Muon is an important signature in many new physics searches and Standard Model (SM) measurements performed at the general purpose detector, the Compact Muon Solenoid (CMS) at the Large Hadron Collider (LHC). The muon sub-detectors in CMS are crucial for the muon identification, triggering CMS readout and muon momentum measurements. The CMS detector and its muon sub-detectors have been performing extremely well in the last 10 years of operation. However, the high collision rate and increased concurrent interactions per collision expected at the high luminosity LHC (LHC), starting around 2029, poses several challenges for the current muon sub-detectors in reconstruction, readout and its general performance. In this talk, I will describe recent highlights in the consolidations and improvements of the CMS endcap muon system in view of HL-LHC operation. In the end, I will also talk about the latest developments of the milliQan detector, recently deployed at the CMS site to search for milli-charged particles, which are well motivated dark matter candidates carrying a fraction of electron charge.
Dr. Hualin Mei is a postdoctoral scholar from University of California, Santa Barbara, working on the CMS and milliQan experiments. He obtained his Ph.D. degree in 2018 from University of Florida, and B.S. degree in 2012 from Wuhan University. His research interests in CMS include properties measurements of the Higgs boson, search for BSM physics using the Higgs boson as a tool. He is currently the co-convener of the CMS Higgs to diphoton physics analysis group. He has also made important contributions to CMS's endcap muon system since 2013 in various aspects including operation, performance study, local reconstruction, DAQ electronics upgrade and its software/firmware developments. In 2022, he joined the milliQan experiment, participated in the construction and commissioning of the Run 3 detectors, and led the developments of DAQ and on-line monitoring of the experiment.
Online Meeting room: https://meeting.tencent.com/dm/4IPmQLbfcCLH
ID: 213932291 Password: 123456
Update your browser to view this website correctly. Update my browser now