
During April 2025, Lavaut enhanced the DUNE/duneana repository by implementing a data-model upgrade to support more detailed low-energy cluster analysis. Leveraging C++ and skills in data structures and algorithm development, Lavaut refactored core data structures to store space-point and waveform information for hits within clusters. This technical approach required updating analysis routines to utilize the enriched data, enabling more precise event reconstruction and improved data fidelity for downstream physics analyses. The work established a robust foundation for finer-grained studies, with clear documentation and disciplined commit practices ensuring traceability. The depth of the changes reflects careful attention to analysis requirements.

Month: 2025-04 — concise performance-review focused update. Overview: Implemented a targeted data-model enhancement in DUNE/duneana to support finer-grained low-energy cluster analysis by storing and leveraging space-point and waveform information associated with cluster hits. The work involved refactoring data structures and updating analysis routines to consume the new details, establishing a foundation for more precise physics analyses and improved data quality in downstream workflows.
Month: 2025-04 — concise performance-review focused update. Overview: Implemented a targeted data-model enhancement in DUNE/duneana to support finer-grained low-energy cluster analysis by storing and leveraging space-point and waveform information associated with cluster hits. The work involved refactoring data structures and updating analysis routines to consume the new details, establishing a foundation for more precise physics analyses and improved data quality in downstream workflows.
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