Classiq/classiq-library
Jul 2025 – Jul 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
BenchmarkingCloud ComputingCode RefactoringDocumentation UpdateJupyter NotebooksQuantum Computing
karamsg
PROFILE
Karamsg
Karam enhanced the Classiq/classiq-library repository by upgrading its Jupyter notebook to support Quantum Volume benchmarking on IBM Cloud quantum computers, specifically targeting ibm_fez, ibm_marrakesh, and ibm_sherbrooke. Using Python and Markdown, Karam refactored the code to decouple IBM-specific configurations, broadening the notebook’s applicability to other quantum providers and reducing vendor lock-in. The work included fixing escape sequence rendering issues to ensure accurate progress bar and terminal output display within the notebook. This focused, month-long effort improved the maintainability and portability of benchmarking workflows, demonstrating depth in cloud computing, benchmarking, and code refactoring within quantum computing environments.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
3Total
Bugs
2
Commits
3
Features
1
Lines of code
672
Activity Months1
Your Network
80 people
Work History
July 2025
3 Commits • 1 Features
Jul 1, 2025July 2025: Delivered targeted notebook enhancements in Classiq/classiq-library to broaden benchmarking capabilities, improve portability, and ensure robust notebook outputs. The work focused on enabling IBM Cloud Quantum Volume benchmarking, decoupling IBM-specific configurations to broaden provider applicability, and fixing rendering issues in notebook outputs, driving business value through cross-provider support, reliability, and maintainability.
3 Commits • 1 Features
Jul 1, 2025July 2025: Delivered targeted notebook enhancements in Classiq/classiq-library to broaden benchmarking capabilities, improve portability, and ensure robust notebook outputs. The work focused on enabling IBM Cloud Quantum Volume benchmarking, decoupling IBM-specific configurations to broaden provider applicability, and fixing rendering issues in notebook outputs, driving business value through cross-provider support, reliability, and maintainability.
July 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
BenchmarkingCloud ComputingCode RefactoringDocumentation UpdateJupyter NotebooksQuantum Computing
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