Classiq/classiq-library
Nov 2025 – Nov 2025
1 Month active
Languages Used
Python
Technical Skills
Pythonasynchronous programmingdata analysisnotebook developmentquantum computingtesting
Nathan Abramov
PROFILE
Nathan Abramov
Nathan enhanced the Classiq/classiq-library repository by delivering targeted improvements to the quantum benchmarking notebook. He refactored the randomized benchmarking workflow to adopt qmod-based gate definitions and execution preferences, replacing legacy library functions to improve clarity and reproducibility. By removing the deprecated SX import, Nathan streamlined dependencies and reduced potential runtime errors, supporting more reliable benchmarking for both customers and internal QA. His work leveraged Python, asynchronous programming, and data analysis skills to align the notebook with updated benchmarking processes. The changes simplified future maintenance and contributed to more consistent benchmarking results, demonstrating thoughtful engineering within a focused project scope.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
97
Activity Months1
Your Network
80 people
Work History
November 2025
2 Commits • 1 Features
Nov 1, 20252025-11 Monthly Summary for Classiq/classiq-library: Delivered targeted Quantum Benchmarking Notebook Enhancements that align the workflow with qmod-based gate definitions and execution preferences, improving clarity, reliability, and benchmarking reproducibility. Dependency cleanup was performed by removing the SX import, reflecting the updated benchmarking process and reducing maintenance overhead. These changes strengthen notebook reliability, simplify future maintenance, and support more consistent benchmarking results for customers and internal QA.
2 Commits • 1 Features
Nov 1, 20252025-11 Monthly Summary for Classiq/classiq-library: Delivered targeted Quantum Benchmarking Notebook Enhancements that align the workflow with qmod-based gate definitions and execution preferences, improving clarity, reliability, and benchmarking reproducibility. Dependency cleanup was performed by removing the SX import, reflecting the updated benchmarking process and reducing maintenance overhead. These changes strengthen notebook reliability, simplify future maintenance, and support more consistent benchmarking results for customers and internal QA.
November 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Pythonasynchronous programmingdata analysisnotebook developmentquantum computingtesting
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