blackSwanCS/Higgs_collaboration_B
Jun 2025 – Jun 2025
1 Month active
Languages Used
Python
Technical Skills
Data AnalysisData VisualizationMachine LearningNumerical MethodsPythonPython Scripting
Benjamin Plumejeau
PROFILE
Benjamin Plumejeau
Benjamin Plumejeau developed a comprehensive TES Uncertainty Analysis and Score Histogram Shifting feature for the blackSwanCS/Higgs_collaboration_B repository. He refined the tes_fitter module to support tes_range-based fitting, enabling per-bin delta calculations and the generation of polynomial fitting coefficients. Using Python and scientific computing techniques, Benjamin implemented granular bin-by-bin uncertainty handling and shifted score distributions under varying TES scenarios. He also created plotting utilities to compare nominal and shifted histograms, supporting detailed data visualization. The work established a robust framework for systematic uncertainty analysis and laid the foundation for future JES uncertainty integration, demonstrating depth in statistical modeling and numerical methods.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
1
Lines of code
930
Activity Months1
Your Network
41 people
Work History
June 2025
7 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for blackSwanCS/Higgs_collaboration_B: Delivered a robust TES Uncertainty Analysis and Score Histogram Shifting feature. Refined the tes_fitter and integrated tes_range-based fitting, enabling per-bin delta calculations and generation of polynomial fitting coefficients. Implemented granular bin-by-bin uncertainty handling (loop over bins to compute delta S and Delta N) and shifted score distributions under varying TES scenarios. Developed plotting utilities to compare nominal vs shifted histograms, including a visualization for a chosen TES value. Finalized tes_fitter version for team stats and completed the final fit function, laying the groundwork for JES uncertainty analysis (placeholder).
7 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for blackSwanCS/Higgs_collaboration_B: Delivered a robust TES Uncertainty Analysis and Score Histogram Shifting feature. Refined the tes_fitter and integrated tes_range-based fitting, enabling per-bin delta calculations and generation of polynomial fitting coefficients. Implemented granular bin-by-bin uncertainty handling (loop over bins to compute delta S and Delta N) and shifted score distributions under varying TES scenarios. Developed plotting utilities to compare nominal vs shifted histograms, including a visualization for a chosen TES value. Finalized tes_fitter version for team stats and completed the final fit function, laying the groundwork for JES uncertainty analysis (placeholder).
June 2025
Activity
Loading activity data...
Quality Metrics
Correctness82.8%
Maintainability80.0%
Architecture80.0%
Performance62.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisData VisualizationMachine LearningNumerical MethodsPythonPython ScriptingScientific ComputingStatistical ModelingSystematic Uncertainty Analysis
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline