Classiq/classiq-library
Jul 2025 – Jul 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
BenchmarkingCloud ComputingCode RefactoringDocumentation UpdateJupyter NotebooksQuantum Computing
karamsg
PROFILE
Karamsg
Worked on enhancing the Classiq/classiq-library repository by upgrading the Quantum Volume benchmarking notebook to support IBM Cloud quantum computers, focusing on ibm_fez, ibm_marrakesh, and ibm_sherbrooke. Used Python and Jupyter Notebooks to introduce new configurations and code cells, enabling cloud-based benchmarking while improving portability. Refactored the codebase to remove IBM-specific references, broadening applicability to other providers and reducing vendor lock-in. Addressed rendering issues in notebook outputs by correcting escape sequences, ensuring accurate display of progress bars and terminal output. The work emphasized benchmarking, code refactoring, and documentation updates, resulting in improved maintainability and cross-provider benchmarking readiness.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
3Total
Bugs
2
Commits
3
Features
1
Lines of code
672
Activity Months1
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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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