
Jake Kurle developed and maintained core solar system object association pipelines for the LSST project, primarily in the lsst/pipe_tasks and lsst/ap_association repositories. He engineered robust data models and processing workflows using Python, Astropy, and Pandas, migrating key components from DataFrames to Astropy Tables with explicit units to improve data integrity and compatibility. Jake implemented scalable association tasks, enhanced metadata tracking, and standardized schema definitions, enabling reliable cross-pipeline analytics and downstream science. His work addressed data quality, reproducibility, and maintainability, introducing configuration-driven processing and rigorous validation. The solutions demonstrated depth in scientific computing, data engineering, and astronomical software development.
March 2026 monthly summary focusing on key accomplishments, major fixes, impact, and skills demonstrated for two core repos.
March 2026 monthly summary focusing on key accomplishments, major fixes, impact, and skills demonstrated for two core repos.
February 2026 monthly summary focusing on delivering robust data integrity, consistent modeling, and reliable ephemerides production across two repositories. The work emphasizes business value by improving accuracy of object designations, enabling cleaner downstream analyses, and reducing rework from data integrity issues.
February 2026 monthly summary focusing on delivering robust data integrity, consistent modeling, and reliable ephemerides production across two repositories. The work emphasizes business value by improving accuracy of object designations, enabling cleaner downstream analyses, and reducing rework from data integrity issues.
January 2026 performance highlights focused on strengthening solar-system data handling, improving visit data processing, and expanding MPC support across SSO associations. The work enhances data quality, pipeline reliability, and cross-repo consistency, delivering measurable business value in data integrity and processing efficiency.
January 2026 performance highlights focused on strengthening solar-system data handling, improving visit data processing, and expanding MPC support across SSO associations. The work enhances data quality, pipeline reliability, and cross-repo consistency, delivering measurable business value in data integrity and processing efficiency.
December 2025 performance summary for lsst/pipe_tasks and lsst/ap_association. Focused on delivering observability improvements, standardized object identifier handling, and data consistency enhancements; aligned MPC designation naming with v10; strengthened package alerts data model; and improved data quality for downstream workflows.
December 2025 performance summary for lsst/pipe_tasks and lsst/ap_association. Focused on delivering observability improvements, standardized object identifier handling, and data consistency enhancements; aligned MPC designation naming with v10; strengthened package alerts data model; and improved data quality for downstream workflows.
November 2025 focused on strengthening Solar System data handling, pipeline reliability, and DP2 compatibility across lsst/drp_pipe and lsst/pipe_tasks. Delivered a new Ephemerides Generation Task in the Solar System Pipeline, extended object ID handling, and improved SSO-DIA associations with full DP2 schema alignment. Implemented long-path safety measures to stabilize file handling in DP2 workflows. These changes enhance data integrity, scalability, and downstream analytics for solar system object processing.
November 2025 focused on strengthening Solar System data handling, pipeline reliability, and DP2 compatibility across lsst/drp_pipe and lsst/pipe_tasks. Delivered a new Ephemerides Generation Task in the Solar System Pipeline, extended object ID handling, and improved SSO-DIA associations with full DP2 schema alignment. Implemented long-path safety measures to stabilize file handling in DP2 workflows. These changes enhance data integrity, scalability, and downstream analytics for solar system object processing.
In 2025-10, the team delivered targeted features across two core repos to enhance maintainability, usability, and data handling. Key refactors and new storage capabilities lay groundwork for scalable workflows, while observer-agnostic ephemerides support broad usability across observatories. The work emphasizes code quality, consistency, and business value by enabling faster onboarding, cross-project reuse, and more reliable data processing.
In 2025-10, the team delivered targeted features across two core repos to enhance maintainability, usability, and data handling. Key refactors and new storage capabilities lay groundwork for scalable workflows, while observer-agnostic ephemerides support broad usability across observatories. The work emphasizes code quality, consistency, and business value by enabling faster onboarding, cross-project reuse, and more reliable data processing.
September 2025 — Focused on preserving solar system object orbit data during table standardization in lsst/ap_association. Implemented MPCORB routing around the DiaPipelineTask standardization so MPCORB data is included in the standardized table, ensuring downstream processing retains complete orbit information.
September 2025 — Focused on preserving solar system object orbit data during table standardization in lsst/ap_association. Implemented MPCORB routing around the DiaPipelineTask standardization so MPCORB data is included in the standardized table, ensuring downstream processing retains complete orbit information.
August 2025: Delivered data-enrichment and robustness improvements across lsst/pipe_tasks and lsst/ap_association, focusing on MPCORB data integration and alert pipeline resilience. The work enhances orbital parameter availability for DiaSource association, strengthens data flow and schema standardization, and expands test coverage, delivering clear business value through more reliable alerts and richer downstream data.
August 2025: Delivered data-enrichment and robustness improvements across lsst/pipe_tasks and lsst/ap_association, focusing on MPCORB data integration and alert pipeline resilience. The work enhances orbital parameter availability for DiaSource association, strengthens data flow and schema standardization, and expands test coverage, delivering clear business value through more reliable alerts and richer downstream data.
July 2025 monthly summary for lsst/sdm_schemas focusing on key accomplishments: Delivered DP1-aligned APDB schema updates and velocity unit corrections for SSSource, with corresponding documentation updates, improving data compatibility, accuracy, and downstream pipeline reliability.
July 2025 monthly summary for lsst/sdm_schemas focusing on key accomplishments: Delivered DP1-aligned APDB schema updates and velocity unit corrections for SSSource, with corresponding documentation updates, improving data compatibility, accuracy, and downstream pipeline reliability.
June 2025: Delivered Solar System Object Count Tracking in the Data Processing Pipeline for lsst/rtn-095, introducing a new parameter nsolarsystemobjects by querying the ss_object dataset and updating nsolarsystemsources to reflect counts from the ss_source dataset. This work is backed by commit c2abe2ca16a66eeb036b0027dfecdab6e8078a59 ("One extra solar system parameter"). No major bugs reported this period; ensured accurate counts and parameter propagation across pipeline components, improving data quality and downstream analytics. This milestone demonstrates proficiency in data pipeline design, dataset querying, parameter management, and cross-dataset integration, delivering measurable business value through better tracking of solar system object counts and improved governance of pipeline parameters.
June 2025: Delivered Solar System Object Count Tracking in the Data Processing Pipeline for lsst/rtn-095, introducing a new parameter nsolarsystemobjects by querying the ss_object dataset and updating nsolarsystemsources to reflect counts from the ss_source dataset. This work is backed by commit c2abe2ca16a66eeb036b0027dfecdab6e8078a59 ("One extra solar system parameter"). No major bugs reported this period; ensured accurate counts and parameter propagation across pipeline components, improving data quality and downstream analytics. This milestone demonstrates proficiency in data pipeline design, dataset querying, parameter management, and cross-dataset integration, delivering measurable business value through better tracking of solar system object counts and improved governance of pipeline parameters.
April 2025 (2025-04) monthly summary for lsst-pst/pstn-019: Delivered a core feature enhancing Solar System object association. Implemented Solar System Object Association: Nearest DiaSource Matching with Configurable Radius, including explicit behavioral guarantees: preloads ephemerides from an internal service, corrects them to the exact observation time, and matches Solar System objects to the nearest DiaSource within a configurable radius. This work improves matching accuracy, reproducibility, and downstream science quality, setting the stage for production use and broader adoption in solar system analytics.
April 2025 (2025-04) monthly summary for lsst-pst/pstn-019: Delivered a core feature enhancing Solar System object association. Implemented Solar System Object Association: Nearest DiaSource Matching with Configurable Radius, including explicit behavioral guarantees: preloads ephemerides from an internal service, corrects them to the exact observation time, and matches Solar System objects to the nearest DiaSource within a configurable radius. This work improves matching accuracy, reproducibility, and downstream science quality, setting the stage for production use and broader adoption in solar system analytics.
March 2025 highlights: Delivered data-model consolidation and pipeline robustness improvements across lsst/pipe_tasks and lsst/drp_pipe to boost data quality, traceability, and cross-pipeline consistency. Implemented a unified SsTable for per-patch ssSource data and generated an ssObject table, enabling accurate object counts and streamlined downstream analytics. Strengthened Solar System association pipeline with data-type enforcement, correct detector usage, and enhanced unassociated-object context, reducing mis-assignments and improving reproducibility. Enriched diaSource history by linking associated diaSources to diaSourceHistory and refining selection to targets linked to Solar System objects within the current patch. Introduced a SsTables consolidation task for DRP pipelines and standardized its naming and configuration scope, with explicit exclusions for non-LSST instrument pipelines. These efforts deliver tangible business value through higher data integrity, better lineage, and more reliable science-ready catalogs across repositories.
March 2025 highlights: Delivered data-model consolidation and pipeline robustness improvements across lsst/pipe_tasks and lsst/drp_pipe to boost data quality, traceability, and cross-pipeline consistency. Implemented a unified SsTable for per-patch ssSource data and generated an ssObject table, enabling accurate object counts and streamlined downstream analytics. Strengthened Solar System association pipeline with data-type enforcement, correct detector usage, and enhanced unassociated-object context, reducing mis-assignments and improving reproducibility. Enriched diaSource history by linking associated diaSources to diaSourceHistory and refining selection to targets linked to Solar System objects within the current patch. Introduced a SsTables consolidation task for DRP pipelines and standardized its naming and configuration scope, with explicit exclusions for non-LSST instrument pipelines. These efforts deliver tangible business value through higher data integrity, better lineage, and more reliable science-ready catalogs across repositories.
February 2025 monthly summary focusing on key business value and technical achievements across multiple LSST pipeline components: Key features delivered - LSST pipe_tasks: Solar System Object (SSO) support integrated into the DRP association pipeline, including a new MPSkyEphemerisQueryTask for querying SSOs, storage format upgrades to ArrowAstropy, a dedicated SolarSystemAssociationTask, robust handling when no unassociated diaSources exist, and ID management for SSOs. - LSST ap_association: Refactor and data handling upgrade for ssoAssociation to accept metadata-only inputs, migration to Astropy Tables, consolidation of signature/imports, and relocation of the task to pipe_tasks. - LSST drp_pipe: Preloaded DRP SSObjects added to test pipeline inputs to standardize testing and validation of SSObject handling. Major bugs fixed - LSST ap_association: DiaPipelineTask data handling compatibility fix by converting Astropy Table objects to Pandas DataFrames to satisfy downstream processing. Overall impact and accomplishments - Achieved robust SSO integration across DRP workflows with improved data interchange formats (ArrowAstropy, Astropy Tables) and clearer task ownership, enabling more scalable SSO processing in production pipelines. - Consolidated and modernized SSO-related code paths, reducing complexity and improving maintainability, with explicit focus on metadata-driven inputs and consistent data handling. - Testing infrastructure gains: standardized SSO data in tests to improve coverage and reliability; CI efficiency improved by disabling non-core SSO steps in CI where appropriate. Technologies/skills demonstrated - Python, LSST Stack integration, ArrowAstropy, Astropy Tables, Pandas, task orchestration, data handling across pipeline components, and test infrastructure optimization.
February 2025 monthly summary focusing on key business value and technical achievements across multiple LSST pipeline components: Key features delivered - LSST pipe_tasks: Solar System Object (SSO) support integrated into the DRP association pipeline, including a new MPSkyEphemerisQueryTask for querying SSOs, storage format upgrades to ArrowAstropy, a dedicated SolarSystemAssociationTask, robust handling when no unassociated diaSources exist, and ID management for SSOs. - LSST ap_association: Refactor and data handling upgrade for ssoAssociation to accept metadata-only inputs, migration to Astropy Tables, consolidation of signature/imports, and relocation of the task to pipe_tasks. - LSST drp_pipe: Preloaded DRP SSObjects added to test pipeline inputs to standardize testing and validation of SSObject handling. Major bugs fixed - LSST ap_association: DiaPipelineTask data handling compatibility fix by converting Astropy Table objects to Pandas DataFrames to satisfy downstream processing. Overall impact and accomplishments - Achieved robust SSO integration across DRP workflows with improved data interchange formats (ArrowAstropy, Astropy Tables) and clearer task ownership, enabling more scalable SSO processing in production pipelines. - Consolidated and modernized SSO-related code paths, reducing complexity and improving maintainability, with explicit focus on metadata-driven inputs and consistent data handling. - Testing infrastructure gains: standardized SSO data in tests to improve coverage and reliability; CI efficiency improved by disabling non-core SSO steps in CI where appropriate. Technologies/skills demonstrated - Python, LSST Stack integration, ArrowAstropy, Astropy Tables, Pandas, task orchestration, data handling across pipeline components, and test infrastructure optimization.
January 2025 (2025-01) — lsst/ap_association: Delivered substantial data-model enhancements to the SSO association workflow, enabling richer positional and state-vector context for downstream analytics and cross-system interoperability. Implemented new angular information columns and source ID handling, and persisted residual RA/Dec, galactic, and ecliptic coordinates for detected sources. Expanded the data model to include detailed state vectors (position and velocity) in heliocentric and topocentric frames, with derived metrics such as phase angle and distances, and improved consistency of source IDs and column naming.
January 2025 (2025-01) — lsst/ap_association: Delivered substantial data-model enhancements to the SSO association workflow, enabling richer positional and state-vector context for downstream analytics and cross-system interoperability. Implemented new angular information columns and source ID handling, and persisted residual RA/Dec, galactic, and ecliptic coordinates for detected sources. Expanded the data model to include detailed state vectors (position and velocity) in heliocentric and topocentric frames, with derived metrics such as phase angle and distances, and improved consistency of source IDs and column naming.
December 2024 monthly summary for developer contributions across lsst/ap_association, lsst/analysis_tools, and lsst/ap_pipe. Focused on delivering measurable business value through enhanced metadata tracking, improved traceability of solar system object associations, and streamlined pipeline integration and performance enhancements. Highlights include standardized metadata updates in DiaPipelineTask, comprehensive propagation of SSO association results, introduction of associationCore for difference-imaging metadata capture, and integration/optimization efforts in DECam and LSSTCam pipelines with conflict resolution and processing-time improvements.
December 2024 monthly summary for developer contributions across lsst/ap_association, lsst/analysis_tools, and lsst/ap_pipe. Focused on delivering measurable business value through enhanced metadata tracking, improved traceability of solar system object associations, and streamlined pipeline integration and performance enhancements. Highlights include standardized metadata updates in DiaPipelineTask, comprehensive propagation of SSO association results, introduction of associationCore for difference-imaging metadata capture, and integration/optimization efforts in DECam and LSSTCam pipelines with conflict resolution and processing-time improvements.
Monthly summary for 2024-11: Summary of work focused on enhancing pipeline reliability, cross-instrument no-template processing, and robust solar system object analysis, with targeted bug fixes and contract refinements across multiple LSST repos. Key outcomes include improved data alignment in GetRegionTimeFromVisit, corrected pipeline contract references to reflect upstream changes, expanded SingleFrame no-template pipelines across instruments, and resilient ephemeris querying. The work emphasizes business value through reduced pipeline failures, greater processing coverage, and clearer, standardized configurations and documentation.
Monthly summary for 2024-11: Summary of work focused on enhancing pipeline reliability, cross-instrument no-template processing, and robust solar system object analysis, with targeted bug fixes and contract refinements across multiple LSST repos. Key outcomes include improved data alignment in GetRegionTimeFromVisit, corrected pipeline contract references to reflect upstream changes, expanded SingleFrame no-template pipelines across instruments, and resilient ephemeris querying. The work emphasizes business value through reduced pipeline failures, greater processing coverage, and clearer, standardized configurations and documentation.
Month 2024-10: Delivered the SsSingleFrameAssociationTask for Solar System Source Association and prepared the pipeline to process single-frame sources and associate them with solar system objects. The feature includes configurations, connections, and core processing logic, with a later refactor updating the input type from DataFrame to SourceTable and adjusting connections accordingly. This work integrates with the existing solar system association workflow to store associated source data and sets the foundation for scalable, table-based inputs.
Month 2024-10: Delivered the SsSingleFrameAssociationTask for Solar System Source Association and prepared the pipeline to process single-frame sources and associate them with solar system objects. The feature includes configurations, connections, and core processing logic, with a later refactor updating the input type from DataFrame to SourceTable and adjusting connections accordingly. This work integrates with the existing solar system association workflow to store associated source data and sets the foundation for scalable, table-based inputs.

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