IMSA-CMS/CMSAnalysis
Oct 2024 – May 2025
3 Months active
Languages Used
C++txt
Technical Skills
C++Data AnalysisObject-Oriented ProgrammingSystematic UncertaintiesC++ DevelopmentPlotting
Maya Kannan
PROFILE
Maya Kannan
During a three-month period, Muthu Kannan engineered a robust systematic uncertainty framework within the IMSA-CMS/CMSAnalysis repository, focusing on scalable and maintainable solutions for high energy physics data analysis. He introduced new C++ classes to aggregate and propagate multiple systematic uncertainties, refactored analysis and plotting components to support both rate-based and shape-based variations, and migrated cross-section data management from static files to dynamic integration. Leveraging C++, the ROOT framework, and object-oriented programming, his work improved the reliability and reproducibility of histogram-based analyses, reduced manual maintenance, and positioned the analysis pipeline for future scalability and integration with evolving data sources.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
4
Lines of code
4,134
Activity Months3
Your Network
34 people
Work History
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary for IMSA-CMS/CMSAnalysis. Delivered a major overhaul of systematic uncertainty handling in the analysis pipeline and began migrating to integrated/dynamic cross-section data management. This work included refactoring analysis code, updating process definitions and file paths, and removing the static crossSections.txt to enable dynamic cross-section usage. The changes improve uncertainty propagation in plotting and data handling, increase pipeline reliability, and reduce maintenance overhead.
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary for IMSA-CMS/CMSAnalysis. Delivered a major overhaul of systematic uncertainty handling in the analysis pipeline and began migrating to integrated/dynamic cross-section data management. This work included refactoring analysis code, updating process definitions and file paths, and removing the static crossSections.txt to enable dynamic cross-section usage. The changes improve uncertainty propagation in plotting and data handling, increase pipeline reliability, and reduce maintenance overhead.
May 2025
November 2024
8 Commits • 2 Features
Nov 1, 2024Month: 2024-11 — IMSA-CMS/CMSAnalysis Delivered end-to-end enhancements for systematic uncertainties in the Higgs analysis, including framework-level uncertainty handling, rate-based variations, and shape-based uncertainties. Refactored plotting to rely on HiggsCompleteAnalysis, added RateSystematic, and updated plot/config logic to better propagate uncertainties. Implemented a ShapeSystematic class to support shape-based variations with high/low adjustments and related code cleanups. Enhanced error handling in SuperImpose and plotting to reduce failures and improve robustness. These changes enable more reliable uncertainty propagation, faster scenario evaluation, and clearer, more reproducible histograms for physics results.
November 2024
8 Commits • 2 Features
Nov 1, 2024Month: 2024-11 — IMSA-CMS/CMSAnalysis Delivered end-to-end enhancements for systematic uncertainties in the Higgs analysis, including framework-level uncertainty handling, rate-based variations, and shape-based uncertainties. Refactored plotting to rely on HiggsCompleteAnalysis, added RateSystematic, and updated plot/config logic to better propagate uncertainties. Implemented a ShapeSystematic class to support shape-based variations with high/low adjustments and related code cleanups. Enhanced error handling in SuperImpose and plotting to reduce failures and improve robustness. These changes enable more reliable uncertainty propagation, faster scenario evaluation, and clearer, more reproducible histograms for physics results.
October 2024
2 Commits • 1 Features
Oct 1, 2024Month: 2024-10. This period focused on delivering a robust systemic uncertainty framework within IMSA-CMS/CMSAnalysis, laying groundwork for cohesive handling of multiple systematics and improving the reliability of histogram-based analyses. The work enhances scalability, maintainability, and overall analytic accuracy by centralizing systematics aggregation and application.
2 Commits • 1 Features
Oct 1, 2024Month: 2024-10. This period focused on delivering a robust systemic uncertainty framework within IMSA-CMS/CMSAnalysis, laying groundwork for cohesive handling of multiple systematics and improving the reliability of histogram-based analyses. The work enhances scalability, maintainability, and overall analytic accuracy by centralizing systematics aggregation and application.
October 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture76.6%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++txt
Technical Skills
C++C++ DevelopmentData AnalysisHigh Energy PhysicsObject-Oriented ProgrammingPlottingROOT FrameworkSystematic UncertaintiesSystematic Uncertainty Analysis
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