qiboteam/qibo
Oct 2024 – Jul 2025
7 Months active
Languages Used
PythonRSTNumPySymPyC++ShellYAMLTOML
Technical Skills
API DesignDocumentationPythonQuantum ComputingSoftware RefactoringBackend Integration
BrunoLiegiBastonLiegi
PROFILE
Brunoliegibastonliegi
Andrea Papaluca contributed to the qiboteam/qibo repository by engineering core features and refactoring the symbolic Hamiltonian framework, focusing on backend-agnostic construction and efficient quantum circuit decoding. Leveraging Python, NumPy, and PyTorch, Andrea streamlined the decoding pipeline, improved measurement sampling, and standardized numerical precision across simulation components. Their work included enhancing test reliability for GPU and CPU backends, optimizing matrix operations with einsum, and enforcing consistent CI/CD environments. By integrating backend awareness and improving documentation, Andrea enabled more accurate, scalable quantum simulations and reduced maintenance overhead, demonstrating depth in backend development, numerical computing, and robust software engineering practices throughout the project.
Overall Statistics
Feature vs Bugs
61%Features
Repository Contributions
102Total
Bugs
15
Commits
102
Features
23
Lines of code
9,150
Activity Months7
Your Network
18 people
Work History
July 2025
18 Commits • 2 Features
Jul 1, 2025Monthly performance summary for 2025-07 focusing on key business value: delivered features, fixed critical bugs, improved numeric reliability, and overall impact for the qibo project.
18 Commits • 2 Features
Jul 1, 2025Monthly performance summary for 2025-07 focusing on key business value: delivered features, fixed critical bugs, improved numeric reliability, and overall impact for the qibo project.
July 2025
June 2025
5 Commits • 2 Features
Jun 1, 2025June 2025 monthly performance summary for qiboteam/qibo: delivered a major overhaul of quantum decoding, stabilized tests and data handling, and hardened CI/CD, driving reliability and efficiency in quantum circuit analysis and deployment. Key work streamlined the decoding pipeline, improved Hamiltonian data integrity, and aligned environments for consistent releases.
June 2025
5 Commits • 2 Features
Jun 1, 2025June 2025 monthly performance summary for qiboteam/qibo: delivered a major overhaul of quantum decoding, stabilized tests and data handling, and hardened CI/CD, driving reliability and efficiency in quantum circuit analysis and deployment. Key work streamlined the decoding pipeline, improved Hamiltonian data integrity, and aligned environments for consistent releases.
March 2025
11 Commits • 2 Features
Mar 1, 2025March 2025 — qiboteam/qibo: Concise monthly summary focusing on enhancements to the NumPy-backed execution path,GPU test reliability improvements, and dependency/build maintenance to support stable releases. Key features delivered: - NumpyBackend: enhanced binary conversion and sampling. Refactored samples_to_binary to use backend numpy (self.np), fixed qrange casting, and improved measurement sampling flow in NumpyBackend. Includes related bitflip and dtype simplifications for clarity. Commits: d603d1104cbc98b6f6dff2f777f2e89061668e05; 028de36339c29aac3990850d80f587829027b146; a79f4f92ab6d742089637325f810877dcccd7e3b; ba7fcb54bc8667a780fa04a35315bcf886c3c9d4. Major bugs fixed: - GPU backend test reliability and regression handling: Addressed flaky GPU tests by skipping regressions on cupy/cuquantum platforms, improving test stability and reliability across hardware backends. Commits: b246f6d6cc9bd51251c2d8cfd71f3c0f482a4143; c32551359776ed377a37f63618dd04957ca26eb3; 60b33e0f3e9a96a8abfe2dd623f2030650a9f62f; e14117f4ea1d6be0e2c0491752aa0dcf8549f580; 812b097223847767431bd12877594d301e099071. Dependencies and build configuration maintenance: - Updates to dependency lockfile and build configs to align with latest branches and stable versions (poetry.lock, dependencies, and main qibojit branch). Commits: 9d9922b96833b746470a2a596f549a9452a92722; 63167f52c1356e60bb45ee0144b44fce635719d0. Overall impact and accomplishments: - Improved measurement accuracy and back-end interoperability (CPU/GPU) leading to more reliable simulations and reduced debugging time. - Greater release confidence due to stable test results and synchronized dependencies across components. Technologies/skills demonstrated: - Python, NumPy backend integration, and backend-aware refactoring. - Testing strategy for flaky GPU tests, including selective regression skipping. - Dependency management and build configuration (poetry.lock, dependencies, main qibojit). - Cross-backend compatibility and performance-oriented refactoring.
11 Commits • 2 Features
Mar 1, 2025March 2025 — qiboteam/qibo: Concise monthly summary focusing on enhancements to the NumPy-backed execution path,GPU test reliability improvements, and dependency/build maintenance to support stable releases. Key features delivered: - NumpyBackend: enhanced binary conversion and sampling. Refactored samples_to_binary to use backend numpy (self.np), fixed qrange casting, and improved measurement sampling flow in NumpyBackend. Includes related bitflip and dtype simplifications for clarity. Commits: d603d1104cbc98b6f6dff2f777f2e89061668e05; 028de36339c29aac3990850d80f587829027b146; a79f4f92ab6d742089637325f810877dcccd7e3b; ba7fcb54bc8667a780fa04a35315bcf886c3c9d4. Major bugs fixed: - GPU backend test reliability and regression handling: Addressed flaky GPU tests by skipping regressions on cupy/cuquantum platforms, improving test stability and reliability across hardware backends. Commits: b246f6d6cc9bd51251c2d8cfd71f3c0f482a4143; c32551359776ed377a37f63618dd04957ca26eb3; 60b33e0f3e9a96a8abfe2dd623f2030650a9f62f; e14117f4ea1d6be0e2c0491752aa0dcf8549f580; 812b097223847767431bd12877594d301e099071. Dependencies and build configuration maintenance: - Updates to dependency lockfile and build configs to align with latest branches and stable versions (poetry.lock, dependencies, and main qibojit branch). Commits: 9d9922b96833b746470a2a596f549a9452a92722; 63167f52c1356e60bb45ee0144b44fce635719d0. Overall impact and accomplishments: - Improved measurement accuracy and back-end interoperability (CPU/GPU) leading to more reliable simulations and reduced debugging time. - Greater release confidence due to stable test results and synchronized dependencies across components. Technologies/skills demonstrated: - Python, NumPy backend integration, and backend-aware refactoring. - Testing strategy for flaky GPU tests, including selective regression skipping. - Dependency management and build configuration (poetry.lock, dependencies, main qibojit). - Cross-backend compatibility and performance-oriented refactoring.
March 2025
February 2025
25 Commits • 7 Features
Feb 1, 2025February 2025: Delivered key features, stabilized GPU-accelerated test stacks, and hardened the build/test infrastructure for reliability and faster releases.
February 2025
25 Commits • 7 Features
Feb 1, 2025February 2025: Delivered key features, stabilized GPU-accelerated test stacks, and hardened the build/test infrastructure for reliability and faster releases.
January 2025
30 Commits • 6 Features
Jan 1, 2025January 2025: Strengthened the symbolic backend ecosystem in qibo by integrating backend awareness across symbols and symbolic terms, improving correctness and consistency in symbol/backend interactions. Delivered meaningful performance gains through einsum-based optimizations in symbolic term matrix operations, including cast removals and caching improvements. Hardened backend consistency for symbolic Hamiltonian terms and stabilized the test environment to improve CI reliability. Expanded test coverage with dense conversion scenarios and intensified Cupy usage support, while refining numpy dtype handling. Added workflow and build tooling improvements to support reliable artifact uploads and dependency updates. Overall impact: higher correctness, faster execution of symbolic components, and more robust deployment pipelines across diverse hardware stacks.
30 Commits • 6 Features
Jan 1, 2025January 2025: Strengthened the symbolic backend ecosystem in qibo by integrating backend awareness across symbols and symbolic terms, improving correctness and consistency in symbol/backend interactions. Delivered meaningful performance gains through einsum-based optimizations in symbolic term matrix operations, including cast removals and caching improvements. Hardened backend consistency for symbolic Hamiltonian terms and stabilized the test environment to improve CI reliability. Expanded test coverage with dense conversion scenarios and intensified Cupy usage support, while refining numpy dtype handling. Added workflow and build tooling improvements to support reliable artifact uploads and dependency updates. Overall impact: higher correctness, faster execution of symbolic components, and more robust deployment pipelines across diverse hardware stacks.
January 2025
December 2024
11 Commits • 2 Features
Dec 1, 2024December 2024: Delivered a major Symbolic Hamiltonian core refactor for qibo, enabling backend-agnostic symbolic construction and robust dense-term handling; improved qubit derivation, caching, and density calculations. Implemented plotting API standardization for consistency across modules. Result: more accurate, scalable simulations (TFIM/Heisenberg/Pauli), easier backend extension, and reduced maintenance cost. Business value includes faster feature delivery, more reliable simulations, and improved developer experience.
December 2024
11 Commits • 2 Features
Dec 1, 2024December 2024: Delivered a major Symbolic Hamiltonian core refactor for qibo, enabling backend-agnostic symbolic construction and robust dense-term handling; improved qubit derivation, caching, and density calculations. Implemented plotting API standardization for consistency across modules. Result: more accurate, scalable simulations (TFIM/Heisenberg/Pauli), easier backend extension, and reduced maintenance cost. Business value includes faster feature delivery, more reliable simulations, and improved developer experience.
October 2024
2 Commits • 2 Features
Oct 1, 2024Month: 2024-10 — qiboteam/qibo. Focused on documentation accuracy, API clarity, and artifact hygiene to improve onboarding and developer experience. Key achievements: - Documentation: Corrected Z Hamiltonian import in advanced examples; import now from qibo.hamiltonians and removed final_result.npy artifact. Commit ea570bf8a7b52025e49a726a6df5beea62b9273b. - SymbolicHamiltonian API: Added expectation_from_circuit as a separate method from expectation_from_samples to improve API clarity and usability. Commit f9943d75d4f158e5616d781f61eb93f5ad221d76. Impact and business value: - Documentation accuracy and artifact integrity improved, reducing user confusion and support overhead. - API surface clarified, accelerating user adoption and reducing time-to-value for new features. Technologies/skills demonstrated: - Python, API design and refactoring, documentation practices, and version control hygiene; cross-team collaboration with docs and API teams.
2 Commits • 2 Features
Oct 1, 2024Month: 2024-10 — qiboteam/qibo. Focused on documentation accuracy, API clarity, and artifact hygiene to improve onboarding and developer experience. Key achievements: - Documentation: Corrected Z Hamiltonian import in advanced examples; import now from qibo.hamiltonians and removed final_result.npy artifact. Commit ea570bf8a7b52025e49a726a6df5beea62b9273b. - SymbolicHamiltonian API: Added expectation_from_circuit as a separate method from expectation_from_samples to improve API clarity and usability. Commit f9943d75d4f158e5616d781f61eb93f5ad221d76. Impact and business value: - Documentation accuracy and artifact integrity improved, reducing user confusion and support overhead. - API surface clarified, accelerating user adoption and reducing time-to-value for new features. Technologies/skills demonstrated: - Python, API design and refactoring, documentation practices, and version control hygiene; cross-team collaboration with docs and API teams.
October 2024
Activity
Loading activity data...
Quality Metrics
Correctness87.2%
Maintainability86.4%
Architecture82.8%
Performance78.4%
AI Usage20.8%
Skills & Technologies
Programming Languages
C++NumPyPythonRSTShellSymPyTOMLYAMLpython
Technical Skills
API DesignAlgorithm ImplementationBackend DevelopmentBackend IntegrationBuild AutomationBuild ConfigurationBuild ManagementBuild ToolsCI/CDCircuit ConstructionCircuit ModelingCircuit TranspilationCode CleanupCode CommentingCode Coverage
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline