simonsobs/sotodlib
Dec 2024 – Jan 2026
5 Months active
Languages Used
PythonC++
Technical Skills
Astronomy Data ProcessingData AnalysisSignal ProcessingSoftware DevelopmentData ProcessingDatabase Management
Erik Rosenberg
PROFILE
Erik Rosenberg
Worked on the simonsobs/sotodlib repository, delivering features and fixes to enhance data processing pipelines for astronomical observations. Developed subscan-level analysis and PSD-based noise ratio computation, enabling more granular data quality assessment and improved noise characterization. Refactored the SAT demod mapmaker and expanded the atomic database, focusing on maintainability and performance. Addressed robustness by fixing edge-case bugs in weight calculations and database initialization, improving reliability for both single-detector and multi-detector scenarios. Utilized Python, C++, and SQLAlchemy to implement scientific computing, signal processing, and database management solutions, consistently updating documentation and tests to align with evolving code structure and functionality.
Overall Statistics
Feature vs Bugs
60%Features
Repository Contributions
5Total
Bugs
2
Commits
5
Features
3
Lines of code
1,557
Activity Months5
Your Network
27 peopleShared Repositories
27
Work History
January 2026
1 Commits
Jan 1, 2026January 2026 (simonsobs/sotodlib): Stability-focused month with a critical bug fix in the DB initialization path. Delivered a fix to ensure correct passing of SQLAlchemy engine arguments, improving utilization of connection parameters and reducing startup/misconfiguration errors. This work enhances reliability for downstream data processing and querying; no new features released this month.
1 Commits
Jan 1, 2026January 2026 (simonsobs/sotodlib): Stability-focused month with a critical bug fix in the DB initialization path. Delivered a fix to ensure correct passing of SQLAlchemy engine arguments, improving utilization of connection parameters and reducing startup/misconfiguration errors. This work enhances reliability for downstream data processing and querying; no new features released this month.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025: PSD-based Noise Ratio Computation delivered for the simonsobs/sotodlib preprocessing pipeline. Introduced PSD-derived noise ratios to enable more accurate noise assessments in observational data, with enhanced support for intra-observation splits and atomic information. This work improves data quality controls and reliability of downstream analyses.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025: PSD-based Noise Ratio Computation delivered for the simonsobs/sotodlib preprocessing pipeline. Introduced PSD-derived noise ratios to enable more accurate noise assessments in observational data, with enhanced support for intra-observation splits and atomic information. This work improves data quality controls and reliability of downstream analyses.
June 2025
1 Commits
Jun 1, 2025June 2025: Robustness and reliability improvements across Sotodlib, stabilizing the data-processing pipeline for edge cases and single-detector scenarios. Implemented cross-module bug fixes in demod_mapmaker, make_atomic_filterbin_map, and PCA modules to harden weight calculations, logging, and error handling, leading to more accurate data products and fewer pipeline failures.
1 Commits
Jun 1, 2025June 2025: Robustness and reliability improvements across Sotodlib, stabilizing the data-processing pipeline for edge cases and single-detector scenarios. Implemented cross-module bug fixes in demod_mapmaker, make_atomic_filterbin_map, and PCA modules to harden weight calculations, logging, and error handling, leading to more accurate data products and fewer pipeline failures.
June 2025
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 performance summary for simonsobs/sotodlib. Delivered a major refactor of the SAT demod mapmaker and expanded the atomic database, focused on robustness, performance, and maintainability. Modularized utility functions into a new utils module, expanded the atomic database with new fields, and refined the data processing pipeline to improve throughput and resilience. Updated tests and documentation to reflect the new structure and features. This work lays a stronger foundation for scalable mapmaking workflows and future feature enhancements.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 performance summary for simonsobs/sotodlib. Delivered a major refactor of the SAT demod mapmaker and expanded the atomic database, focused on robustness, performance, and maintainability. Modularized utility functions into a new utils module, expanded the atomic database with new fields, and refined the data processing pipeline to improve throughput and resilience. Updated tests and documentation to reflect the new structure and features. This work lays a stronger foundation for scalable mapmaking workflows and future feature enhancements.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for simonsobs/sotodlib focusing on Subscan-level TOD analysis in preprocessing. Implemented subscan processing to enable per-subscan statistics, power spectral densities (PSDs), and glitch detection, significantly enhancing data quality assessment and granularity for Time-Ordered Data pipelines. This work supports more robust data products and faster detection of data issues across TOD workflows. Key commit: cfc268f2a2f041b1aebffb6c825f0cc36689067a (Add subscan operations to preprocess, #1028).
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for simonsobs/sotodlib focusing on Subscan-level TOD analysis in preprocessing. Implemented subscan processing to enable per-subscan statistics, power spectral densities (PSDs), and glitch detection, significantly enhancing data quality assessment and granularity for Time-Ordered Data pipelines. This work supports more robust data products and faster detection of data issues across TOD workflows. Key commit: cfc268f2a2f041b1aebffb6c825f0cc36689067a (Add subscan operations to preprocess, #1028).
December 2024
Activity
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Quality Metrics
Correctness88.0%
Maintainability86.0%
Architecture88.0%
Performance80.0%
AI Usage24.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Astronomy Data ProcessingBug FixingData AnalysisData ProcessingDatabase ManagementMapmakingPythonPython programmingRefactoringSQLAlchemyScientific ComputingSignal ProcessingSoftware DevelopmentSoftware Engineeringdata analysis
Repositories Contributed To
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