Towards Redefining the Reproducibility in Quantum Computing: A Data Analysis Approach on NISQ Devices-Reference-Cited by-同舟云学术

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Towards Redefining the Reproducibility in Quantum Computing: A Data Analysis Approach on NISQ Devices

Published:2023-09-17 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Quantum Computing and Engineering (QCE)
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Author:

Senapati Priyabrata¹,Wang Zhepeng²,Jiang Weiwen²,Humble Travis S³,Fang Bo⁴,Xu Shuai⁵,Guan Qiang¹

Affiliation:

1. Kent State University,Department of Computer Science

2. George Mason University,Department of Electrical and Computer Engineering

3. Quantum Science Center, Oak Ridge National Laboratory

4. HPC Group,Pacific Northwest National Laboratory

5. Case Western Reserve University,Department of Computer and Data Sciences

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10313590/10313591/10313593.pdf?arnumber=10313593

Reference32 articles.

1. QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits

2. Quantumnat: Quantum noise-aware training with noise injection, quantization and normalization;wang;ArXiv Preprint,2021

3. Recurrent quantum neural networks;bausch;ArXiv Preprint,2020

4. Quantum neuron: an elementary building block for machine learning on quantum computers;cao;ArXiv Preprint,2017

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