Michael E. Beverland

681 citations
11 papers · 345 indexed · h-index 9

Impact in

Papers in

Michael E. Beverland

11 papers receiving 338 citations

Peers

Michael E. Beverland
Comparison fields: 5 of 26
  • Artificial Intelligence 286
  • Computational Theory and Mathematics 114
  • Atomic and Molecular Physics, and Optics 177
  • Hardware and Architecture 16
  • Condensed Matter Physics 25
Replace Peter Groszkowski with:
Peter Groszkowski United States
Guillaume Duclos-Cianci Canada
Daniel Litinski Germany
Zhenyu Cai United Kingdom
James R. Wootton Switzerland
Nhung H. Nguyen United States
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Citations per field
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Citations per year

Countries citing papers authored by Michael E. Beverland

Since Specialization
Citations

This map shows the geographic impact of Michael E. Beverland's research. 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 Michael E. Beverland with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael E. Beverland more than expected).

Fields of papers citing papers by Michael E. Beverland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael E. Beverland. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael E. Beverland. The network helps show where Michael E. Beverland may publish in the future.

Co-authors

The 20 scholars most cited alongside Michael E. Beverland, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael E. Beverland Line = papers co-authored together Michael E. Beverland links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 201578
2 202151
3 202247
4 201836
5 202030
6 202229
7 201625
8 202022
9 201616
10 20186
11 20145

About Michael E. Beverland

Michael E. Beverland is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Condensed Matter Physics and Signal Processing, having authored 11 papers that have together received 345 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (7 papers), Quantum many-body systems (4 papers), Quantum Information and Cryptography (4 papers), Quantum and electron transport phenomena (3 papers), Cold Atom Physics and Bose-Einstein Condensates (3 papers), Quantum-Dot Cellular Automata (2 papers), Physics of Superconductivity and Magnetism (1 paper) and Topological Materials and Phenomena (1 paper). The work is most often cited by research in Artificial Intelligence (286 citations), Computational Theory and Mathematics (114 citations), Atomic and Molecular Physics, and Optics (177 citations), Hardware and Architecture (16 citations) and Condensed Matter Physics (25 citations). Michael E. Beverland has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Aleksander Kubica, Krysta M. Svore, Nicolas Delfosse, John Preskill, Nicole Yunger Halpern, Amir Kalev, Vadym Kliuchnikov, Eddie Schoute, Fernando G. S. L. Brandão and Jeongwan Haah. Their work appears in journals such as Physical Review Letters, PRX Quantum, Quantum, Physical review. A and Physical review. E.

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.

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