searches for exotic and rare physics signals in DUNE.

Wednesday April 3 or April 17, 2024 at 3:30pm  in DRL 3W2

Wednesday April 24 and May 1, 2024 at 3:30pm  in DRL 3W2
Joint HEX-HET seminars scheduled

Previous seminars before 2023-24

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