CESGA-Quantum-Spain/cunqa
Nov 2025 – Nov 2025
1 Month active
Languages Used
C++CMakeNonePythonShell
Technical Skills
ASIO library usageC++C++ developmentCMakeCluster computingCode Maintenance
Jorge Vázquez
PROFILE
Jorge Vázquez
Jorge Vazquez Perez enhanced the CESGA-Quantum-Spain/cunqa repository by delivering core platform features that improved deployment reliability, simulation workflows, and job data management for quantum computing experiments. He integrated the CUNQA framework with the CiTIUS cluster, optimizing file paths and executables while refining JSON-based job handling. Using C++, Python, and CMake, Jorge streamlined build processes, incorporated the nlohmann_json library, and updated simulator submodules. He also improved SLURM job data management and network robustness by implementing IP selection based on interface speed. His work included targeted bug fixes and codebase cleanup, demonstrating depth in system programming, cluster integration, and code maintenance.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
8Total
Bugs
1
Commits
8
Features
5
Lines of code
1,310
Activity Months1
Your Network
12 peopleSame Organization
@usc.es1
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Jorge Vázquez PérezMember
martaMember
Work History
November 2025
8 Commits • 5 Features
Nov 1, 2025November 2025 performance summary for CESGA-Quantum-Spain/cunqa: Delivered core platform enhancements to improve deployment reliability, build and simulation workflows, job data management, network robustness, and quantum circuit handling. These changes reduce time-to-deploy, increase observability, and boost overall system resilience, directly supporting faster experimentation and production readiness.
8 Commits • 5 Features
Nov 1, 2025November 2025 performance summary for CESGA-Quantum-Spain/cunqa: Delivered core platform enhancements to improve deployment reliability, build and simulation workflows, job data management, network robustness, and quantum circuit handling. These changes reduce time-to-deploy, increase observability, and boost overall system resilience, directly supporting faster experimentation and production readiness.
November 2025
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Quality Metrics
Correctness90.0%
Maintainability85.0%
Architecture85.0%
Performance87.6%
AI Usage27.4%
Skills & Technologies
Programming Languages
C++CMakeNonePythonShell
Technical Skills
ASIO library usageC++C++ developmentCMakeCluster computingCode MaintenanceError handlingFile I/OJSON handlingNetwork programmingPython developmentPython programmingPython scriptingSLURM integrationShell scripting
Repositories Contributed To
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