bmad-sim/BeamTracking.jl
May 2025 – Dec 2025
6 Months active
Languages Used
BibTeXJuliaMakefileMarkdownPythonTOMLYAML
Technical Skills
CI/CDCondaDocumentationDocumentation DeploymentGitHub ActionsMyST
David Sagan
PROFILE
David Sagan
Over six months, Daniel S. contributed to the bmad-sim/BeamTracking.jl repository, developing eight features and addressing two bugs to advance particle beam simulation capabilities. He enhanced alignment and aperture tracking, implemented robust coordinate transformation utilities, and improved RF parameter handling, all while maintaining a strong focus on test coverage and code maintainability. Using Julia and C++ (via KernelAbstractions), Daniel refactored core simulation kernels, introduced quaternion-based alignment, and automated documentation deployment with Sphinx and MyST. His work improved simulation accuracy, reliability, and onboarding for contributors, demonstrating depth in scientific computing, numerical methods, and continuous integration practices throughout the project.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
43Total
Bugs
2
Commits
43
Features
8
Lines of code
3,505
Activity Months6
Your Network
136 peopleSame Organization
@cornell.edu126
Shared Repositories
10
Alex HeMember
CompatHelper JuliaMember
Eiad HamwiMember
eiad-hamwiMember
Joseph DevlinMember
Matt SignorelliMember
Matthew George SignorelliMember
ndwangMember
obeznosovMember
Work History
December 2025
8 Commits • 2 Features
Dec 1, 2025December 2025: Delivered key BeamTracking.jl enhancements focused on RF parameter handling, robustness for unsupported features, and test reliability. Improvements include an rf_omega routine, rf_phi0 handling with updated zero_phase validation, temporary error checks for CrabCavity and edge parameter usage, and strengthened beamline utilities tests (BeamTrackingBeamlinesExt). These changes enhance simulation accuracy, prevent runtime errors, and improve development and QA processes.
8 Commits • 2 Features
Dec 1, 2025December 2025: Delivered key BeamTracking.jl enhancements focused on RF parameter handling, robustness for unsupported features, and test reliability. Improvements include an rf_omega routine, rf_phi0 handling with updated zero_phase validation, temporary error checks for CrabCavity and edge parameter usage, and strengthened beamline utilities tests (BeamTrackingBeamlinesExt). These changes enhance simulation accuracy, prevent runtime errors, and improve development and QA processes.
December 2025
November 2025
7 Commits • 2 Features
Nov 1, 2025Month: 2025-11 — In BeamTracking.jl, delivered two high-impact features with clear business value and expanded testing, while maintaining a focus on reliability and performance. Key outcomes include improvements to particle tracking accuracy and speed through enhanced coordinate transformation routines and quaternion operations, and the introduction of bending elements with a broader testing framework to validate beamline alignment and kicker elements. No explicit major bug fixes documented for this period; several commits indicate stability-oriented tweaks and cleanup. Overall impact includes higher fidelity simulations, more robust validation workflows, and a solid foundation for future optimizations. Technologies demonstrated include Julia, advanced coordinate transforms, quaternion algebra, beamline modeling, and automated testing.
November 2025
7 Commits • 2 Features
Nov 1, 2025Month: 2025-11 — In BeamTracking.jl, delivered two high-impact features with clear business value and expanded testing, while maintaining a focus on reliability and performance. Key outcomes include improvements to particle tracking accuracy and speed through enhanced coordinate transformation routines and quaternion operations, and the introduction of bending elements with a broader testing framework to validate beamline alignment and kicker elements. No explicit major bug fixes documented for this period; several commits indicate stability-oriented tweaks and cleanup. Overall impact includes higher fidelity simulations, more robust validation workflows, and a solid foundation for future optimizations. Technologies demonstrated include Julia, advanced coordinate transforms, quaternion algebra, beamline modeling, and automated testing.
October 2025
4 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for bmad-sim/BeamTracking.jl: Focused on improving beam alignment transformation capabilities and tracking accuracy. Implemented and refactored coordinate transformation utilities to support concatenation, bending, translation, and rotation, with enhanced handling of alignment and misalignment using quaternion operations. Updated tests to validate the new implementations; all tests pass. No explicit bug fixes were reported this month; however, the changes reduce risk by improving correctness and reliability of alignment calculations. This work increases modeling fidelity for beamline design and simulation, enabling more reliable planning and faster iteration.
4 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for bmad-sim/BeamTracking.jl: Focused on improving beam alignment transformation capabilities and tracking accuracy. Implemented and refactored coordinate transformation utilities to support concatenation, bending, translation, and rotation, with enhanced handling of alignment and misalignment using quaternion operations. Updated tests to validate the new implementations; all tests pass. No explicit bug fixes were reported this month; however, the changes reduce risk by improving correctness and reliability of alignment calculations. This work increases modeling fidelity for beamline design and simulation, enabling more reliable planning and faster iteration.
October 2025
September 2025
10 Commits • 1 Features
Sep 1, 2025September 2025 focused on stabilizing and validating aperture tracking within BeamTracking.jl. Delivered Aperture Tracking Core Enhancements and Validation, introducing STATE_LOST_XXX constants, improved state handling, kernel refactoring, and expanded test coverage for rectangular/elliptical apertures. Standardized kernel naming and test infrastructure to ensure reliable particle-loss reporting, and added targeted tests (beamlines_aperture_test.jl, test_matrix) to validate end-to-end aperture behavior. Fixed time-related tests by updating the expected particle state to STATE_LOST_POS_X, increasing test determinism. Implemented a workaround for a FastGTPSA issue to improve test stability. These changes collectively improve accuracy of particle-loss reporting, reduce debugging time, and boost confidence in simulation results used for design and verification.
September 2025
10 Commits • 1 Features
Sep 1, 2025September 2025 focused on stabilizing and validating aperture tracking within BeamTracking.jl. Delivered Aperture Tracking Core Enhancements and Validation, introducing STATE_LOST_XXX constants, improved state handling, kernel refactoring, and expanded test coverage for rectangular/elliptical apertures. Standardized kernel naming and test infrastructure to ensure reliable particle-loss reporting, and added targeted tests (beamlines_aperture_test.jl, test_matrix) to validate end-to-end aperture behavior. Fixed time-related tests by updating the expected particle state to STATE_LOST_POS_X, increasing test determinism. Implemented a workaround for a FastGTPSA issue to improve test stability. These changes collectively improve accuracy of particle-loss reporting, reduce debugging time, and boost confidence in simulation results used for design and verification.
August 2025
5 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for bmad-sim/BeamTracking.jl: Delivered major enhancement to alignment and aperture tracking in particle beam simulations. Introduced new alignment/aperture tracking functionality, added modular support and kernel-based tracking, and reorganized the codebase for maintainability. Fixed a bug in AlignmentTracking state comparison and resolved minor path/import issues. All changes integrated with the universal tracking function and updated dependencies to ensure compatibility with the latest tracking framework. Result: more accurate simulations, faster iteration, and improved reliability for beamline design.
5 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for bmad-sim/BeamTracking.jl: Delivered major enhancement to alignment and aperture tracking in particle beam simulations. Introduced new alignment/aperture tracking functionality, added modular support and kernel-based tracking, and reorganized the codebase for maintainability. Fixed a bug in AlignmentTracking state comparison and resolved minor path/import issues. All changes integrated with the universal tracking function and updated dependencies to ensure compatibility with the latest tracking framework. Result: more accurate simulations, faster iteration, and improved reliability for beamline design.
August 2025
May 2025
9 Commits • 1 Features
May 1, 2025Monthly summary for 2025-05 for repo bmad-sim/BeamTracking.jl focused on delivering a robust documentation infrastructure and enabling self-serve access to users and contributors. Implemented a MyST-based documentation pipeline with Sphinx, integrated with Read the Docs, and automated deployment to GitHub Pages via CI workflows. This work standardizes documentation structure, improves onboarding for new contributors, and enhances external discoverability of BeamTracking.jl. No major bug fixes were recorded this month; key gains come from improved docs reliability, reduced maintenance burden, and faster documentation iteration cycles.
May 2025
9 Commits • 1 Features
May 1, 2025Monthly summary for 2025-05 for repo bmad-sim/BeamTracking.jl focused on delivering a robust documentation infrastructure and enabling self-serve access to users and contributors. Implemented a MyST-based documentation pipeline with Sphinx, integrated with Read the Docs, and automated deployment to GitHub Pages via CI workflows. This work standardizes documentation structure, improves onboarding for new contributors, and enhances external discoverability of BeamTracking.jl. No major bug fixes were recorded this month; key gains come from improved docs reliability, reduced maintenance burden, and faster documentation iteration cycles.
Activity
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Quality Metrics
Correctness87.2%
Maintainability85.6%
Architecture82.4%
Performance79.0%
AI Usage21.0%
Skills & Technologies
Programming Languages
BibTeXJuliaMakefileMarkdownPythonTOMLYAML
Technical Skills
Beam PhysicsC++ (via KernelAbstractions)CI/CDCode RefactoringCondaDebuggingDocumentationDocumentation DeploymentGitHub ActionsJuliaJulia DevelopmentKernel DevelopmentMySTNumerical MethodsNumerical Simulation
Repositories Contributed To
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