May 2025 performance summary focusing on feature delivery, bug fixes, and stability improvements across two MaCh3 repositories. Delivered user-visible plotting enhancements for acceptance and projection titles, modernized the build system for maintainability and reliability, and expanded the physics dataset with additional particle masses. Also completed targeted bug fixes and code-cleanup that reduce technical debt and improve data analysis workflows. Overall, these efforts increased analysis clarity, reduced build-related risk, and broadened dataset coverage for downstream physics studies.

April 2025 focused on expanding projection analytics, enhancing MaCh3_DUNE analysis, and tightening build configurability, while pruning legacy code to reduce maintenance. Key features delivered: - Projections core enhancements: particle-level histograms, particle-property histogram generation, refined binning, data-structure improvements, projection configurations, and support for 1D/2D histograms with ROOT output. - NDGAr-specific projection support: build options and modularization with macro toggles to include/exclude NDGAr code paths. - MaCh3_DUNE analysis enhancements: new kinematic variables and plotting to enable richer histograms of momentum, transverse momentum, and related quantities. - Build/configurability: added CMake option to build either NDGAr or all other samplepdf classes. - Codebase cleanup: removed Projections functionality to streamline maintenance (src deleted). Major bugs fixed: - Resolved particle-level histogram generation bugs and ensured correct 1D/2D histogram behavior. - Stabilized DUNEFactory integration. - Fixed plotting/workflow issues in MaCh3_DUNE analyses. Overall impact and accomplishments: - Significantly enhanced granularity and reliability of projection-based analytics, enabling deeper physics insights and faster iteration for MaCh3_DUNE analyses. - Improved build-time configurability and maintainability through modularization and NDGAr-focused paths. - Reduced technical debt by removing obsolete Projections code and standardizing conventions across the project. Technologies/skills demonstrated: - C++/ROOT histogram pipelines, event-level kinematic selections, and plotting backends. - CMake-based build customization and macro-driven code paths for NDGAr vs non-NDGAr workflows. - Code modularization and selective compilation strategies, with performance-oriented refactors (e.g., pow() optimizations).

March 2025 (2025-03) Monthly Summary for DUNE/MaCh3_DUNE Key features delivered: - 2D projection histograms and NDGAr sample integration: enables 2D histograms for projections and updates NDGAr sample usability; includes refactoring ProjectionVariable for multi-var strings and 2D plotting support. Commits: 6f341aab605eb4360fe240ee7bdad58168773d98; 681b406b759a930b28a4672c23c646d7f9b8d556. - NDGAr particle acceptance logic and kinematic variable calculations: adds particle acceptance criteria logic and detailed kinematic variable calculations, including particlevar structure and robust IsParticleAccepted function. Commits: 5427c6e129fbf39f340f7bbc04d79af246b7cd7f; b3528a28fc47eacac61bbff4a763d3f71e2fa555. - Root-output formatting and enhanced plotting for projections: implements output of projection data to ROOT files and improves histogram printing, legend handling, and category visualizations. Commits: b634c3f6c3cb03fa6ae4c121b126d18a310e7752. Major bugs fixed: - Hardened and robust particle acceptance evaluation via IsParticleAccepted, reducing misclassification of events. - Stabilized NDGAr sample transfer and 2D projection plotting integration, eliminating inconsistencies across modules. - Improved ROOT I/O path and plotting formatting to prevent data loss and ensure consistent visualizations. Overall impact and accomplishments: - Enhanced data exploration and physics analysis readiness through richer visualization (2D projections) and robust event selection. - Streamlined data output workflow with ROOT-based storage and improved plotting, accelerating downstream analysis and reporting. Technologies/skills demonstrated: - C++ refactoring and modular design (ProjectionVariable, NDGAr structures). - ROOT I/O: ROOT file output, histogram formatting, and visualization improvements. - Data processing workflows: particle-level kinematic calculations and acceptance logic. - Clear commit-level traceability, maintainability, and testability.