paulgessinger/acts
Jan 2026 – Jan 2026
1 Month active
Languages Used
C++Python
Technical Skills
C++ developmentCMake integrationGeant4 simulationPython developmentUnit testing
Davide Di Croce
PROFILE
Davide Di Croce
Developed a robust toroidal magnetic field model for the paulgessinger/acts repository, focusing on simulation fidelity and reproducibility within ACTS-based workflows. The implementation used C++ and Python, leveraging Biot-Savart law to enable configurable parameters such as radii, current, and coil count. Python bindings were added for seamless integration, and the feature was incorporated into the build system using CMake with conditional compilation to maintain modularity. End-to-end examples in Python demonstrated usage and validation, supporting quick adoption in GeoModel and Geant4 simulations. The work emphasized clean integration, flexible configuration, and realistic modeling for efficient evaluation of magnetic field configurations.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
3,149
Activity Months1
Your Network
365 peopleSame Organization
@cern.ch341
Work History
January 2026
1 Commits • 1 Features
Jan 1, 2026Monthly performance summary for 2026-01 focused on delivering a robust toroidal magnetic field model for the ACTS-based suite, with Python bindings and end-to-end example coverage. The work emphasizes business value (simulation fidelity, reproducibility, and quicker evaluation of magnetic configurations) and technical achievement (clean integration into build and examples, with configurable parameters).
1 Commits • 1 Features
Jan 1, 2026Monthly performance summary for 2026-01 focused on delivering a robust toroidal magnetic field model for the ACTS-based suite, with Python bindings and end-to-end example coverage. The work emphasizes business value (simulation fidelity, reproducibility, and quicker evaluation of magnetic configurations) and technical achievement (clean integration into build and examples, with configurable parameters).
January 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++ developmentCMake integrationGeant4 simulationPython developmentUnit testing
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