NVIDIA/cuda-quantum
Aug 2025 – Oct 2025
2 Months active
Languages Used
C++PythonRSTShell
Technical Skills
C++C++ DevelopmentCompiler DevelopmentMLIRPython DevelopmentQuantum Computing
Adam T. Geller
PROFILE
Adam T. Geller
Adam Geller contributed to NVIDIA/cuda-quantum by developing a simulator-based resource counting system that replaced the previous estimate_resources method, enabling precise tracking of qubit allocations and gate usage for quantum workload planning. He refactored kernel execution to support remote simulators, adding comprehensive tests to ensure correctness across local and remote environments. Adam also implemented a phase folding optimization for Rz gate consolidation, reducing circuit gate counts through an environment-controlled feature. His work leveraged C++, MLIR, and Python, demonstrating depth in compiler development, algorithm design, and quantum computing, and resulted in improved accuracy, scalability, and reproducibility for quantum resource estimation and circuit optimization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
4,731
Activity Months2
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — NVIDIA/cuda-quantum: Phase Folding Optimization for Rz Gate Consolidation delivered; introduced an environment-flag controlled optimization reducing gate count, with new tests and validation utilities. No major bugs fixed this period; overall impact includes improved circuit efficiency and test coverage; demonstrates CUDA-quantum stack proficiency, testing discipline, and environment-driven features.
1 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — NVIDIA/cuda-quantum: Phase Folding Optimization for Rz Gate Consolidation delivered; introduced an environment-flag controlled optimization reducing gate count, with new tests and validation utilities. No major bugs fixed this period; overall impact includes improved circuit efficiency and test coverage; demonstrates CUDA-quantum stack proficiency, testing discipline, and environment-driven features.
October 2025
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 performance summary for NVIDIA/cuda-quantum focused on enhancing resource estimation capabilities and enabling remote experimentation. Delivered a simulator-based resource counting system that replaces the previous estimate_resources approach, added a conditional function to handle measurement-based branching, and refactored kernel execution to support remote simulators with accompanying tests to validate correctness across local and remote environments. These changes significantly improve accuracy, scalability, and reproducibility for quantum workload planning.
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 performance summary for NVIDIA/cuda-quantum focused on enhancing resource estimation capabilities and enabling remote experimentation. Delivered a simulator-based resource counting system that replaces the previous estimate_resources approach, added a conditional function to handle measurement-based branching, and refactored kernel execution to support remote simulators with accompanying tests to validate correctness across local and remote environments. These changes significantly improve accuracy, scalability, and reproducibility for quantum workload planning.
Activity
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Quality Metrics
Correctness86.6%
Maintainability83.4%
Architecture86.6%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++PythonRSTShell
Technical Skills
Algorithm DesignC++C++ DevelopmentCompiler DevelopmentCompiler OptimizationMLIRPython DevelopmentQuantum ComputingRemote SystemsTesting
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