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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Automatic depth optimization for a quantum approximate optimization algorithm
Yu Pan, Yifan Tong, Yi Yang
Physical review. A/Physical review, A (2022) Vol. 105, Iss. 3
Open Access | Times Cited: 11

Showing 11 citing articles:

Multilevel Leapfrogging Initialization Strategy for Quantum Approximate Optimization Algorithm
Xiao‐Hui Ni, Bin‐Bin Cai, Hailing Liu, et al.
Advanced Quantum Technologies (2024) Vol. 7, Iss. 5
Closed Access | Times Cited: 5
Convergence of digitized-counterdiabatic QAOA: circuit depth versus free parameters
Mara Vizzuso, Gianluca Passarelli, Giovanni Cantele, et al.
New Journal of Physics (2023) Vol. 26, Iss. 1, pp. 013002-013002
Open Access | Times Cited: 9
Lithium-ion battery state of health estimation method based on variational quantum algorithm optimized stacking strategy
Longze Wang, Siyu Jiang, Yuteng Mao, et al.
Energy Reports (2024) Vol. 11, pp. 2877-2891
Open Access | Times Cited: 3
QPU-System Co-design for Quantum HPC Accelerators
Karen Wintersperger, Hila Safi, Wolfgang Mauerer
Lecture notes in computer science (2022), pp. 100-114
Closed Access | Times Cited: 15
A superconducting quantum processor architecture design method for improving performance and reducing frequency collisions
Tian Yang, Weilong Wang, Lixin Wang, et al.
Results in Physics (2023) Vol. 53, pp. 106944-106944
Open Access | Times Cited: 4
Robust optimization for quantum reinforcement learning control using partial observations
Chunying Chen, Yu Pan, Zheng-Guang Wu, et al.
Physical review. A/Physical review, A (2022) Vol. 105, Iss. 6
Open Access | Times Cited: 4
Max-Cut Linear Binary Classifier Based on Quantum Approximate Optimization Algorithm
Jiaji Wang, Yuqi Wang, Xi Li, et al.
International Journal of Theoretical Physics (2024) Vol. 63, Iss. 11
Closed Access
Quantum machine learning algorithms for anomaly detection: A review
Sebastiano Corli, Lorenzo Moro, Daniele Dragoni, et al.
Future Generation Computer Systems (2024), pp. 107632-107632
Open Access
Near-term quantum algorithm for solving the MaxCut problem with fewer quantum resources
Zhao Xiumei, Yongmei Li, Jing Li, et al.
Physica A Statistical Mechanics and its Applications (2024) Vol. 648, pp. 129951-129951
Closed Access
Efficient depth selection for the implementation of noisy quantum approximate optimization algorithm
Yu Pan, Yifan Tong, Shibei Xue, et al.
Journal of the Franklin Institute (2022) Vol. 359, Iss. 18, pp. 11273-11287
Open Access | Times Cited: 2
Convergence of Digitized-Counterdiabatic QAOA: circuit depth versus free parameters
Mara Vizzuso, Gianluca Passarelli, Giovanni Cantele, et al.
arXiv (Cornell University) (2023)
Open Access
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