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\n\n \n \n \n \n \n The Quantum Circuit Model is not a Practical Representation of Quantum Software.\n \n \n \n\n\n \n \\textbfMeijer-van de Griend, \\.\n\n\n \n\n\n\n In
2024 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C), pages 146-148, 2024. \n
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@INPROCEEDINGS{10621734,\n author={\\textbf{Arianne} \\textbf{Meijer-van de Griend}},\n booktitle={2024 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)}, \n title={The Quantum Circuit Model is not a Practical Representation of Quantum Software}, \n year={2024},\n volume={},\n number={},\n pages={146-148},\n keywords={Codes;Computational modeling;Debugging;Programming;Software;Hardware;Mathematical models;quantum computing;quantum circuit model;quantum software, published},\n doi={10.1109/SANER-C62648.2024.00025}}\n\n
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\n\n \n \n \n \n \n \n Advances in Quantum Compilation in the NISQ Era.\n \n \n \n \n\n\n \n \\textbfMeijer-van de Griend, \\.\n\n\n \n\n\n\n . 2024.\n
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@article{PhDThesis,\n title={Advances in Quantum Compilation in the NISQ Era},\n author={\\textbf{Arianne} \\textbf{Meijer-van de Griend}},\n year={2024},\n publisher={Helsingin yliopisto},\n url_Paper={http://urn.fi/URN:ISBN:978-952-84-0077-6},\n keywords = {published},\n abstract = {Recent advances in the development of quantum technology have made it possible to run small quantum programs on real quantum computers. This has created a need for compiling methods specific to these quantum computers. Unlike classical computers, if a quantum computation takes too long, the qubits might decohere and lose their information, making the computation useless. Hence, well-optimized quantum programs are a necessity.\n\nLike classical computers, quantum computers have registers for qubits that are generally sparsely connected. However, classical compilation methods that rely on copying data from one register to another do not apply to quantum computers because qubits cannot be copied. This problem is called the qubit routing problem. Following classical compilation, one could solve the connectivity constraints by moving the qubits to adjacent qubit registers. However, this requires the addition of SWAP gates throughout the quantum circuit, resulting in a strictly longer program. Additionally, a SWAP gate on qubits is not cheap and requires three CNOT gates each.\n\nInstead, in this thesis, we have defined a new method for quantum compilation that is based in the quantum nature of the program to be compiled. Instead of routing the qubits directly, we generate new machine code (in the form of quantum circuits) from an intermediate representation. We call this process quantum circuit synthesis. During synthesis, we make sure that all generated gates are supported by the target quantum hardware. Additionally, if the synthesis process is optimal, the resulting quantum circuit will also be optimal, although the methods proposed in this thesis are all heuristic in nature due to the computational complexity of optimal architecture-aware synthesis.\n\nWe construct the nested intermediate representation starting from sequences of CNOT circuits interleaved with single qubit gates and incrementally generalize the intermediate representation to a universal representation. In particular, we propose two algorithms for synthesizing CNOT circuits from their parity matrix representation and one algorithm for synthesizing phase polynomials (i.e. CNOT+$R_Z$ circuits). Additionally, we show that when combining these methods into the universal representation called Mixed ZX-phase polynomial, it is competitive with existing commercial quantum compilers IBM's Qiskit and Quantinuum's TKET for large circuits.\n\nThis thesis additionally contains a proposal for a framework to benchmark the quality of circuits used in an algorithm called Variational Quantum Eigensolver (VQE). This framework attempts to measure how close the solution found by the VQE is to our best estimate of a real molecule (i.e. accuracy), rather than a classical simulation of the approximate molecule as given to the quantum computer (i.e. precision).},\n}\n\n
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\n Recent advances in the development of quantum technology have made it possible to run small quantum programs on real quantum computers. This has created a need for compiling methods specific to these quantum computers. Unlike classical computers, if a quantum computation takes too long, the qubits might decohere and lose their information, making the computation useless. Hence, well-optimized quantum programs are a necessity. Like classical computers, quantum computers have registers for qubits that are generally sparsely connected. However, classical compilation methods that rely on copying data from one register to another do not apply to quantum computers because qubits cannot be copied. This problem is called the qubit routing problem. Following classical compilation, one could solve the connectivity constraints by moving the qubits to adjacent qubit registers. However, this requires the addition of SWAP gates throughout the quantum circuit, resulting in a strictly longer program. Additionally, a SWAP gate on qubits is not cheap and requires three CNOT gates each. Instead, in this thesis, we have defined a new method for quantum compilation that is based in the quantum nature of the program to be compiled. Instead of routing the qubits directly, we generate new machine code (in the form of quantum circuits) from an intermediate representation. We call this process quantum circuit synthesis. During synthesis, we make sure that all generated gates are supported by the target quantum hardware. Additionally, if the synthesis process is optimal, the resulting quantum circuit will also be optimal, although the methods proposed in this thesis are all heuristic in nature due to the computational complexity of optimal architecture-aware synthesis. We construct the nested intermediate representation starting from sequences of CNOT circuits interleaved with single qubit gates and incrementally generalize the intermediate representation to a universal representation. In particular, we propose two algorithms for synthesizing CNOT circuits from their parity matrix representation and one algorithm for synthesizing phase polynomials (i.e. CNOT+$R_Z$ circuits). Additionally, we show that when combining these methods into the universal representation called Mixed ZX-phase polynomial, it is competitive with existing commercial quantum compilers IBM's Qiskit and Quantinuum's TKET for large circuits. This thesis additionally contains a proposal for a framework to benchmark the quality of circuits used in an algorithm called Variational Quantum Eigensolver (VQE). This framework attempts to measure how close the solution found by the VQE is to our best estimate of a real molecule (i.e. accuracy), rather than a classical simulation of the approximate molecule as given to the quantum computer (i.e. precision).\n
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\n\n \n \n \n \n \n Exposing the hidden layers and interplay in the quantum software stack.\n \n \n \n\n\n \n Stirbu, V.; \\textbfMeijer-van de Griend, \\.; and Muff, J.\n\n\n \n\n\n\n In
2024 IEEE 21st International Conference on Software Architecture Companion (ICSA-C), pages 24–25, 2024. IEEE\n
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@inproceedings{stirbu2024exposinghiddenlayersinterplay,\n title={Exposing the hidden layers and interplay in the quantum software stack},\n author={Stirbu, Vlad and \\textbf{Meijer-van de Griend}, \\textbf{Arianne} and Muff, Jake},\n booktitle={2024 IEEE 21st International Conference on Software Architecture Companion (ICSA-C)},\n pages={24--25},\n year={2024},\n organization={IEEE},\n keywords = {published},\n}\n\n
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\n\n \n \n \n \n \n Redefining lexicographical ordering: Optimizing pauli string decompositions for quantum compiling.\n \n \n \n\n\n \n Huang, Q.; Winderl, D.; \\textbfMeijer-van de Griend, \\.; and Yeung, R.\n\n\n \n\n\n\n In
2024 IEEE International Conference on Quantum Computing and Engineering (QCE), volume 1, pages 885–896, 2024. IEEE\n
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@inproceedings{huang2024redefining,\n title={Redefining lexicographical ordering: Optimizing pauli string decompositions for quantum compiling},\n author={Huang, Qunsheng and Winderl, David and \\textbf{Meijer-van de Griend}, \\textbf{Arianne} and Yeung, Richie},\n booktitle={2024 IEEE International Conference on Quantum Computing and Engineering (QCE)},\n volume={1},\n pages={885--896},\n year={2024},\n organization={IEEE},\n keywords = {published}\n}\n\n
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