mg5amcnlo/mg5amcnlo
Oct 2024 – Jan 2026
16 Months active
Languages Used
PythonFortranMakefileShellMarkdownTextBashC++
Technical Skills
Build AutomationScriptingBackend DevelopmentBug FixBug FixingBuild Systems
Olivier Mattelaer
PROFILE
Olivier Mattelaer
Over 16 months, contributed to the mg5amcnlo/mg5amcnlo repository by developing and maintaining advanced features for high-energy physics simulations. Delivered 32 features and resolved 72 bugs, focusing on robust event generation, cross-platform build automation, and improved configuration management. Leveraged Python, Fortran, and C++ to enhance code generation, testing infrastructure, and compatibility with evolving toolchains. Applied skills in backend development, CI/CD, and scientific computing to streamline workflows, increase reliability, and support new physics models. Emphasized maintainability through code refactoring, error handling, and documentation, enabling smoother deployments and more accurate simulations for both users and developers in production environments.
Overall Statistics
Feature vs Bugs
31%Features
Repository Contributions
179Total
Bugs
72
Commits
179
Features
32
Lines of code
18,414
Activity Months16
Your Network
20 peopleShared Repositories
14
Work History
January 2026
5 Commits • 2 Features
Jan 1, 2026January 2026 focused on stabilizing and expanding the mg5amcnlo/mg5amcnlo platform, with clear business value through improved configurability, release readiness, and feature communications. Deliverables centered on robust configuration handling, release-quality fixes, and up-to-date release notes to enable smoother user onboarding and advanced usage scenarios.
5 Commits • 2 Features
Jan 1, 2026January 2026 focused on stabilizing and expanding the mg5amcnlo/mg5amcnlo platform, with clear business value through improved configurability, release readiness, and feature communications. Deliverables centered on robust configuration handling, release-quality fixes, and up-to-date release notes to enable smoother user onboarding and advanced usage scenarios.
January 2026
December 2025
15 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on key deliverables, reliability, and impact across MadGraph workflows. 1) Key features delivered: - MadSpin enhancements for on-shell production and decay width calculations: Improved on-shell handling and cumulative branching ratio calculations to increase the accuracy of decay width computations when multiple decays are involved. (Commits: a68bb3472f10ede27738001fad345059bd53ac28; e55fdc49693221fc17213516ae2d57bd50696533) - Performance, tests, and tooling improvements: Added pigz-based data processing tests, updated test configurations, and refined command interfaces and help utilities to improve test reliability and developer experience. (Commits: 1334d5d3f64353507a429670b5bab13191468b41; 10b62101c9ed54aecab0201dac0f844538a498ab; 5ec8ac4e8309d9203afa314486279c50e451af87; 430cc9d9bd10cc814b3e99f036097b7d44618366; 7e0be87c6845709c7a47453becc53b9987f3ddbd) - Core robustness and correctness fixes for MadGraph event generation: A set of stability and correctness fixes across event generation, storage, amplitude normalization, and import handling, including safer directory creation, improved error handling, normalization consistency, and removal of problematic function duplicates. (Commits: 1f6f221338bfe407175ab9100465421651d47b09; 68719d56d48efc668c094f5bf502c124d06570af; a84e32e1a8fd608a351e8e7455975f4c1c477eea; 67dae0e7310a0acf1fd83f21f6de5835f5409a12; ea103e6f0f08d59d8b2d5ce41ae10968f0dcdc4e; 87cf0dedc41d6001ac89f90700f1b90d3b1e6ba7; 94d0163a8f7d31352f016d2329bc7d11bea364d6; 04a4062c4431cea099a170192ab2d435fc6d60bf) 2) Major bugs fixed: - Core robustness and correctness across MadGraph workflows, including safer directory creation, improved error handling, normalization consistency, and prevention of duplicate function references in templates and imports. This reduces runtime errors and unhandled failure modes in production and CI. 3) Overall impact and accomplishments: - Increased stability and reliability of MadGraph/MadSpin workflows in production, with measurable improvements in event generation correctness and import handling. Enhanced test coverage and tooling contribute to faster iterations and safer feature delivery, ultimately reducing downstream debugging time for users and enabling more accurate physics studies. 4) Technologies/skills demonstrated: - Deep domain expertise in MadGraph/MadSpin event generation, BR/width calculations, and NLO EW considerations. - Strong emphasis on testing and tooling: pigz-based processing, test configuration management, and CLI/interface improvements. - Proactive code quality improvements: error handling, normalization, import handling, and duplication avoidance, reflecting robust software craftsmanship and maintainability.
December 2025
15 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on key deliverables, reliability, and impact across MadGraph workflows. 1) Key features delivered: - MadSpin enhancements for on-shell production and decay width calculations: Improved on-shell handling and cumulative branching ratio calculations to increase the accuracy of decay width computations when multiple decays are involved. (Commits: a68bb3472f10ede27738001fad345059bd53ac28; e55fdc49693221fc17213516ae2d57bd50696533) - Performance, tests, and tooling improvements: Added pigz-based data processing tests, updated test configurations, and refined command interfaces and help utilities to improve test reliability and developer experience. (Commits: 1334d5d3f64353507a429670b5bab13191468b41; 10b62101c9ed54aecab0201dac0f844538a498ab; 5ec8ac4e8309d9203afa314486279c50e451af87; 430cc9d9bd10cc814b3e99f036097b7d44618366; 7e0be87c6845709c7a47453becc53b9987f3ddbd) - Core robustness and correctness fixes for MadGraph event generation: A set of stability and correctness fixes across event generation, storage, amplitude normalization, and import handling, including safer directory creation, improved error handling, normalization consistency, and removal of problematic function duplicates. (Commits: 1f6f221338bfe407175ab9100465421651d47b09; 68719d56d48efc668c094f5bf502c124d06570af; a84e32e1a8fd608a351e8e7455975f4c1c477eea; 67dae0e7310a0acf1fd83f21f6de5835f5409a12; ea103e6f0f08d59d8b2d5ce41ae10968f0dcdc4e; 87cf0dedc41d6001ac89f90700f1b90d3b1e6ba7; 94d0163a8f7d31352f016d2329bc7d11bea364d6; 04a4062c4431cea099a170192ab2d435fc6d60bf) 2) Major bugs fixed: - Core robustness and correctness across MadGraph workflows, including safer directory creation, improved error handling, normalization consistency, and prevention of duplicate function references in templates and imports. This reduces runtime errors and unhandled failure modes in production and CI. 3) Overall impact and accomplishments: - Increased stability and reliability of MadGraph/MadSpin workflows in production, with measurable improvements in event generation correctness and import handling. Enhanced test coverage and tooling contribute to faster iterations and safer feature delivery, ultimately reducing downstream debugging time for users and enabling more accurate physics studies. 4) Technologies/skills demonstrated: - Deep domain expertise in MadGraph/MadSpin event generation, BR/width calculations, and NLO EW considerations. - Strong emphasis on testing and tooling: pigz-based processing, test configuration management, and CLI/interface improvements. - Proactive code quality improvements: error handling, normalization, import handling, and duplication avoidance, reflecting robust software craftsmanship and maintainability.
November 2025
40 Commits • 7 Features
Nov 1, 2025November 2025 focused on delivering cross-platform build and integration improvements for mg5amcnlo/mg5amcnlo, with major progress on F2PY integration and dynamic libraries, and improved Python version compatibility. Enabled richer physics data handling through Lorentz geometry enhancements and access to nhel information. Strengthened reliability and maintenance via parallel execution fixes, CI stability enhancements, and expanded build scaffolding. Reduced log noise and stabilized key dependencies to support smoother deployments and faster debugging.
40 Commits • 7 Features
Nov 1, 2025November 2025 focused on delivering cross-platform build and integration improvements for mg5amcnlo/mg5amcnlo, with major progress on F2PY integration and dynamic libraries, and improved Python version compatibility. Enabled richer physics data handling through Lorentz geometry enhancements and access to nhel information. Strengthened reliability and maintenance via parallel execution fixes, CI stability enhancements, and expanded build scaffolding. Reduced log noise and stabilized key dependencies to support smoother deployments and faster debugging.
November 2025
October 2025
3 Commits • 2 Features
Oct 1, 2025In Oct 2025, the mg5amcnlo/mg5amcnlo project delivered targeted features and fixes that strengthen batch event processing reliability, warp-level performance, and release readiness. Key outcomes include a robust color assignment fix for batched event generation, a warp-based processing optimization with improved I/O handling and configuration management, and the 3.6.5 release with NLO syntax error handling and a new LO compile command, plus accompanying versioning and release notes updates. These efforts reduced runtime errors, improved stability, and streamlined deployment and verification processes across the codebase.
October 2025
3 Commits • 2 Features
Oct 1, 2025In Oct 2025, the mg5amcnlo/mg5amcnlo project delivered targeted features and fixes that strengthen batch event processing reliability, warp-level performance, and release readiness. Key outcomes include a robust color assignment fix for batched event generation, a warp-based processing optimization with improved I/O handling and configuration management, and the 3.6.5 release with NLO syntax error handling and a new LO compile command, plus accompanying versioning and release notes updates. These efforts reduced runtime errors, improved stability, and streamlined deployment and verification processes across the codebase.
September 2025
10 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for mg5amcnlo/mg5amcnlo focused on stability, build tooling, and test reliability. Key feature delivered: UI 'compile' command to build the current directory and related components with run configuration handling. Major bugs fixed across MadSpin activation, ALOHA vector handling, RAMBO tests, color algebra, and template generation. These changes improved run-to-run consistency, export-format compatibility, and overall reliability in LHE merging, vector operations, and test suites. Release metadata updated to reflect the current state; Python codebase cleanup (raw strings for banner regex) and vector config gating ensured that Golem templates respect vector_size. Demonstrates strengths in Python tooling, test automation, build processes, and release management. Business value includes reduced manual steps, fewer failed runs, faster iteration, and clearer release state.
10 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for mg5amcnlo/mg5amcnlo focused on stability, build tooling, and test reliability. Key feature delivered: UI 'compile' command to build the current directory and related components with run configuration handling. Major bugs fixed across MadSpin activation, ALOHA vector handling, RAMBO tests, color algebra, and template generation. These changes improved run-to-run consistency, export-format compatibility, and overall reliability in LHE merging, vector operations, and test suites. Release metadata updated to reflect the current state; Python codebase cleanup (raw strings for banner regex) and vector config gating ensured that Golem templates respect vector_size. Demonstrates strengths in Python tooling, test automation, build processes, and release management. Business value includes reduced manual steps, fewer failed runs, faster iteration, and clearer release state.
September 2025
August 2025
4 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for mg5amcnlo/mg5amcnlo focused on stabilizing NLO scans and expanding UFO modeling capabilities to support more flexible physics definitions. Key fixes and enhancements were implemented to improve reliability, compatibility with toolchains, and modeling workflows.
August 2025
4 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for mg5amcnlo/mg5amcnlo focused on stabilizing NLO scans and expanding UFO modeling capabilities to support more flexible physics definitions. Key fixes and enhancements were implemented to improve reliability, compatibility with toolchains, and modeling workflows.
July 2025
11 Commits • 2 Features
Jul 1, 2025July 2025: mg5amcnlo/mg5amcnlo delivered cross-compiler reliability improvements, correctness fixes, and internal build/test enhancements that strengthen stability, performance, and physics accuracy. Focus areas included (1) feature refinements to color algebra for efficiency and correctness; (2) critical bug fixes across compiler compatibility, helicity propagation, and alpha_s logic; and (3) tightened test/build infrastructure for I/O tests and Python extension builds (f2py), reducing CI friction and deployment risk.
11 Commits • 2 Features
Jul 1, 2025July 2025: mg5amcnlo/mg5amcnlo delivered cross-compiler reliability improvements, correctness fixes, and internal build/test enhancements that strengthen stability, performance, and physics accuracy. Focus areas included (1) feature refinements to color algebra for efficiency and correctness; (2) critical bug fixes across compiler compatibility, helicity propagation, and alpha_s logic; and (3) tightened test/build infrastructure for I/O tests and Python extension builds (f2py), reducing CI friction and deployment risk.
July 2025
June 2025
12 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for mg5amcnlo/mg5amcnlo focused on delivering robust features, stabilizing the release, and improving user and developer productivity. Key features and improvements extend interoperability with external tools (Pythia8, plugins), enhance robustness of event generation workflows, and improve testing and release hygiene. The work emphasizes business value through smoother integrations, fewer run-time crashes, and clearer release documentation.
June 2025
12 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for mg5amcnlo/mg5amcnlo focused on delivering robust features, stabilizing the release, and improving user and developer productivity. Key features and improvements extend interoperability with external tools (Pythia8, plugins), enhance robustness of event generation workflows, and improve testing and release hygiene. The work emphasizes business value through smoother integrations, fewer run-time crashes, and clearer release documentation.
May 2025
8 Commits • 1 Features
May 1, 2025May 2025 monthly summary for mg5amcnlo/mg5amcnlo: delivered robustness fixes for MadSpin, implemented empty events pruning with enhanced diagnostics, corrected asymmetric beam scale propagation, improved Fortran initialization safety, and GCC15 compatibility improvements, contributing to a stable release and clearer diagnostics. Business value includes more reliable event generation (decayed samples correctly merged), safer runtime behavior, and smoother builds across compilers.
8 Commits • 1 Features
May 1, 2025May 2025 monthly summary for mg5amcnlo/mg5amcnlo: delivered robustness fixes for MadSpin, implemented empty events pruning with enhanced diagnostics, corrected asymmetric beam scale propagation, improved Fortran initialization safety, and GCC15 compatibility improvements, contributing to a stable release and clearer diagnostics. Business value includes more reliable event generation (decayed samples correctly merged), safer runtime behavior, and smoother builds across compilers.
May 2025
April 2025
21 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary focusing on key accomplishments, business value, and technical achievements for mg5amcnlo/mg5amcnlo. The month delivered core feature enhancements, major stability fixes, and improvements in model coverage, plotting, tests, and gridpack/PDF handling. These changes reduce production risk, improve numerical accuracy, and broaden the applicability of the generator in production pipelines.
April 2025
21 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary focusing on key accomplishments, business value, and technical achievements for mg5amcnlo/mg5amcnlo. The month delivered core feature enhancements, major stability fixes, and improvements in model coverage, plotting, tests, and gridpack/PDF handling. These changes reduce production risk, improve numerical accuracy, and broaden the applicability of the generator in production pipelines.
March 2025
15 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on business value and technical achievements. Delivered reliable gridpack workflows, improved event processing, hardened numerical stability, and strengthened CI/release processes. The work reduced manual maintenance, increased reproducibility in production, and improved overall resilience of the workflow.
15 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for mg5amcnlo/mg5amcnlo focusing on business value and technical achievements. Delivered reliable gridpack workflows, improved event processing, hardened numerical stability, and strengthened CI/release processes. The work reduced manual maintenance, increased reproducibility in production, and improved overall resilience of the workflow.
March 2025
February 2025
15 Commits • 3 Features
Feb 1, 2025February 2025 monthly summary for mg5amcnlo/mg5amcnlo: concise articulation of delivered features, bug fixes, impact, and skills demonstrated. Focus on business value and technical achievements. Highlights include an upgrade to PNG image output, stability and capability improvements in cross-language code generation for C++/Fortran exporters, a new Fortran template enabling Python integration, enhanced input precision via floating-point shortcuts on the run interface, a fix to dressed lepton processing, and CI/test infrastructure stabilization to ensure reliable automated testing and release readiness.
February 2025
15 Commits • 3 Features
Feb 1, 2025February 2025 monthly summary for mg5amcnlo/mg5amcnlo: concise articulation of delivered features, bug fixes, impact, and skills demonstrated. Focus on business value and technical achievements. Highlights include an upgrade to PNG image output, stability and capability improvements in cross-language code generation for C++/Fortran exporters, a new Fortran template enabling Python integration, enhanced input precision via floating-point shortcuts on the run interface, a fix to dressed lepton processing, and CI/test infrastructure stabilization to ensure reliable automated testing and release readiness.
January 2025
6 Commits • 1 Features
Jan 1, 2025January 2025 summary for mg5amcnlo/mg5amcnlo focusing on business value and technical accomplishments. Delivered user-facing FD Gauge functionality with accompanying documentation and initial release notes, aligning with relevant publications to support scientific usage and adoption. Improved installation reliability by fixing PATH guidance to ensure the bin directory is exported, reducing setup friction for new users. Strengthened runtime robustness and debuggability across the codebase: multiprocess debugging now emits tracebacks to both a debug file and console, and banner handling was hardened to avoid runtime errors when iterating dynamic keys. Enhanced Aloha parsing resilience by gracefully handling missing expand methods, preventing item-level failures during parsing. Cleaned up UPC photon PDF handling to remove redundancy and improve accuracy for non-factorized PDFs, and adjusted sde_strategy2 to prevent negative weights, boosting numerical stability and simulation correctness. These changes collectively reduce user downtime, improve result reproducibility, and demonstrate strong Python engineering practices.
6 Commits • 1 Features
Jan 1, 2025January 2025 summary for mg5amcnlo/mg5amcnlo focusing on business value and technical accomplishments. Delivered user-facing FD Gauge functionality with accompanying documentation and initial release notes, aligning with relevant publications to support scientific usage and adoption. Improved installation reliability by fixing PATH guidance to ensure the bin directory is exported, reducing setup friction for new users. Strengthened runtime robustness and debuggability across the codebase: multiprocess debugging now emits tracebacks to both a debug file and console, and banner handling was hardened to avoid runtime errors when iterating dynamic keys. Enhanced Aloha parsing resilience by gracefully handling missing expand methods, preventing item-level failures during parsing. Cleaned up UPC photon PDF handling to remove redundancy and improve accuracy for non-factorized PDFs, and adjusted sde_strategy2 to prevent negative weights, boosting numerical stability and simulation correctness. These changes collectively reduce user downtime, improve result reproducibility, and demonstrate strong Python engineering practices.
January 2025
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for mg5amcnlo/mg5amcnlo. Focused on delivering Python 3.12 compatibility for matrix element generation and hardening fermion flow validation with form-factors to improve robustness in symbolic expressions. These changes ensure compatibility with modern Python environments and reduce runtime errors in simulations.
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for mg5amcnlo/mg5amcnlo. Focused on delivering Python 3.12 compatibility for matrix element generation and hardening fermion flow validation with form-factors to improve robustness in symbolic expressions. These changes ensure compatibility with modern Python environments and reduce runtime errors in simulations.
November 2024
11 Commits • 1 Features
Nov 1, 2024November 2024 (mg5amcnlo/mg5amcnlo) delivered targeted stability, safety, and compatibility improvements across the NLO workflow, build/run environments, Python 3.13 support, and automatic configuration behavior. The work reduces operational risk, accelerates reliable deployments, and strengthens the production readiness of NLO calculations and template usage.
11 Commits • 1 Features
Nov 1, 2024November 2024 (mg5amcnlo/mg5amcnlo) delivered targeted stability, safety, and compatibility improvements across the NLO workflow, build/run environments, Python 3.13 support, and automatic configuration behavior. The work reduces operational risk, accelerates reliable deployments, and strengthens the production readiness of NLO calculations and template usage.
November 2024
October 2024
1 Commits • 1 Features
Oct 1, 2024Oct 2024 mg5amcnlo/mg5amcnlo: Key feature delivered is centralized offline installer link management by refactoring the download logic to pull URLs from a single central configuration for Collier and Ninja. Removed a tarball-version test as part of centralization. Major bugs fixed: none reported this month. Impact: improves maintainability, reduces duplication, and accelerates tool updates across environments; aligns with configuration-driven deployment practices. Technologies/skills demonstrated: Python scripting/refactoring, configuration management, and environment/tool deployment automation.
October 2024
1 Commits • 1 Features
Oct 1, 2024Oct 2024 mg5amcnlo/mg5amcnlo: Key feature delivered is centralized offline installer link management by refactoring the download logic to pull URLs from a single central configuration for Collier and Ninja. Removed a tarball-version test as part of centralization. Major bugs fixed: none reported this month. Impact: improves maintainability, reduces duplication, and accelerates tool updates across environments; aligns with configuration-driven deployment practices. Technologies/skills demonstrated: Python scripting/refactoring, configuration management, and environment/tool deployment automation.
Activity
Loading activity data...
Quality Metrics
Correctness85.2%
Maintainability83.8%
Architecture78.2%
Performance73.2%
AI Usage20.6%
Skills & Technologies
Programming Languages
BashC++DatFortranMakefileMarkdownNonePerlPythonShell
Technical Skills
Acceptance TestingAlgorithm OptimizationBackend DevelopmentBug FixBug FixingBuild AutomationBuild SystemBuild SystemsBuild system managementC++C++ DevelopmentC++ integrationC/C++ integrationCI/CDCode Analysis
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline