
Hannah Bossi developed core analysis infrastructure for the ginnocen/MITHIGAnalysis2024 repository, focusing on high energy physics workflows in C++ and Shell. Over four months, she engineered modular frameworks for D0 meson and jet analyses in ultra-peripheral collisions, implementing data reduction pipelines, event selection logic, and reproducible plotting routines. Her work introduced configurable modules for prompt versus non-prompt signal separation, event shape engineering, and gamma+N event identification, leveraging ROOT for data processing and Monte Carlo simulation. The codebase emphasized scalability, parallel processing, and data/MC comparison, providing a robust foundation for collaborative physics analysis and future feature expansion.

August 2025: Delivered Gamma+N event identification and analysis enhancements in ginnocen/MITHIGAnalysis2024. Implemented a new isGammaN flag in Messenger, updated UPCEEC.cpp to leverage the flag for selection/analysis, and extended DataAnalyzer to compute and store histograms of event properties and particle characteristics to support future data/MC comparisons. Initiated data/MC agreement investigations to validate acceptance and selection criteria.
August 2025: Delivered Gamma+N event identification and analysis enhancements in ginnocen/MITHIGAnalysis2024. Implemented a new isGammaN flag in Messenger, updated UPCEEC.cpp to leverage the flag for selection/analysis, and extended DataAnalyzer to compute and store histograms of event properties and particle characteristics to support future data/MC comparisons. Initiated data/MC agreement investigations to validate acceptance and selection criteria.
June 2025 performance summary for ginnocen/MITHIGAnalysis2024: Delivered foundational Event Shape Engineering (EEC) analysis support within the HFJet framework, establishing scaffolding for future physics analyses. Implemented new header files for RNG and four-vector calculations, updated Messenger to support UPCEEC, and laid groundwork for processing particle flow candidates and tracks to derive EEC distributions with options to use summed transverse momentum (pT) or transverse mass as the hard scale. This work strengthens analytical capabilities, accelerates early validation, and enhances collaboration traceability. No critical bugs fixed this month; focus was on feature development and architectural readiness.
June 2025 performance summary for ginnocen/MITHIGAnalysis2024: Delivered foundational Event Shape Engineering (EEC) analysis support within the HFJet framework, establishing scaffolding for future physics analyses. Implemented new header files for RNG and four-vector calculations, updated Messenger to support UPCEEC, and laid groundwork for processing particle flow candidates and tracks to derive EEC distributions with options to use summed transverse momentum (pT) or transverse mass as the hard scale. This work strengthens analytical capabilities, accelerates early validation, and enhances collaboration traceability. No critical bugs fixed this month; focus was on feature development and architectural readiness.
March 2025 monthly summary for ginnocen/MITHIGAnalysis2024: Delivered end-to-end Dzero Jet UPC data handling and forest reduction pipeline. Implemented DzeroJetUPCTreeMessenger for robust UPC data flow in D0 jets; introduced ReduceForest.cpp to process and reduce forest data using the new messenger; added shell scripts enabling parallel processing for data and Monte Carlo samples. This work is backed by commit c5995d4b457924a67a3ce42e4c5d3dbf4ec915aa ([HFJet:Add updated Messenger] (#92)). No separate bug fixes were reported in this dataset; however, the new features improve data reliability, throughput, and scalability across data and MC processing.
March 2025 monthly summary for ginnocen/MITHIGAnalysis2024: Delivered end-to-end Dzero Jet UPC data handling and forest reduction pipeline. Implemented DzeroJetUPCTreeMessenger for robust UPC data flow in D0 jets; introduced ReduceForest.cpp to process and reduce forest data using the new messenger; added shell scripts enabling parallel processing for data and Monte Carlo samples. This work is backed by commit c5995d4b457924a67a3ce42e4c5d3dbf4ec915aa ([HFJet:Add updated Messenger] (#92)). No separate bug fixes were reported in this dataset; however, the new features improve data reliability, throughput, and scalability across data and MC processing.
December 2024 monthly summary for ginnocen/MITHIGAnalysis2024 focused on delivering an end-to-end analysis framework for D0 meson production in ultra-peripheral collisions (UPC), enabling clear differentiation between prompt and non-prompt contributions and establishing a scalable, reproducible workflow.
December 2024 monthly summary for ginnocen/MITHIGAnalysis2024 focused on delivering an end-to-end analysis framework for D0 meson production in ultra-peripheral collisions (UPC), enabling clear differentiation between prompt and non-prompt contributions and establishing a scalable, reproducible workflow.
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