
Over five months, Cyifan contributed to the DUNE/larnd-sim and DUNE/ndlar_flow repositories by developing and refining simulation and data processing tools for detector research. They enhanced detector simulation accuracy by tuning step sizes and decoupling configuration parameters, enabling more flexible and realistic modeling. Cyifan improved data visualization workflows by integrating configurable data sources and streamlining event display setup using Python and YAML. Their work included targeted bug fixes, such as correcting ADC digitization and event ID handling, and introduced robust configuration management for Monte Carlo pipelines. These efforts resulted in more maintainable, efficient, and reproducible scientific computing workflows.

Month: 2025-07 — DUNE/larnd-sim delivered a feature enabling configurable max_radius for detector properties, decoupling from response file dimensions and improving configuration flexibility for detector simulations. Neighbor pixel distance calculations were updated to respect the new configurable max_radius, ensuring consistency across simulation components.
Month: 2025-07 — DUNE/larnd-sim delivered a feature enabling configurable max_radius for detector properties, decoupling from response file dimensions and improving configuration flexibility for detector simulations. Neighbor pixel distance calculations were updated to respect the new configurable max_radius, ensuring consistency across simulation components.
March 2025 monthly summary for DUNE/larnd-sim focusing on detector simulation enhancements and efficiency improvements. Implemented targeted changes to align simulation with detector response characteristics, delivering higher fidelity results with reduced compute time.
March 2025 monthly summary for DUNE/larnd-sim focusing on detector simulation enhancements and efficiency improvements. Implemented targeted changes to align simulation with detector response characteristics, delivering higher fidelity results with reduced compute time.
February 2025 monthly summary: Delivered stability-critical fixes and configuration enhancements across DUNE/larnd-sim and DUNE/ndlar_flow, emphasizing correctness, reproducibility, and flexible data processing. Key outcomes include targeted bug fixes and configuration upgrades that improve simulation accuracy, data integrity, and maintenance efficiency across both repositories.
February 2025 monthly summary: Delivered stability-critical fixes and configuration enhancements across DUNE/larnd-sim and DUNE/ndlar_flow, emphasizing correctness, reproducibility, and flexible data processing. Key outcomes include targeted bug fixes and configuration upgrades that improve simulation accuracy, data integrity, and maintenance efficiency across both repositories.
Concise monthly summary for 2025-01 highlighting key features delivered, major fixes, impact, and skills demonstrated. Focused on business value and technical achievement with concrete deliverables.
Concise monthly summary for 2025-01 highlighting key features delivered, major fixes, impact, and skills demonstrated. Focused on business value and technical achievement with concrete deliverables.
Concise monthly summary for 2024-11 focusing on business value and technical achievements. Delivered refactor of LArEventDisplay with RunsDB integration in DUNE/ndlar_flow, enabling flexible data source configuration for event visualization and laying groundwork for multi-source data support. Improved maintainability through code cleanup and script enhancements that streamline data-driven display setups.
Concise monthly summary for 2024-11 focusing on business value and technical achievements. Delivered refactor of LArEventDisplay with RunsDB integration in DUNE/ndlar_flow, enabling flexible data source configuration for event visualization and laying groundwork for multi-source data support. Improved maintainability through code cleanup and script enhancements that streamline data-driven display setups.
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