Smithsonian/layup
Jan 2025 – May 2025
4 Months active
Languages Used
MarkdownCC++PythonSQL
Technical Skills
Project InitializationAlgorithm DevelopmentAlgorithm ImplementationAstrodynamicsC++C++ Development
matthewholman
PROFILE
Matthewholman
Michael Holman developed core orbit fitting infrastructure for the Smithsonian/layup repository, focusing on robust, scalable solutions for LSST-scale astrodynamics. He established the project’s C++ and Python codebase, integrating numerical methods such as the Gauss method and Levenberg-Marquardt optimization to automate orbit determination and improve convergence. Holman enhanced data ingestion, error handling, and caching, enabling reliable barycentric conversions and temporal accuracy in predictions. His work included comprehensive documentation, code cleanup, and the creation of a structured API that returns encapsulated results. These contributions improved maintainability, reduced debugging effort, and provided a strong foundation for scientific computing and downstream analytics.
Overall Statistics
Feature vs Bugs
64%Features
Repository Contributions
24Total
Bugs
4
Commits
24
Features
7
Lines of code
23,066
Activity Months4
Your Network
12 peopleSame Organization
@cfa.harvard.edu2
Work History
May 2025
13 Commits • 3 Features
May 1, 2025May 2025 monthly summary for Smithsonian/layup: Focused on improving orbit fitting robustness, Python-C++ integration, and documentation with targeted bug fixes to improve temporal accuracy and caching consistency. Key outcomes include expanded support for TNOs/small asteroids, ID passing from Python to C++, and a more reliable barycentric conversion pipeline. These changes deliver measurable business value through more accurate predictions, reduced debugging effort, and improved maintainability.
13 Commits • 3 Features
May 1, 2025May 2025 monthly summary for Smithsonian/layup: Focused on improving orbit fitting robustness, Python-C++ integration, and documentation with targeted bug fixes to improve temporal accuracy and caching consistency. Key outcomes include expanded support for TNOs/small asteroids, ID passing from Python to C++, and a more reliable barycentric conversion pipeline. These changes deliver measurable business value through more accurate predictions, reduced debugging effort, and improved maintainability.
May 2025
April 2025
2 Commits • 1 Features
Apr 1, 2025April 2025: Delivered a major Orbit Fitting API overhaul for Smithsonian/layup, introducing an OrbfitResult-based output struct encapsulating all relevant results, and added a new predict function for calculating observation covariances. Also enhanced data ingestion and orbit determination with an improved run_from_files path. Hardened the simulation pipeline with explicit error handling in light travel time integration, improving robustness and reliability of corrections. Overall, these changes enable more reliable orbit determinations, cleaner interfaces, and a stronger foundation for downstream analytics.
April 2025
2 Commits • 1 Features
Apr 1, 2025April 2025: Delivered a major Orbit Fitting API overhaul for Smithsonian/layup, introducing an OrbfitResult-based output struct encapsulating all relevant results, and added a new predict function for calculating observation covariances. Also enhanced data ingestion and orbit determination with an improved run_from_files path. Hardened the simulation pipeline with explicit error handling in light travel time integration, improving robustness and reliability of corrections. Overall, these changes enable more reliable orbit determinations, cleaner interfaces, and a stronger foundation for downstream analytics.
March 2025
8 Commits • 2 Features
Mar 1, 2025March 2025: Laid the foundation for automated orbit fitting in Smithsonian/layup. Delivered core C++ based infrastructure and initial optimization workflow to accelerate end-to-end orbit determination. Key work included establishing Orbit Fitting Foundations with a scalable directory structure, integrating Gauss method for initial orbit determination and combining it with Levenberg-Marquardt optimization (including IOD_indices for automatic triad selection) to improve residuals and convergence, and introducing orbit file handling along with a simple three-observation selector. Also performed codebase cleanup by removing duplicate/outdated orbit fitting files to reduce maintenance overhead.
8 Commits • 2 Features
Mar 1, 2025March 2025: Laid the foundation for automated orbit fitting in Smithsonian/layup. Delivered core C++ based infrastructure and initial optimization workflow to accelerate end-to-end orbit determination. Key work included establishing Orbit Fitting Foundations with a scalable directory structure, integrating Gauss method for initial orbit determination and combining it with Levenberg-Marquardt optimization (including IOD_indices for automatic triad selection) to improve residuals and convergence, and introducing orbit file handling along with a simple three-observation selector. Also performed codebase cleanup by removing duplicate/outdated orbit fitting files to reduce maintenance overhead.
March 2025
January 2025
1 Commits • 1 Features
Jan 1, 2025Concise monthly summary for 2025-01 focusing on key accomplishments, impact, and skills demonstrated for the Smithsonian/layup project.
January 2025
1 Commits • 1 Features
Jan 1, 2025Concise monthly summary for 2025-01 focusing on key accomplishments, impact, and skills demonstrated for the Smithsonian/layup project.
Activity
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Quality Metrics
Correctness86.6%
Maintainability89.2%
Architecture80.4%
Performance78.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
CC++MarkdownPythonSQL
Technical Skills
Algorithm DevelopmentAlgorithm ImplementationAlgorithm OptimizationAstrodynamicsAstrophysicsBackend DevelopmentC++C++ DevelopmentCachingCode CleanupCode DocumentationCode ReadabilityCode RefactoringData AnalysisData Processing
Repositories Contributed To
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