
Greg Putnam developed and maintained core data processing and simulation infrastructure for the SBNSoftware/icaruscode and sbncode repositories, focusing on high-energy physics workflows. He engineered robust configuration management and integrated advanced C++ modules for signal processing, detector simulation, and event reconstruction, including GPU-accelerated DNN inference and overlay generation for Monte Carlo data. By refactoring data structures, standardizing Geant4 configurations, and enhancing calibration and timing alignment, Greg improved reliability and data quality across the pipeline. His work leveraged C++, CMake, and FCL to deliver scalable, maintainable solutions that enabled more accurate physics analyses and streamlined end-to-end simulation-to-analysis throughput.

September 2025 summary: Key features delivered to sbncode include a new WireModGen Monte Carlo muon generator overlay with CRT plane configuration, enabling overlay of MC muons on wire-chamber data and multi-plane CRT intersection checks (commits 65892227a1f988ca38156a756357a3d3e7f00cde; 51bf49fee530565ef0665278e214f33701519a94); CAFMaker CRT truth matching enhancement adding FEB channel to AuxDetID mapping and integration into FillCRTHit for precise origin/properties analysis (commit 33f34553003226b5f729a3418ad4398b107587fb); TrackCaloSkimmer cosmic muon filter tool implemented as a new C++ class and registered as an ART plugin to improve calibration by excluding unwanted cosmic muon events (commit 58a0b00887f3409d0dd7b74566230350dc5a718e). These efforts advance data overlay fidelity, event origin analysis, and calibration quality. Overall impact and accomplishments: The month delivered end-to-end enhancements across simulation overlays, detector-hit association, and data-quality tooling, enabling more accurate background estimation, richer physics analyses, and more reliable calibration. Maintained and improved by leveraging modular C++ components, ART plugin architecture, and integration with CORSIKA shower databases. Technologies/skills demonstrated: C++, ART framework/plugin development, CAFMaker CRT integration, overlay generation and multi-plane detector configuration, CRT hit-to-simulation truth mapping, and performance-conscious data processing pipelines.
September 2025 summary: Key features delivered to sbncode include a new WireModGen Monte Carlo muon generator overlay with CRT plane configuration, enabling overlay of MC muons on wire-chamber data and multi-plane CRT intersection checks (commits 65892227a1f988ca38156a756357a3d3e7f00cde; 51bf49fee530565ef0665278e214f33701519a94); CAFMaker CRT truth matching enhancement adding FEB channel to AuxDetID mapping and integration into FillCRTHit for precise origin/properties analysis (commit 33f34553003226b5f729a3418ad4398b107587fb); TrackCaloSkimmer cosmic muon filter tool implemented as a new C++ class and registered as an ART plugin to improve calibration by excluding unwanted cosmic muon events (commit 58a0b00887f3409d0dd7b74566230350dc5a718e). These efforts advance data overlay fidelity, event origin analysis, and calibration quality. Overall impact and accomplishments: The month delivered end-to-end enhancements across simulation overlays, detector-hit association, and data-quality tooling, enabling more accurate background estimation, richer physics analyses, and more reliable calibration. Maintained and improved by leveraging modular C++ components, ART plugin architecture, and integration with CORSIKA shower databases. Technologies/skills demonstrated: C++, ART framework/plugin development, CAFMaker CRT integration, overlay generation and multi-plane detector configuration, CRT hit-to-simulation truth mapping, and performance-conscious data processing pipelines.
June 2025 focused on stabilizing hit collection, improving data quality, and enabling GPU-accelerated inference for the Icarus workflow. Deliverables emphasize reliability, resource utilization, and precise timing alignment across hit finding and DNN processing in SBNSoftware/icaruscode.
June 2025 focused on stabilizing hit collection, improving data quality, and enabling GPU-accelerated inference for the Icarus workflow. Deliverables emphasize reliability, resource utilization, and precise timing alignment across hit finding and DNN processing in SBNSoftware/icaruscode.
May 2025 monthly summary for SBNSoftware/icaruscode: Achieved configuration cleanup, Geant4 configuration standardization, improved test filtering, and targeted fixes in MC Stage0 input handling and calibration tag versions. These efforts reduced configuration clutter, stabilized test runs, and ensured alignment with current data versions, delivering measurable business value and technical reliability.
May 2025 monthly summary for SBNSoftware/icaruscode: Achieved configuration cleanup, Geant4 configuration standardization, improved test filtering, and targeted fixes in MC Stage0 input handling and calibration tag versions. These efforts reduced configuration clutter, stabilized test runs, and ensured alignment with current data versions, delivering measurable business value and technical reliability.
April 2025: Strengthened data processing reliability and extended capabilities across SBNSoftware and ICARUS codebases. Key features include SimEnergyDepositLite support in FilterSimEnergyDeposits and overlay generation support to enable more realistic simulations. Critical bugs fixed include: improved TrackCaloSkimmer CRTHitT0TaggingInfo association, buffer-overflow guard for GENIE record processing, and corrected ADCScaleFactor application. Major architectural updates include MC Stage0 processing without trigger pathway and Stage1 integration with pipeline cleanup, along with data pipeline output optimization. Real-data handling improvements and purity analysis reintroduction were completed to improve data/MC separation and analysis fidelity. These changes collectively enhance robustness, data quality, and end-to-end simulation-to-analysis throughput, delivering business value through more reliable results and scalable workflows.
April 2025: Strengthened data processing reliability and extended capabilities across SBNSoftware and ICARUS codebases. Key features include SimEnergyDepositLite support in FilterSimEnergyDeposits and overlay generation support to enable more realistic simulations. Critical bugs fixed include: improved TrackCaloSkimmer CRTHitT0TaggingInfo association, buffer-overflow guard for GENIE record processing, and corrected ADCScaleFactor application. Major architectural updates include MC Stage0 processing without trigger pathway and Stage1 integration with pipeline cleanup, along with data pipeline output optimization. Real-data handling improvements and purity analysis reintroduction were completed to improve data/MC separation and analysis fidelity. These changes collectively enhance robustness, data quality, and end-to-end simulation-to-analysis throughput, delivering business value through more reliable results and scalable workflows.
March 2025 monthly summary focusing on business value and technical achievements across SBNSoftware repositories (icaruscode, sbncode, sbnobj). The work delivered improves reconstruction quality, MC realism, end-to-end workflow stability, and calibration data handling, supporting more reliable physics results and faster iteration cycles.
March 2025 monthly summary focusing on business value and technical achievements across SBNSoftware repositories (icaruscode, sbncode, sbnobj). The work delivered improves reconstruction quality, MC realism, end-to-end workflow stability, and calibration data handling, supporting more reliable physics results and faster iteration cycles.
Monthly work summary for February 2025 across SBNSoftware repositories (sbncode, sbnobj, sbndcode). Focused on delivering core reconstruction improvements, data integrity features, and enhanced data quality metrics to enable robust physics reconstruction, validation, and monitoring.
Monthly work summary for February 2025 across SBNSoftware repositories (sbncode, sbnobj, sbndcode). Focused on delivering core reconstruction improvements, data integrity features, and enhanced data quality metrics to enable robust physics reconstruction, validation, and monitoring.
Monthly summary for 2025-01 focusing on ICARUS codebase stabilization and bug resolution in stage 0 reconstruction configuration.
Monthly summary for 2025-01 focusing on ICARUS codebase stabilization and bug resolution in stage 0 reconstruction configuration.
December 2024 monthly summary for SBNSoftware/icaruscode: Delivered targeted fixes and configuration improvements that enhance data interpretation reliability, reduce IO-related issues, and align the 2D analysis workflow with the latest processing modules. Focused on correcting data mapping for H5 IO, deprecating incompatible H5 saving defaults, and standardizing 2D SPAna defaults with updated wire production wiring.
December 2024 monthly summary for SBNSoftware/icaruscode: Delivered targeted fixes and configuration improvements that enhance data interpretation reliability, reduce IO-related issues, and align the 2D analysis workflow with the latest processing modules. Focused on correcting data mapping for H5 IO, deprecating incompatible H5 saving defaults, and standardizing 2D SPAna defaults with updated wire production wiring.
In November 2024, the ICARUS reconstruction and signal processing (SP) workstream delivered a major integration upgrade for 2D SP within ICARUS reconstruction, a comprehensive configuration overhaul, and DNN readiness enhancements, while tightening outputs and instrumenting performance metrics. The work improves reconstruction fidelity, maintainability, and readiness for DNN-enabled analyses, contributing measurable business value through more reliable results and cleaner data products.
In November 2024, the ICARUS reconstruction and signal processing (SP) workstream delivered a major integration upgrade for 2D SP within ICARUS reconstruction, a comprehensive configuration overhaul, and DNN readiness enhancements, while tightening outputs and instrumenting performance metrics. The work improves reconstruction fidelity, maintainability, and readiness for DNN-enabled analyses, contributing measurable business value through more reliable results and cleaner data products.
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