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Recommending Solution Paths for Solving Optimization Problems with Quantum Computing
Benedikt Poggel, Nils Quetschlich, Lukas Burgholzer +2
Solving real-world optimization problems with quantum computing requires choosing between a large number of options concerning formulation, encoding, algorithm and hardware. Findin…
Compiler Optimization for Quantum Computing Using Reinforcement Learning
Nils Quetschlich, Lukas Burgholzer, Robert Wille
Any quantum computing application, once encoded as a quantum circuit, must be compiled before being executable on a quantum computer. Similar to classical compilation, quantum comp…
Towards an Automated Framework for Realizing Quantum Computing Solutions
Nils Quetschlich, Lukas Burgholzer, Robert Wille
Quantum computing is fast evolving as a technology due to recent advances in hardware, software, as well as the development of promising applications. To use this technology for so…
Predicting Good Quantum Circuit Compilation Options
Nils Quetschlich, Lukas Burgholzer, Robert Wille
Any potential application of quantum computing, once encoded as a quantum circuit, needs to be compiled in order to be executed on a quantum computer. Deciding which qubit technolo…
MQT Bench: Benchmarking Software and Design Automation Tools for Quantum Computing
Nils Quetschlich, Lukas Burgholzer, Robert Wille
Quantum software tools for a wide variety of design tasks on and across different levels of abstraction are crucial in order to eventually realize useful quantum applications. This…