
Worked on the LDMX-Software/pflib repository to deliver calibration enhancements focused on improving measurement accuracy and automation for embedded systems. Developed and integrated new tools for clock phase and Time-of-Arrival (TOA) calibration, including sampling phase scans and TOA alignment workflows, using both C++ and Python for data acquisition, analysis, and visualization. Enhanced the calibration workflow by updating configuration management and implementing automated data handling and plotting scripts. Addressed a boundary bug in TOA alignment to ensure reliable operation. The work established a scalable foundation for batch calibration studies, demonstrating depth in scientific computing, signal processing, and firmware development within complex systems.
August 2025 (2025-08) monthly summary for LDMX-Software/pflib: Focused on delivering Time-of-Arrival (TOA) calibration tooling and improving alignment reliability. Implemented TOA Calibration Tooling with trim_toa scan and vref_scan, including Python scripts for data analysis, plotting, and configuration generation, plus a new C++ task to execute the TOA scan. Refactored the TOA alignment workflow to integrate a dedicated vref_scan implementation and fixed a boundary bug to enforce the correct max trim_toa (63). This work enhances measurement accuracy, enables automated analysis, and establishes a scalable foundation for batch TOA studies across datasets.
August 2025 (2025-08) monthly summary for LDMX-Software/pflib: Focused on delivering Time-of-Arrival (TOA) calibration tooling and improving alignment reliability. Implemented TOA Calibration Tooling with trim_toa scan and vref_scan, including Python scripts for data analysis, plotting, and configuration generation, plus a new C++ task to execute the TOA scan. Refactored the TOA alignment workflow to integrate a dedicated vref_scan implementation and fixed a boundary bug to enforce the correct max trim_toa (63). This work enhances measurement accuracy, enables automated analysis, and establishes a scalable foundation for batch TOA studies across datasets.
July 2025 (LDMX-Software/pflib) — This period focused on delivering calibration enhancements that improve measurement accuracy, automation, and data handling within the pflib module. No major bugs were reported during the month.
July 2025 (LDMX-Software/pflib) — This period focused on delivering calibration enhancements that improve measurement accuracy, automation, and data handling within the pflib module. No major bugs were reported during the month.

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