IMSA-CMS/CMSAnalysis
Jun 2025 – Dec 2025
6 Months active
Languages Used
C++
Technical Skills
C++Data AnalysisROOTC++ ProgrammingHigh Energy PhysicsROOT Framework
Brooke Hobbs
PROFILE
Brooke Hobbs
Over six months, Ben Hobbs developed and enhanced data analysis workflows in the IMSA-CMS/CMSAnalysis repository, focusing on high energy and particle physics applications. He implemented automated background fitting for Higgs and Drell-Yan processes, parameterized histograms across channels, and streamlined particle data models by refactoring class structures. Using C++ and the ROOT framework, Ben improved statistical modeling accuracy, reduced manual analysis steps, and enhanced traceability through robust error handling and logging. His work addressed both signal and background paths, optimized data loading and plotting for Dark Photon studies, and prioritized maintainability, resulting in more reliable, scalable, and efficient scientific computing pipelines.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
15Total
Bugs
0
Commits
15
Features
7
Lines of code
2,474
Activity Months6
Your Network
34 people
Work History
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025: Focused refactor in IMSA-CMS/CMSAnalysis to streamline particle representation for analysis by removing dxy and dz parameters from particle classes and methods. This reduces data complexity, accelerates analysis pipelines, and lowers maintenance burden while preserving essential attributes.
1 Commits • 1 Features
Dec 1, 2025December 2025: Focused refactor in IMSA-CMS/CMSAnalysis to streamline particle representation for analysis by removing dxy and dz parameters from particle classes and methods. This reduces data complexity, accelerates analysis pipelines, and lowers maintenance burden while preserving essential attributes.
December 2025
November 2025
2 Commits • 1 Features
Nov 1, 2025In November 2025, delivered consolidated Higgs fitting workflow enhancements for IMSA-CMS/CMSAnalysis, addressing both signal and background paths. The work tightened function call structure, clarified parameter handling during function creation, ensured consistent channel naming, and added enhanced logging to streamline debugging. Background improvements focused on fit function creation and histogram loading to support robust fitting workflows. Together, these changes improve fitting reliability, enable faster issue diagnosis, and lay groundwork for future extensions.
November 2025
2 Commits • 1 Features
Nov 1, 2025In November 2025, delivered consolidated Higgs fitting workflow enhancements for IMSA-CMS/CMSAnalysis, addressing both signal and background paths. The work tightened function call structure, clarified parameter handling during function creation, ensured consistent channel naming, and added enhanced logging to streamline debugging. Background improvements focused on fit function creation and histogram loading to support robust fitting workflows. Together, these changes improve fitting reliability, enable faster issue diagnosis, and lay groundwork for future extensions.
October 2025
3 Commits • 1 Features
Oct 1, 2025October 2025 Monthly Summary for IMSA-CMS/CMSAnalysis: Delivered Dark Photon Analysis plotting and data-loading enhancements, enabling end-to-end Dark Photon workflows with clear labeling of signal, background, and data. The work improved plotting configurability and data handling, enhancing reproducibility and collaboration for DP studies.
3 Commits • 1 Features
Oct 1, 2025October 2025 Monthly Summary for IMSA-CMS/CMSAnalysis: Delivered Dark Photon Analysis plotting and data-loading enhancements, enabling end-to-end Dark Photon workflows with clear labeling of signal, background, and data. The work improved plotting configurability and data handling, enhancing reproducibility and collaboration for DP studies.
October 2025
September 2025
5 Commits • 2 Features
Sep 1, 2025Month: 2025-09 — Focused on delivering scalable Higgs histogram parameterization and enhancing DarkPhoton data handling to improve modeling fidelity and analysis throughput. No standalone bug fixes were required this month; several enhancements addressed robustness and resource efficiency across the IMSA-CMS/CMSAnalysis repo, with direct business value in faster, more reliable fits and easier maintenance.
September 2025
5 Commits • 2 Features
Sep 1, 2025Month: 2025-09 — Focused on delivering scalable Higgs histogram parameterization and enhancing DarkPhoton data handling to improve modeling fidelity and analysis throughput. No standalone bug fixes were required this month; several enhancements addressed robustness and resource efficiency across the IMSA-CMS/CMSAnalysis repo, with direct business value in faster, more reliable fits and easier maintenance.
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 — IMSA-CMS/CMSAnalysis: Implemented automated Higgs background fitting workflow and cross-year histogram aggregation to streamline background estimation, reducing manual steps and improving analysis readiness.
2 Commits • 1 Features
Aug 1, 2025August 2025 — IMSA-CMS/CMSAnalysis: Implemented automated Higgs background fitting workflow and cross-year histogram aggregation to streamline background estimation, reducing manual steps and improving analysis readiness.
August 2025
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 — IMSA-CMS/CMSAnalysis delivered a set of enhancements to Drell-Yan background fitting and EventDumpModule, aimed at improving accuracy, provenance, and traceability to strengthen the reliability of background modeling and downstream physics results. Key outcomes include starting the fit range at 50 to reduce low-statistics bias, updating output naming for mapped vs standard fits, enabling weighted fits with proper Sumw2 histogram error handling, and reconfiguring the EventDumpModule with filters/parameters to improve statistical precision and traceability. Commits: 098364a941148c7d7b52220ee6123e715dde999a; 150de5f3d5ba26aecbc5c4991a87ca4c870a5262.
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 — IMSA-CMS/CMSAnalysis delivered a set of enhancements to Drell-Yan background fitting and EventDumpModule, aimed at improving accuracy, provenance, and traceability to strengthen the reliability of background modeling and downstream physics results. Key outcomes include starting the fit range at 50 to reduce low-statistics bias, updating output naming for mapped vs standard fits, enabling weighted fits with proper Sumw2 histogram error handling, and reconfiguring the EventDumpModule with filters/parameters to improve statistical precision and traceability. Commits: 098364a941148c7d7b52220ee6123e715dde999a; 150de5f3d5ba26aecbc5c4991a87ca4c870a5262.
Activity
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Quality Metrics
Correctness80.6%
Maintainability80.0%
Architecture77.4%
Performance65.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++
Technical Skills
C++C++ ProgrammingC++ programmingData AnalysisData VisualizationDebuggingHigh Energy PhysicsParticle PhysicsPlottingROOTROOT FrameworkScientific Computingdata analysisstatistical modeling
Repositories Contributed To
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