March 2025 monthly performance summary for the MaCh3 family. Delivered significant configurability, stability, and workflow improvements across MaCh3, MaCh3_DUNE, and MaCh3Tutorial. Highlights include enabling MO switching by default, configurable MCMC burn-in with YAML-driven defaults and cross-component stabilization, and user-configurable 2D likelihood scan parameters. Fixed critical boundary handling in CircularPrior and hardened defaults for OscFixParams and XsecFixParams to safe empty vectors. Also advanced parallel experimentation with concurrent 1D/2D likelihood scans and laid groundwork for future 2D scanning in the tutorial.

February 2025 (2025-02) performance summary for DUNE/MaCh3_DUNE: Delivered two key features that enhance precision and reliability of atmospheric analyses and likelihood scans. (1) Atmospheric binning granularity upgrade: increased RecoCosineZ bin count from 5 to 10 for AtmSample_nueselec.yaml and AtmSample_numuselec.yaml to improve precision of atmospheric event reconstruction and simulation. (2) Likelihood scan configurability and initialization: added a configuration-driven toggle to enable/disable the 2D likelihood scan and initialized oscillation parameters from the config before running the scan to ensure starting points near the Asimov-like point for improved accuracy. No major bugs fixed this month. Overall impact: higher accuracy in atmospheric analyses, more reliable and faster-converging likelihood scans, enabling more precise fits and reproducible results. Technologies/skills demonstrated: binning strategy optimization, configuration-driven design, YAML/config handling, initialization heuristics, and strong commit traceability.

January 2025 performance summary for MaCh3 work across DUNE/MaCh3_DUNE and mach3-software/MaCh3. Delivered automation-driven atmospheric binning enhancements, expanded multi-dimensional data support in C++ data processing, and stabilized ROOT-based builds for broader compatibility. These outcomes improve data quality and processing efficiency, reduce manual tuning, and enhance future scalability. Key outcomes include automated binning selection, 1D/2D data support, and a build compatibility fix that prevents ROOT-related failures. Demonstrates strong C++ proficiency, scripting, data handling, and cross-repo collaboration.