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Compilation, Optimization, Error Mitigation, and Machine Learning in Quantum Algorithms
Paul Wang, Jianzhou Mao, Eric Sakk·June 18, 2025·DOI: 10.5121/csit.2025.150501
PhysicsComputer Science
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Abstract
This paper discusses the compilation, optimization, and error mitigation of quantum algorithms, essential steps to execute real-world quantum algorithms. Quantum algorithms running on a hybrid platform with QPU and CPU/GPU take advantage of existing high-performance computing power with quantum-enabled exponential speedups. The proposed approximate quantum Fourier transform (AQFT) for quantum algorithm optimization improves the circuit execution on top of an exponential speed-ups the quantum Fourier transform has provided.