The flux qubit revisited to enhance coherence and reproducibility
- Journal
- Nature Communications
In The Last Decade
doi.org/10.1038/ncomms12964 →Countries where authors are citing The flux qubit revisited to enhance coherence and reproducibility
This map shows the geographic impact of The flux qubit revisited to enhance coherence and reproducibility. 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 The flux qubit revisited to enhance coherence and reproducibility with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The flux qubit revisited to enhance coherence and reproducibility more than expected).
Fields of papers citing The flux qubit revisited to enhance coherence and reproducibility
This network shows the impact of The flux qubit revisited to enhance coherence and reproducibility. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The flux qubit revisited to enhance coherence and reproducibility.
About The flux qubit revisited to enhance coherence and reproducibility
This paper, published in 2016, received 357 indexed citations . Written by Fei Yan, Simon Gustavsson, Archana Kamal, Jeffrey Birenbaum, Adam Sears, David Hover, Danna Rosenberg, Gabriel Samach, Steven Weber and Jonilyn Yoder covering the research area of Artificial Intelligence and Atomic and Molecular Physics, and Optics. It is primarily cited by scholars working on Atomic and Molecular Physics, and Optics (322 citations), Artificial Intelligence (291 citations) and Condensed Matter Physics (48 citations). Published in Nature Communications.
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/ncomms12964.