Smithsonian/layup
Jan 2025 – May 2025
4 Months active
Languages Used
MarkdownCC++PythonSQL
Technical Skills
Project InitializationAlgorithm DevelopmentAlgorithm ImplementationAstrodynamicsC++C++ Development
matthewholman
PROFILE
Matthewholman
Developed core orbit fitting infrastructure for the Smithsonian/layup repository, focusing on robust, scalable solutions for astrodynamics and astrophysics applications. Over four months, delivered features such as a C++-based orbit determination workflow, integration of the Gauss method with Levenberg-Marquardt optimization, and a comprehensive API overhaul returning structured results. Enhanced reliability through explicit error handling, improved data ingestion, and consistent caching mechanisms. Expanded support for small bodies and enabled seamless Python-C++ integration for object identification. Emphasized maintainability with thorough documentation, code cleanup, and targeted bug fixes, leveraging skills in C++, Python, numerical methods, and scientific computing to streamline orbit analysis.
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
13 peopleSame Organization
@cfa.harvard.edu3
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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