sandialabs/pyGSTi
Dec 2024 – Aug 2025
4 Months active
Languages Used
Python
Technical Skills
Bug FixBug FixingCode RefactoringError MitigationLinear AlgebraNumerical Analysis
Erik Nielsen
PROFILE
Erik Nielsen
Over four months, Michael Nielsen enhanced the sandialabs/pyGSTi repository by developing and refining features that improve quantum experiment analysis and reliability. He implemented robust experiment design merging, advanced Clifford compilation strategies, and flexible badfit estimation for GateSetTomography, addressing edge cases where gauge optimization is unavailable. His work included targeted bug fixes in DataFrame export, Hessian computations, and error handling, ensuring stability across diverse NumPy and pandas versions. Using Python, NumPy, and Pandas, Michael applied algorithm development, code refactoring, and scientific computing skills to deliver maintainable solutions that streamline quantum circuit workflows and reduce user-facing errors in research environments.
Overall Statistics
Feature vs Bugs
40%Features
Repository Contributions
15Total
Bugs
6
Commits
15
Features
4
Lines of code
371
Activity Months4
Your Network
16 people
Work History
August 2025
1 Commits
Aug 1, 2025August 2025 (sandialabs/pyGSTi): Focused on stability and reliability of data export workflows. No new features were released this month; major effort centered on a critical bug fix to ensure smooth DataFrame conversions from results. This work reduces user-facing errors and improves downstream analysis workflows.
1 Commits
Aug 1, 2025August 2025 (sandialabs/pyGSTi): Focused on stability and reliability of data export workflows. No new features were released this month; major effort centered on a critical bug fix to ensure smooth DataFrame conversions from results. This work reduces user-facing errors and improves downstream analysis workflows.
August 2025
June 2025
4 Commits • 1 Features
Jun 1, 2025June 2025: Delivered reliability and performance improvements in pyGSTi. Key bug fixes: wildcard budget error handling (ValueError), clearer messages for missing gates, and qubit label typing corrections. Clifford compilation enhancements: added a compilation template hook and implemented CNOT via iSWAP and pi/2 with improved progress feedback. Impact: more stable simulations, reduced debugging time, and smoother long-running compilations, enabling researchers to iterate faster on quantum circuits. Technologies demonstrated: Python code quality, error handling, type discipline, and Clifford-aware compilation strategies.
June 2025
4 Commits • 1 Features
Jun 1, 2025June 2025: Delivered reliability and performance improvements in pyGSTi. Key bug fixes: wildcard budget error handling (ValueError), clearer messages for missing gates, and qubit label typing corrections. Clifford compilation enhancements: added a compilation template hook and implemented CNOT via iSWAP and pi/2 with improved progress feedback. Impact: more stable simulations, reduced debugging time, and smoother long-running compilations, enabling researchers to iterate faster on quantum circuits. Technologies demonstrated: Python code quality, error handling, type discipline, and Clifford-aware compilation strategies.
February 2025
5 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for sandialabs/pyGSTi focusing on delivering robust experiment design capabilities, improving model/metrics handling, and strengthening robustness across NumPy versions. The month emphasizes business value through reliable design composition, clearer error handling, and broader model support.
5 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for sandialabs/pyGSTi focusing on delivering robust experiment design capabilities, improving model/metrics handling, and strengthening robustness across NumPy versions. The month emphasizes business value through reliable design composition, clearer error handling, and broader model support.
February 2025
December 2024
5 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for sandialabs/pyGSTi. Focused on strengthening reliability and business value of GST analysis through robust feature delivery and targeted bug fixes that preserve analysis viability in constrained environments. Key outcomes include enabling badfit estimation in GateSetTomography when gaugeopt is unavailable, hardening Hessian computations for multi-atom layouts, and improving list slicing robustness to prevent serialization-related crashes. These changes contribute to more accurate uncertainty quantification, smoother optimization workflows, and higher overall stability across the toolkit.
December 2024
5 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for sandialabs/pyGSTi. Focused on strengthening reliability and business value of GST analysis through robust feature delivery and targeted bug fixes that preserve analysis viability in constrained environments. Key outcomes include enabling badfit estimation in GateSetTomography when gaugeopt is unavailable, hardening Hessian computations for multi-atom layouts, and improving list slicing robustness to prevent serialization-related crashes. These changes contribute to more accurate uncertainty quantification, smoother optimization workflows, and higher overall stability across the toolkit.
Activity
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Quality Metrics
Correctness89.4%
Maintainability88.0%
Architecture83.4%
Performance77.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API DesignAlgorithm DevelopmentBasis RepresentationBug FixBug FixingCode RefactoringData AnalysisData ManipulationError HandlingError MitigationLinear AlgebraModel DevelopmentNumPyNumerical AnalysisNumerical Computation
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