Hybrid quantum-classical algorithms and quantum error mitigation
Impact in
Classified as
- Authors
- Simon C. BenjaminXiao Yuan
- Journal
- Oxford University Research Archive (ORA) (University of Oxford)
In The Last Decade
doi.org/w16418230 →Countries where authors are citing Hybrid quantum-classical algorithms and quantum error mitigation
This map shows the geographic impact of Hybrid quantum-classical algorithms and quantum error mitigation. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hybrid quantum-classical algorithms and quantum error mitigation with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hybrid quantum-classical algorithms and quantum error mitigation more than expected).
Fields of papers citing Hybrid quantum-classical algorithms and quantum error mitigation
This network shows the impact of Hybrid quantum-classical algorithms and quantum error mitigation. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Hybrid quantum-classical algorithms and quantum error mitigation.
About Hybrid quantum-classical algorithms and quantum error mitigation
This paper, published in 2021, received 313 indexed citations . Written by Simon C. Benjamin and Xiao Yuan covering the research area of Artificial Intelligence and Atomic and Molecular Physics, and Optics. It is primarily cited by scholars working on Artificial Intelligence (297 citations), Atomic and Molecular Physics, and Optics (177 citations), Computational Theory and Mathematics (48 citations), Electrical and Electronic Engineering (36 citations) and Information Systems (8 citations). Published in Oxford University Research Archive (ORA) (University of Oxford).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w16418230.