
Over a three-month period, JT Umlins developed and integrated new numerical datasets and visualization tools within the foggie-sims/foggie repository to advance cosmological simulation analytics. They delivered halo track data assets and enhanced plotting scripts, focusing on data availability, reproducibility, and broader analytic coverage for halo evolution and gas-mass studies. Their technical approach centered on Python for data management, scientific computing, and plotting, with careful version control and documentation to ensure data provenance. The work enabled faster research iteration, improved downstream processing, and more robust cross-halo analyses, reflecting a thoughtful, research-driven engineering process with attention to pipeline readiness and analytic depth.

September 2025 monthly summary for foggie-sims/foggie focused on expanding gas-mass visualization capabilities to support broader halo-mass analyses. Deliverable: CGM and ISM gas mass plotting enhancements in FOGGHORN scripts, including updated imports and axis limits to accommodate a wider range of halo masses. This enables more comprehensive cross-halo gas-property analyses and improves consistency across datasets. Commit: e1b323e418705aeb658da78b60f7e225f2a8664a. No major bugs fixed this month. Overall impact: improved research throughput and more robust plotting tools for gas-mass analyses. Technologies/skills demonstrated: Python scripting, plotting configuration, refactoring for broader data ranges, and version control practices.
September 2025 monthly summary for foggie-sims/foggie focused on expanding gas-mass visualization capabilities to support broader halo-mass analyses. Deliverable: CGM and ISM gas mass plotting enhancements in FOGGHORN scripts, including updated imports and axis limits to accommodate a wider range of halo masses. This enables more comprehensive cross-halo gas-property analyses and improves consistency across datasets. Commit: e1b323e418705aeb658da78b60f7e225f2a8664a. No major bugs fixed this month. Overall impact: improved research throughput and more robust plotting tools for gas-mass analyses. Technologies/skills demonstrated: Python scripting, plotting configuration, refactoring for broader data ranges, and version control practices.
Month 2025-07: No major bugs fixed; Key feature delivered: added z=0 fast-forward halo track data for halos 5036 and 8508 in foggie-sims/foggie. This enhances data availability for halo evolution analyses and accelerates downstream simulations. Tech stack demonstrated includes Python-based data handling, Git version control, and data curation. Business value includes faster research iteration, improved reproducibility, and streamlined preparation of halo evolution datasets.
Month 2025-07: No major bugs fixed; Key feature delivered: added z=0 fast-forward halo track data for halos 5036 and 8508 in foggie-sims/foggie. This enhances data availability for halo evolution analyses and accelerates downstream simulations. Tech stack demonstrated includes Python-based data handling, Git version control, and data curation. Business value includes faster research iteration, improved reproducibility, and streamlined preparation of halo evolution datasets.
April 2025: Delivered a new numerical halo track data dataset and integrated it into the foggie-sims/foggie repository, enabling expanded simulation analytics and downstream processing. The work was anchored by commit 60b56a97c814661a7eedb1d3a7fdcd648259db62. No critical bugs were reported this month; focus was on data availability, reproducibility, and pipeline readiness, setting the foundation for enhanced model validation and analytics.
April 2025: Delivered a new numerical halo track data dataset and integrated it into the foggie-sims/foggie repository, enabling expanded simulation analytics and downstream processing. The work was anchored by commit 60b56a97c814661a7eedb1d3a7fdcd648259db62. No critical bugs were reported this month; focus was on data availability, reproducibility, and pipeline readiness, setting the foundation for enhanced model validation and analytics.
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