mg5amcnlo/mg5amcnlo
Jan 2025 – Jul 2025
4 Months active
Languages Used
FortranPythonTextgnuplotperltext
Technical Skills
Computational PhysicsEvent GenerationFortran ProgrammingHigh Energy PhysicsNLO CalculationsPython Scripting
Rikkert
PROFILE
Rikkert
Rikkert Frederix contributed to the mg5amcnlo/mg5amcnlo repository by developing and refining features for next-to-leading order (NLO) event generation in high energy physics. He implemented flavour-aware biasing controls and stabilized weight handling, enabling more accurate and flexible event simulations. Rikkert introduced a grid-based interpolation method for alphaS calculations in FxFx merging, optimizing performance and reducing computation time. He improved documentation clarity and enhanced the robustness of histogram plotting and testing workflows. Working primarily in Fortran and Python, Rikkert also addressed critical bugs affecting merging accuracy, demonstrating a thorough approach to both feature development and code reliability within scientific computing.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
11Total
Bugs
3
Commits
11
Features
3
Lines of code
838
Activity Months4
Work History
July 2025
2 Commits
Jul 1, 2025In 2025-07, delivered critical FxFx merging stability improvements for mg5amcnlo/mg5amcnlo. Fixed two bugs: prefactor computation in driver_mintMC.f and jet clustering scale in cuts.f (commits 353703a8698106b580263d959ca566b70bcaa348). Also published v3.6.4 release notes documenting fixes for negatively weighted events and high-pT jets (commit 6144ee9a4cd92becfca8758465cb0c156fdab84a). Targeted validation confirmed improved FxFx merging accuracy and stability. Updated UpdateNotes.txt as part of the release process.
2 Commits
Jul 1, 2025In 2025-07, delivered critical FxFx merging stability improvements for mg5amcnlo/mg5amcnlo. Fixed two bugs: prefactor computation in driver_mintMC.f and jet clustering scale in cuts.f (commits 353703a8698106b580263d959ca566b70bcaa348). Also published v3.6.4 release notes documenting fixes for negatively weighted events and high-pT jets (commit 6144ee9a4cd92becfca8758465cb0c156fdab84a). Targeted validation confirmed improved FxFx merging accuracy and stability. Updated UpdateNotes.txt as part of the release process.
July 2025
March 2025
3 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on documentation clarity and code robustness. Key outcomes include a documentation update clarifying that alpha_S grid usage in NLO calculations applies only when LHAPDF is not used, and histogram plotting/test robustness improvements with updated tests. These changes improve user guidance, reliability, and test integrity without altering functionality.
March 2025
3 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on documentation clarity and code robustness. Key outcomes include a documentation update clarifying that alpha_S grid usage in NLO calculations applies only when LHAPDF is not used, and histogram plotting/test robustness improvements with updated tests. These changes improve user guidance, reliability, and test integrity without altering functionality.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on performance optimization and business value. Key features delivered: AlphaS Grid Interpolation for FxFx Computations. Major bugs fixed: none reported this period. Overall impact: introduced a pre-computed interpolation grid (alphas_from_grids) to compute alphaS for FxFx processes, replacing direct numerical evaluation with linear interpolation across energy scales, leading to faster Sudakov-related computations and higher throughput for FxFx event generation. Technologies/skills demonstrated: grid-based interpolation, energy-scale interpolation, and performance optimization within the MG5_aMC workflow. Business value: reduced compute time per FxFx calculation, enabling higher simulation throughput and better resource utilization across large-scale analyses.
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on performance optimization and business value. Key features delivered: AlphaS Grid Interpolation for FxFx Computations. Major bugs fixed: none reported this period. Overall impact: introduced a pre-computed interpolation grid (alphas_from_grids) to compute alphaS for FxFx processes, replacing direct numerical evaluation with linear interpolation across energy scales, leading to faster Sudakov-related computations and higher throughput for FxFx event generation. Technologies/skills demonstrated: grid-based interpolation, energy-scale interpolation, and performance optimization within the MG5_aMC workflow. Business value: reduced compute time per FxFx calculation, enabling higher simulation throughput and better resource utilization across large-scale analyses.
February 2025
January 2025
5 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on delivering fatigue-free momentum in NLO event generation through flavour-aware biasing. Work completed in mg5amcnlo/mg5amcnlo strengthened the NLO workflow by enabling controlled flavour biasing and ensuring weight consistency across event generation, with targeted fixes to multi-file weight calculations.
January 2025
5 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on delivering fatigue-free momentum in NLO event generation through flavour-aware biasing. Work completed in mg5amcnlo/mg5amcnlo strengthened the NLO workflow by enabling controlled flavour biasing and ensuring weight consistency across event generation, with targeted fixes to multi-file weight calculations.
Activity
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Quality Metrics
Correctness87.2%
Maintainability85.4%
Architecture80.8%
Performance76.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
FortranPythonTextgnuplotperltext
Technical Skills
Computational PhysicsData VisualizationDocumentationEvent GenerationFortran ProgrammingHigh Energy PhysicsMonte Carlo MethodsNLO CalculationsNumerical AnalysisPerformance OptimizationPlotting LibrariesPython ScriptingScientific ComputingScriptingTesting
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