JeffersonLab/coatjava
Oct 2024 – May 2025
5 Months active
Languages Used
Java
Technical Skills
C++Geometry CalculationKalman FilterPhysics SimulationCode RefactoringGeometry
efuchey
PROFILE
Efuchey
Emmanuel Fuchéy contributed to JeffersonLab/coatjava by engineering robust improvements to Kalman filter–based track reconstruction and detector simulation workflows. He enhanced the accuracy of hit positioning and trajectory calculations by refining geometry handling and implementing stereo angle corrections, Z-offset adjustments, and left-right hit disambiguation. Using C++ and Java, Emmanuel overhauled measurement and noise matrices, optimized covariance parameters, and introduced detailed diagnostics for validation and debugging. His work included refactoring KFitter usage for clarity, enabling advanced track finding algorithms, and improving simulation flag management. These changes deepened the reliability and flexibility of particle physics analyses, supporting both production and simulation environments.
Overall Statistics
Feature vs Bugs
86%Features
Repository Contributions
8Total
Bugs
1
Commits
8
Features
6
Lines of code
1,253
Activity Months5
Your Network
36 people
Work History
May 2025
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on JeffersonLab/coatjava. Delivered substantial improvements to the AHDC Kalman filter to enhance trajectory reconstruction and data quality for AHDC-based analyses. Implemented track path calculations and momentum at AHDC exit, added dE/dx estimates, and refactored KFitter usage for clarity. Introduced a new KFitter setup to improve accuracy of path and residual calculations, enabling more detailed particle trajectory information within AHDC. These changes streamline physics analyses, reduce post-processing effort, and establish a foundation for further detector-level enhancements.
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on JeffersonLab/coatjava. Delivered substantial improvements to the AHDC Kalman filter to enhance trajectory reconstruction and data quality for AHDC-based analyses. Implemented track path calculations and momentum at AHDC exit, added dE/dx estimates, and refactored KFitter usage for clarity. Introduced a new KFitter setup to improve accuracy of path and residual calculations, enabling more detailed particle trajectory information within AHDC. These changes streamline physics analyses, reduce post-processing effort, and establish a foundation for further detector-level enhancements.
May 2025
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for JeffersonLab/coatjava: Focused on enhancing robustness of AHDC track reconstruction within the Kalman filter. Implemented looping over all track candidates (not just the first) to improve accuracy, refined simulation flag handling, and ensured vertex constraint is properly initialized and managed to avoid nonsensical values and missing MC bank fetches when unavailable. These changes address issue #553 and contribute to more reliable AHDC operation in production and simulation.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for JeffersonLab/coatjava: Focused on enhancing robustness of AHDC track reconstruction within the Kalman filter. Implemented looping over all track candidates (not just the first) to improve accuracy, refined simulation flag handling, and ensured vertex constraint is properly initialized and managed to avoid nonsensical values and missing MC bank fetches when unavailable. These changes address issue #553 and contribute to more reliable AHDC operation in production and simulation.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for JeffersonLab/coatjava: Focused feature delivery around the ALERT Kalman filter with enhanced diagnostics and disambiguation, driven by a priority on tracking accuracy and maintainability. Delivered substantial Kalman filter enhancements, improved post-fit residuals, and introduced left-right hit disambiguation, complemented by code cleanup and parameter tuning.
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for JeffersonLab/coatjava: Focused feature delivery around the ALERT Kalman filter with enhanced diagnostics and disambiguation, driven by a priority on tracking accuracy and maintainability. Delivered substantial Kalman filter enhancements, improved post-fit residuals, and introduced left-right hit disambiguation, complemented by code cleanup and parameter tuning.
March 2025
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 (JeffersonLab/coatjava) delivered significant improvements to track reconstruction and track finding workflows, driven by a Kalman Filter overhaul and the enabling of established track finding methods in AHDCEngine. The work focused on improving physics performance, increasing developer flexibility for targeted debugging, and preparing for broader analyses.
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 (JeffersonLab/coatjava) delivered significant improvements to track reconstruction and track finding workflows, driven by a Kalman Filter overhaul and the enabling of established track finding methods in AHDCEngine. The work focused on improving physics performance, increasing developer flexibility for targeted debugging, and preparing for broader analyses.
October 2024
2 Commits • 1 Features
Oct 1, 2024In October 2024, delivered key accuracy improvements to Kalman filter–based reconstruction in JeffersonLab/coatjava and fixed a critical B-field sign issue, enhancing both hit-positioning and trajectory reliability. The work strengthens physics analysis fidelity, reduces systematic uncertainties, and improves validation workflows through debugging aids and clearer verification paths. All changes are traceable in commits for reproducibility and review.
2 Commits • 1 Features
Oct 1, 2024In October 2024, delivered key accuracy improvements to Kalman filter–based reconstruction in JeffersonLab/coatjava and fixed a critical B-field sign issue, enhancing both hit-positioning and trajectory reliability. The work strengthens physics analysis fidelity, reduces systematic uncertainties, and improves validation workflows through debugging aids and clearer verification paths. All changes are traceable in commits for reproducibility and review.
October 2024
Activity
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Quality Metrics
Correctness83.8%
Maintainability80.0%
Architecture81.2%
Performance65.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
C++Code RefactoringData AnalysisData ReconstructionDetector SimulationGeometryGeometry CalculationJavaKalman FilterParticle PhysicsPhysics ReconstructionPhysics SimulationSoftware EngineeringTrack Reconstruction
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