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arXiv · 2506.15760

Compilation, Optimization, Error Mitigation, and Machine Learning in Quantum Algorithms

Shuangbao Paul Wang·Jianzhou Mao·Eric Sakk
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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.

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Shuangbao Paul Wang, Jianzhou Mao, Eric Sakk. 2025-06-18. Compilation, Optimization, Error Mitigation, and Machine Learning in Quantum Algorithms. https://doi.org/10.5121/csit.2025.150501

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