High-rate quantum key distribution exceeding 110 Mb s–1
Impact in
Classified as
- Authors
- Wei LiHao TanYichen LuSheng‐Kai LiaoJia Huang
- Journal
- Nature Photonics
In The Last Decade
doi.org/10.1038/s41566-023-01166-4 →Countries where authors are citing High-rate quantum key distribution exceeding 110 Mb s–1
This map shows the geographic impact of High-rate quantum key distribution exceeding 110 Mb s–1. 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 High-rate quantum key distribution exceeding 110 Mb s–1 with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites High-rate quantum key distribution exceeding 110 Mb s–1 more than expected).
Fields of papers citing High-rate quantum key distribution exceeding 110 Mb s–1
This network shows the impact of High-rate quantum key distribution exceeding 110 Mb s–1. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the High-rate quantum key distribution exceeding 110 Mb s–1.
About High-rate quantum key distribution exceeding 110 Mb s–1
This paper, published in 2023, received 179 indexed citations . Written by Wei Li, Hao Tan, Yichen Lu, Sheng‐Kai Liao, Jia Huang, Hao Li, Zhen Wang, Haokun Mao, Qiong Li and Yang Liu covering the research area of Artificial Intelligence and Atomic and Molecular Physics, and Optics. It is primarily cited by scholars working on Artificial Intelligence (140 citations), Atomic and Molecular Physics, and Optics (95 citations), Electrical and Electronic Engineering (58 citations), Instrumentation (11 citations) and Biomedical Engineering (10 citations). Published in Nature Photonics.
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/10.1038/s41566-023-01166-4.