sandialabs/pyGSTi
Nov 2024 – Aug 2025
9 Months active
Languages Used
PythonJSONJupyter Notebook
Technical Skills
Algorithm DevelopmentCircuit CompilationQuantum ComputingSoftware EngineeringCode CleanupCode Organization
Noah Siekierski
PROFILE
Noah Siekierski
Nick Siekierski developed and maintained advanced quantum circuit compilation and analysis tools in the sandialabs/pyGSTi repository, focusing on robust interoperability with Qiskit and streamlined MCFE workflows. He engineered reusable Python modules for circuit conversion, fidelity estimation, and data processing, emphasizing modularity and maintainability through object-oriented design and comprehensive unit testing. His work included API evolution, algorithm refinement, and extensive documentation, addressing both feature expansion and bug resolution. By integrating data analysis pipelines and enhancing compatibility across Python and Qiskit versions, Nick enabled reproducible, end-to-end quantum experiments, demonstrating depth in backend development, scientific computing, and cross-framework integration.
Overall Statistics
Feature vs Bugs
61%Features
Repository Contributions
41Total
Bugs
11
Commits
41
Features
17
Lines of code
14,440
Activity Months9
Your Network
79 people
Work History
August 2025
27 Commits • 8 Features
Aug 1, 2025Concise monthly summary for August 2025 focused on delivering business value through feature evolution, reliability improvements, and code quality enhancements. Highlights include the B-Sqale API evolution and tooling integration, targeted bug fixes that stabilize calculations and data handling, and a strengthened testing/documentation baseline to reduce risk in future iterations. The initiatives below reflect a balanced emphasis on user-facing capabilities, maintainability, and ecosystem compatibility.
27 Commits • 8 Features
Aug 1, 2025Concise monthly summary for August 2025 focused on delivering business value through feature evolution, reliability improvements, and code quality enhancements. Highlights include the B-Sqale API evolution and tooling integration, targeted bug fixes that stabilize calculations and data handling, and a strengthened testing/documentation baseline to reduce risk in future iterations. The initiatives below reflect a balanced emphasis on user-facing capabilities, maintainability, and ecosystem compatibility.
August 2025
July 2025
2 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for sandialabs/pyGSTi: Delivered focused enhancements to quantum circuit conversion/transpilation with Qiskit integration and reinforced robustness of mirror design and circuit compilation, directly boosting experimental reliability and research throughput. The work enabled more accurate circuit generation, improved sampling and data capture for analysis, and stronger guardrails on numerical estimates and qubit mapping. These changes align with MCFE paper objectives and enhance the overall impact of the project in terms of reproducibility, collaboration readiness, and technical leadership.
July 2025
2 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for sandialabs/pyGSTi: Delivered focused enhancements to quantum circuit conversion/transpilation with Qiskit integration and reinforced robustness of mirror design and circuit compilation, directly boosting experimental reliability and research throughput. The work enabled more accurate circuit generation, improved sampling and data capture for analysis, and stronger guardrails on numerical estimates and qubit mapping. These changes align with MCFE paper objectives and enhance the overall impact of the project in terms of reproducibility, collaboration readiness, and technical leadership.
June 2025
2 Commits • 2 Features
Jun 1, 2025June 2025 — sandialabs/pyGSTi: Delivered core enhancements to MCFE data processing and cross-framework circuit work, strengthening end-to-end fidelity analysis pipelines and interoperability with Qiskit. Key features delivered: - MCFE Data Processing and Bootstrapping: Added end-to-end fidelity calculations with bootstrap-based error estimation, refactored into reusable functions, and introduced a VBDataFrame-based processing path for standardized MCFE data handling. - PyGSTi-Qiskit Circuit Conversion and Subcircuit Sampling Enhancements: Improved circuit conversion interoperability between pyGSTi and Qiskit, including conversion of pyGSTi circuits to Qiskit and enhanced subcircuit sampling strategies. Major bugs fixed: - No critical bugs reported this month; focus remained on feature delivery and interoperability improvements. Overall impact and accomplishments: - Accelerated MCFE analysis pipeline with robust error estimates, reducing manual data wrangling and enabling faster decision-making. - Strengthened cross-tool workflows, enabling end-to-end experiments from pyGSTi to Qiskit representations and back. - Laid groundwork for scaling MCFE experiments through modular, reusable code and notebooks. Technologies/skills demonstrated: - Python, data processing with dataframes, bootstrapping for error estimation, modular refactoring, VBDataFrame usage, circuit conversion, subcircuit sampling, and notebook-to-functionization workflows. Commit highlights: - 57c78536f265afdadccce769fa093891f4118dd6 — Factor MCFE VB process fidelity calculations into pyGSTi - 9ad4941b28114b8559d6b381e5a53611663d4917 — Preliminary functionizations of notebooks for fullstack, subcirc, and vanilla MCFE
2 Commits • 2 Features
Jun 1, 2025June 2025 — sandialabs/pyGSTi: Delivered core enhancements to MCFE data processing and cross-framework circuit work, strengthening end-to-end fidelity analysis pipelines and interoperability with Qiskit. Key features delivered: - MCFE Data Processing and Bootstrapping: Added end-to-end fidelity calculations with bootstrap-based error estimation, refactored into reusable functions, and introduced a VBDataFrame-based processing path for standardized MCFE data handling. - PyGSTi-Qiskit Circuit Conversion and Subcircuit Sampling Enhancements: Improved circuit conversion interoperability between pyGSTi and Qiskit, including conversion of pyGSTi circuits to Qiskit and enhanced subcircuit sampling strategies. Major bugs fixed: - No critical bugs reported this month; focus remained on feature delivery and interoperability improvements. Overall impact and accomplishments: - Accelerated MCFE analysis pipeline with robust error estimates, reducing manual data wrangling and enabling faster decision-making. - Strengthened cross-tool workflows, enabling end-to-end experiments from pyGSTi to Qiskit representations and back. - Laid groundwork for scaling MCFE experiments through modular, reusable code and notebooks. Technologies/skills demonstrated: - Python, data processing with dataframes, bootstrapping for error estimation, modular refactoring, VBDataFrame usage, circuit conversion, subcircuit sampling, and notebook-to-functionization workflows. Commit highlights: - 57c78536f265afdadccce769fa093891f4118dd6 — Factor MCFE VB process fidelity calculations into pyGSTi - 9ad4941b28114b8559d6b381e5a53611663d4917 — Preliminary functionizations of notebooks for fullstack, subcirc, and vanilla MCFE
June 2025
May 2025
1 Commits
May 1, 2025May 2025: Delivered a targeted bug fix in pyGSTi to improve debugging clarity for reference circuit matching. No new features released this month; the primary effort focused on correcting an assertion message in mirror_edesign so that mismatches report the correct test ID, reducing debugging time and the risk of misinterpretation during validation.
May 2025
1 Commits
May 1, 2025May 2025: Delivered a targeted bug fix in pyGSTi to improve debugging clarity for reference circuit matching. No new features released this month; the primary effort focused on correcting an assertion message in mirror_edesign so that mismatches report the correct test ID, reducing debugging time and the risk of misinterpretation during validation.
March 2025
2 Commits • 2 Features
Mar 1, 2025March 2025 performance summary: Delivered integrated Qiskit-to-pyGSTi circuit conversion and IBMQ-centered workflow enhancements in sandialabs/pyGSTi. Key features include the Circuit.from_qiskit method for converting Qiskit QuantumCircuit objects to pyGSTi Circuit objects, handling qubit mapping, gate conversion, and layer management; this functionality is now integrated into the Circuit class, consolidating logic and removing the previous standalone qiskit_to_pygsti.py script. Also released an MCFE notebook for IBMQ circuits that demonstrates end-to-end usage of pyGSTi with IBMQ, along with bug fixes related to IBMQ interfacing and circuit line ordering to improve accuracy and usability. Major bugs fixed: IBMQ interfacing issues and line ordering problems, leading to more reliable circuit assessments. Overall impact: streamlined the end-to-end workflow from circuit construction to model evaluation, reduced maintenance by centralizing conversion logic, and improved accuracy of IBMQ-based experiments. Technologies/skills demonstrated: Python object-oriented design, circuit representation, Jupyter notebook workflows, IBMQ interfacing, and code refactoring for maintainability. Business value: accelerates experimentation, reduces manual conversion effort, and enhances reliability of circuit preparation and evaluation workflows.
2 Commits • 2 Features
Mar 1, 2025March 2025 performance summary: Delivered integrated Qiskit-to-pyGSTi circuit conversion and IBMQ-centered workflow enhancements in sandialabs/pyGSTi. Key features include the Circuit.from_qiskit method for converting Qiskit QuantumCircuit objects to pyGSTi Circuit objects, handling qubit mapping, gate conversion, and layer management; this functionality is now integrated into the Circuit class, consolidating logic and removing the previous standalone qiskit_to_pygsti.py script. Also released an MCFE notebook for IBMQ circuits that demonstrates end-to-end usage of pyGSTi with IBMQ, along with bug fixes related to IBMQ interfacing and circuit line ordering to improve accuracy and usability. Major bugs fixed: IBMQ interfacing issues and line ordering problems, leading to more reliable circuit assessments. Overall impact: streamlined the end-to-end workflow from circuit construction to model evaluation, reduced maintenance by centralizing conversion logic, and improved accuracy of IBMQ-based experiments. Technologies/skills demonstrated: Python object-oriented design, circuit representation, Jupyter notebook workflows, IBMQ interfacing, and code refactoring for maintainability. Business value: accelerates experimentation, reduces manual conversion effort, and enhances reliability of circuit preparation and evaluation workflows.
March 2025
February 2025
3 Commits • 2 Features
Feb 1, 2025February 2025 summary for sandialabs/pyGSTi. Key feature deliveries and testing enhancements focused on enabling easier integration with Qiskit and increasing reliability of circuit compilation under varied error scenarios. No major bug fixes recorded this month. Highlights include a Qiskit-to-pygsti circuit conversion utility and substantial RandomCompilation testing enhancements, accompanied by refactoring to support test layers and broaden gate-type coverage.
February 2025
3 Commits • 2 Features
Feb 1, 2025February 2025 summary for sandialabs/pyGSTi. Key feature deliveries and testing enhancements focused on enabling easier integration with Qiskit and increasing reliability of circuit compilation under varied error scenarios. No major bug fixes recorded this month. Highlights include a Qiskit-to-pygsti circuit conversion utility and substantial RandomCompilation testing enhancements, accompanied by refactoring to support test layers and broaden gate-type coverage.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for sandialabs/pyGSTi. Primary focus was unifying the Random Pauli compilation workflow and refactoring for reuse, setting the stage for easier extension of randomization strategies and more reliable experimentation. Key change: introduction of the RandomCompilation class and refactor to have make_mirror_edesign use this class for both pauli_rc and central_pauli strategies. Commit referenced: b89d1e262cef40b87ad4a700cb1aec68d30c844e. This work improves maintainability, reduces duplication, and supports consistent behavior across strategies, enabling faster iteration and more robust results. No explicit major bug fixes were documented in this dataset for January 2025.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for sandialabs/pyGSTi. Primary focus was unifying the Random Pauli compilation workflow and refactoring for reuse, setting the stage for easier extension of randomization strategies and more reliable experimentation. Key change: introduction of the RandomCompilation class and refactor to have make_mirror_edesign use this class for both pauli_rc and central_pauli strategies. Commit referenced: b89d1e262cef40b87ad4a700cb1aec68d30c844e. This work improves maintainability, reduces duplication, and supports consistent behavior across strategies, enabling faster iteration and more robust results. No explicit major bug fixes were documented in this dataset for January 2025.
January 2025
December 2024
2 Commits
Dec 1, 2024December 2024: Improved codebase health for sandialabs/pyGSTi by resolving a circular import and removing dead code, reducing maintenance risk and enabling faster feature work.
December 2024
2 Commits
Dec 1, 2024December 2024: Improved codebase health for sandialabs/pyGSTi by resolving a circular import and removing dead code, reducing maintenance risk and enabling faster feature work.
November 2024
1 Commits • 1 Features
Nov 1, 2024Monthly work summary for 2024-11 focusing on pyGSTi development. This month centered on groundwork for MCFE integration by extending subcircuit selection, processor utilities, and circuit analysis components. A targeted branch was created to prototype MCFE utilities and facilitate future integration, laying the foundation for enhanced circuit manipulation, analysis, and compilation workflows.
1 Commits • 1 Features
Nov 1, 2024Monthly work summary for 2024-11 focusing on pyGSTi development. This month centered on groundwork for MCFE integration by extending subcircuit selection, processor utilities, and circuit analysis components. A targeted branch was created to prototype MCFE utilities and facilitate future integration, laying the foundation for enhanced circuit manipulation, analysis, and compilation workflows.
November 2024
Activity
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Quality Metrics
Correctness88.4%
Maintainability88.2%
Architecture82.8%
Performance73.8%
AI Usage20.4%
Skills & Technologies
Programming Languages
JSONJupyter NotebookPython
Technical Skills
API DesignAPI DevelopmentAPI IntegrationAlgorithm DevelopmentAlgorithm ImplementationAlgorithm RefinementBackend DevelopmentBug FixingCircuit CompilationCircuit ConversionCircuit DesignCircuit SimulationClass InheritanceCode CleanupCode Documentation
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