Validating the CMS Search for Doubly Charged Higgs Bosons Using a Window-Based Background Estimation Method
Session Number
1
Advisor(s)
Dr. Peter Dong, IMSA
Location
B110
Discipline
Physical Science
Start Date
15-4-2026 10:15 AM
End Date
15-4-2026 11:00 AM
Abstract
The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) searches for doubly charged Higgs bosons (H++), exotic particles predicted by left-right symmetric extensions to the Standard Model whose discovery would represent a major breakthrough in particle physics. The primary CMS analysis employs an unbinned maximum likelihood fit to extract limits on H++ production cross sections. This investigation develops and implements a complementary window-based background estimation method as an independent validation of that primary analysis. Using C++ within the CMS software framework, signal and background event yields were calculated across fixed ±40 GeV mass windows centered at H++ test masses ranging from 500 to 1500 GeV across multiple same-sign lepton flavor channels. Background contributions were estimated using both histogram-based event counting and parameterized fit functions integrated over each window. Sensitivity was quantified using s/√(b+2.5) for each channel and mass point. At higher masses, parameterized curves provide more reliable background estimates where histogram statistics become sparse. Consistency between window-based results and the primary unbinned likelihood analysis strengthens confidence in the overall search strategy and validates the signal and background models employed.
Validating the CMS Search for Doubly Charged Higgs Bosons Using a Window-Based Background Estimation Method
B110
The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) searches for doubly charged Higgs bosons (H++), exotic particles predicted by left-right symmetric extensions to the Standard Model whose discovery would represent a major breakthrough in particle physics. The primary CMS analysis employs an unbinned maximum likelihood fit to extract limits on H++ production cross sections. This investigation develops and implements a complementary window-based background estimation method as an independent validation of that primary analysis. Using C++ within the CMS software framework, signal and background event yields were calculated across fixed ±40 GeV mass windows centered at H++ test masses ranging from 500 to 1500 GeV across multiple same-sign lepton flavor channels. Background contributions were estimated using both histogram-based event counting and parameterized fit functions integrated over each window. Sensitivity was quantified using s/√(b+2.5) for each channel and mass point. At higher masses, parameterized curves provide more reliable background estimates where histogram statistics become sparse. Consistency between window-based results and the primary unbinned likelihood analysis strengthens confidence in the overall search strategy and validates the signal and background models employed.