Authors
Paul Wang, Jianzhou Mao and Eric Sakk, Morgan State University, USA
Abstract
This paper discusses the compilation, optimization, and error mitigation of quantum algo-rithms, 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.
Keywords
Transpilation, Optimization, Error Mitigation, quantum machine learning, quantum algo-rithms