cda-tum/mqt-core
May 2025 – Oct 2025
6 Months active
Languages Used
C++CMakeMLIRMarkdownPythonLLVM IR
Technical Skills
Algorithm DesignC++ DevelopmentQuantum ComputingSoftware RefactoringUnit TestingC++
matthias
PROFILE
Matthias
Matthias Reumann contributed to the cda-tum/mqt-core repository by engineering core features for quantum circuit compilation and simulation. Over six months, he developed scalable decision diagram approximation, centralized quantum state generation, and advanced memory management through a mark-and-sweep garbage collector. His work included refactoring state creation APIs, implementing MLIR dialect enhancements, and introducing robust routing algorithms such as MLIR-based QMAP and A*-search. Using C++, MLIR, and Python, Matthias focused on maintainable code organization, reproducible testing, and efficient memory usage. The depth of his contributions improved reliability, scalability, and architectural flexibility for quantum computing workflows within the mqt-core project.
Overall Statistics
Feature vs Bugs
90%Features
Repository Contributions
16Total
Bugs
1
Commits
16
Features
9
Lines of code
16,046
Activity Months6
Your Network
129 people
Work History
October 2025
3 Commits • 2 Features
Oct 1, 20252025-10 focused on delivering high-impact routing improvements for cda-tum/mqt-core. Key outcomes include MLIR-based QMAP routing with Layerizer/Planner, memory-efficient ThinLayout, and an A*-routing refactor; plus a new --arch option for MLIR routing to target IBM Falcon with propagated settings and updated tests. These changes yield faster, more memory-efficient circuit mapping and broader architectural support, directly enabling larger designs and improved operational efficiency.
3 Commits • 2 Features
Oct 1, 20252025-10 focused on delivering high-impact routing improvements for cda-tum/mqt-core. Key outcomes include MLIR-based QMAP routing with Layerizer/Planner, memory-efficient ThinLayout, and an A*-routing refactor; plus a new --arch option for MLIR routing to target IBM Falcon with propagated settings and updated tests. These changes yield faster, more memory-efficient circuit mapping and broader architectural support, directly enabling larger designs and improved operational efficiency.
October 2025
September 2025
3 Commits • 1 Features
Sep 1, 2025September 2025: cda-tum/mqt-core — Delivered primary MLIR quantum circuit routing and placement enhancements, including a naive mapping algorithm, robustness improvements in the routing pass via standardized entry-point checks, and a dedicated PlacementPass that splits routing into placement and routing steps, while supporting static qubit replacement, initial placement generation, and extended control-flow constructs. Also completed refactors of Common.h and Layout.h for better organization.
September 2025
3 Commits • 1 Features
Sep 1, 2025September 2025: cda-tum/mqt-core — Delivered primary MLIR quantum circuit routing and placement enhancements, including a naive mapping algorithm, robustness improvements in the routing pass via standardized entry-point checks, and a dedicated PlacementPass that splits routing into placement and routing steps, while supporting static qubit replacement, initial placement generation, and extended control-flow constructs. Also completed refactors of Common.h and Layout.h for better organization.
August 2025
3 Commits • 2 Features
Aug 1, 2025August 2025 (cda-tum/mqt-core): Key feature deliveries include static qubit addressing across dialects with MQTDyn renamed to MQTRef and a new Qubit operation in mqtopt; a major refactor introducing StatefulOpConversionPattern to centralize lowering state and reduce boilerplate. Tests and docs updated to reflect static addressing and static references. Business value: improved cross-dialect interoperability, more maintainable lowering code, and a stronger foundation for future optimizations. No major bugs fixed this month.
3 Commits • 2 Features
Aug 1, 2025August 2025 (cda-tum/mqt-core): Key feature deliveries include static qubit addressing across dialects with MQTDyn renamed to MQTRef and a new Qubit operation in mqtopt; a major refactor introducing StatefulOpConversionPattern to centralize lowering state and reduce boilerplate. Tests and docs updated to reflect static addressing and static references. Business value: improved cross-dialect interoperability, more maintainable lowering code, and a stronger foundation for future optimizations. No major bugs fixed this month.
August 2025
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 | cda-tum/mqt-core 1) Key features delivered - Decision Diagram Garbage Collector Overhaul (Mark-and-Sweep): migrated GC from reference counting to mark-and-sweep for the decision diagram package, improving memory management and reclaiming nodes and complex numbers more efficiently. Commit 121df7f8207b7df793d56776e83cc8f3f59b6f84; message: "♻️ Switch from reference counting to mark-and-sweep garbage collection in decision diagram package (#1020)". 2) Major bugs fixed - None reported this month; primary focus was architectural memory-management improvement rather than bug fixes. 3) Overall impact and accomplishments - Improved memory reclamation and stability for large decision-diagram workloads, enabling higher throughput and reduced memory pressure. This work lays groundwork for further GC tuning and performance gains across the mqt-core stack. 4) Technologies/skills demonstrated - Garbage collection strategies (mark-and-sweep), memory-management optimization, refactoring for GC architecture, traceability via commit references, proficiency with the cda-tum/mqt-core codebase.
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 | cda-tum/mqt-core 1) Key features delivered - Decision Diagram Garbage Collector Overhaul (Mark-and-Sweep): migrated GC from reference counting to mark-and-sweep for the decision diagram package, improving memory management and reclaiming nodes and complex numbers more efficiently. Commit 121df7f8207b7df793d56776e83cc8f3f59b6f84; message: "♻️ Switch from reference counting to mark-and-sweep garbage collection in decision diagram package (#1020)". 2) Major bugs fixed - None reported this month; primary focus was architectural memory-management improvement rather than bug fixes. 3) Overall impact and accomplishments - Improved memory reclamation and stability for large decision-diagram workloads, enabling higher throughput and reduced memory pressure. This work lays groundwork for further GC tuning and performance gains across the mqt-core stack. 4) Technologies/skills demonstrated - Garbage collection strategies (mark-and-sweep), memory-management optimization, refactoring for GC architecture, traceability via commit references, proficiency with the cda-tum/mqt-core codebase.
June 2025
5 Commits • 2 Features
Jun 1, 2025During June 2025, delivered key features enabling scalable quantum state modeling and improved testing. Introduced Random vector DD state generation with centralized StateGeneration API, supporting exponentially large states, configurable wiring strategies, and reproducible seeding. Refactored state creation into dd::StateGeneration for maintainability. Expanded QA with a comprehensive MQTDyn MLIR dialect test suite covering allocation, extraction, measurement, and gate support. Fixed numerical inaccuracies in ThreeQubitRemoveUnconnected test and added a controlled-RY gate to better simulate complex scenarios. Overall impact: increased reliability and scalability of state generation, stronger validation of MLIR dialect, and lower risk for future changes. Tech stack: C++, MLIR, unit testing, reproducible seeding, and gate implementation.
5 Commits • 2 Features
Jun 1, 2025During June 2025, delivered key features enabling scalable quantum state modeling and improved testing. Introduced Random vector DD state generation with centralized StateGeneration API, supporting exponentially large states, configurable wiring strategies, and reproducible seeding. Refactored state creation into dd::StateGeneration for maintainability. Expanded QA with a comprehensive MQTDyn MLIR dialect test suite covering allocation, extraction, measurement, and gate support. Fixed numerical inaccuracies in ThreeQubitRemoveUnconnected test and added a controlled-RY gate to better simulate complex scenarios. Overall impact: increased reliability and scalability of state generation, stronger validation of MLIR dialect, and lower risk for future changes. Tech stack: C++, MLIR, unit testing, reproducible seeding, and gate implementation.
June 2025
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for the cda-tum/mqt-core repository focused on delivering a high-value feature with solid validation and scalable design. Executive summary: Delivered a new Decision Diagram Approximation feature by migrating and refactoring the DDSim functionality, establishing a foundation for accurate, scalable decision diagram analytics in the core MQT pipeline. This work includes new architecture for the approximation logic, supporting header and source files, and comprehensive unit tests to validate fidelity across multiple scenarios.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for the cda-tum/mqt-core repository focused on delivering a high-value feature with solid validation and scalable design. Executive summary: Delivered a new Decision Diagram Approximation feature by migrating and refactoring the DDSim functionality, establishing a foundation for accurate, scalable decision diagram analytics in the core MQT pipeline. This work includes new architecture for the approximation logic, supporting header and source files, and comprehensive unit tests to validate fidelity across multiple scenarios.
Activity
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Quality Metrics
Correctness95.6%
Maintainability92.6%
Architecture92.6%
Performance83.2%
AI Usage22.6%
Skills & Technologies
Programming Languages
C++CMakeLLVM IRMLIRMarkdownPython
Technical Skills
Algorithm DesignAlgorithm ImplementationAlgorithm OptimizationAttribute HandlingC++C++ DevelopmentCMakeCode OrganizationCode RefactoringCompiler DesignCompiler DevelopmentData StructuresDecision DiagramsDialect DevelopmentGarbage Collection
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