Classiq/classiq-library
Mar 2026 – Jun 2026
2 Months active
Languages Used
PythonJSON
Technical Skills
algorithm designdata analysisquantum computingJupyter NotebookJupyter NotebooksNumPy
Maya Baruch
PROFILE
Maya Baruch
Worked on the Classiq/classiq-library repository, focusing on quantum algorithm optimization and reliability. Addressed a degeneration bug in the Traveling Salesman Problem route derivation by introducing a defensive default, which stabilized route calculations and reduced downstream errors. Delivered resource-optimized quantum algorithm improvements by refining auxiliary qubit allocation and tuning QSVT synthesis parameters, enhancing performance and efficiency. Improved the correctness and robustness of Jupyter Notebook tutorials by fixing iteration type casting and restoring test coverage, particularly for the Alice and Bob example. Utilized Python, NumPy, and quantum computing frameworks to ensure more reliable model deployments and a smoother onboarding experience for users.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
6Total
Bugs
2
Commits
6
Features
1
Lines of code
45
Activity Months2
Your Network
87 peopleShared Repositories
54
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Work History
June 2026
5 Commits • 1 Features
Jun 1, 2026June 2026 monthly summary for Classiq/classiq-library: delivered resource-optimized quantum algorithm improvements and fixed notebook correctness for tutorials, contributing to better performance and reliability with expanded test coverage.
5 Commits • 1 Features
Jun 1, 2026June 2026 monthly summary for Classiq/classiq-library: delivered resource-optimized quantum algorithm improvements and fixed notebook correctness for tutorials, contributing to better performance and reliability with expanded test coverage.
June 2026
March 2026
1 Commits
Mar 1, 2026March 2026: Stabilized Traveling Salesman Problem routing in Classiq/library by fixing a degeneration bug in the TSP route derivation. Implemented a defensive default (0) when no indices are found, ensuring robust route calculations and preventing downstream errors. Result: more reliable quantum-inspired routing outputs, reduced manual triage, and improved customer trust in model deployments.
March 2026
1 Commits
Mar 1, 2026March 2026: Stabilized Traveling Salesman Problem routing in Classiq/library by fixing a degeneration bug in the TSP route derivation. Implemented a defensive default (0) when no indices are found, ensuring robust route calculations and preventing downstream errors. Result: more reliable quantum-inspired routing outputs, reduced manual triage, and improved customer trust in model deployments.
Activity
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Quality Metrics
Correctness96.6%
Maintainability83.4%
Architecture83.4%
Performance86.6%
AI Usage43.4%
Skills & Technologies
Programming Languages
JSONPython
Technical Skills
Jupyter NotebookJupyter NotebooksNumPyPythonQMODQuantum ComputingTestingalgorithm designalgorithm optimizationcryptographydata analysisdata visualizationquantum computing
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