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
Davide Di Croce developed a robust toroidal magnetic field model for the paulgessinger/acts repository, focusing on simulation fidelity and reproducibility in ACTS-based workflows. He implemented the model using C++ with Biot-Savart calculations, providing Python bindings for flexible integration and parameter configuration. The solution included header-only C++ components, dual constructors, and CMake-based build integration with conditional compilation, ensuring minimal disruption to existing code. Davide also created end-to-end Python examples for validation and quick adoption in Geant4 simulations. His work demonstrated depth in C++ development, Python interoperability, and build system design, addressing realistic magnetic field modeling requirements.
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
341 peopleSame Organization
@cern.ch317
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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