Martin Plesch

849 citations
34 papers · 481 · h-index 12

Impact in

Papers in

Martin Plesch

33 papers receiving 465 citations

Peers

Martin Plesch
Comparison fields: 5 of 46
  • Artificial Intelligence 433
  • Atomic and Molecular Physics, and Optics 291
  • Computational Theory and Mathematics 92
  • Computational Mathematics 2
  • Statistical and Nonlinear Physics 33
Replace Yingkai Ouyang with:
Yingkai Ouyang Singapore
Peter Brown France
Wen‐Zhao Liu China
Pierre-Luc Dallaire-Demers Germany
Carl A. Miller United States
Matej Pivoluska Slovakia
Anna Pappa Germany
Phillip Kaye Canada
Bill Fefferman United States
Dan Shepherd United Kingdom
Martin Plesch relative to Yingkai Ouyang Singapore Yingkai Ouyang's profile →
Citations per field
00.5×4.5×
Yingkai Ouyang · 1×
Citations per year

Countries citing papers authored by Martin Plesch

Since Specialization
Citations

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

Fields of papers citing papers by Martin Plesch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Plesch. 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 Martin Plesch. The network helps show where Martin Plesch may publish in the future.

Co-authors

The 20 scholars most cited alongside Martin Plesch, 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 Martin Plesch Line = papers co-authored together Martin Plesch links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011199
2 201240
3 200338
4 201030
5 201418
6 202217
7 201117
8 201414
9 202213
10 202111
11 200811
12 200511
13 200311
14 20228
15 20148
16
Device Independent Random Number Generation
20144
17 20044
18 20054
19 20063
20 20143

About Martin Plesch

Martin Plesch is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Statistical and Nonlinear Physics, Computational Theory and Mathematics and Control and Systems Engineering, having authored 34 papers that have together received 481 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (25 papers), Quantum Computing Algorithms and Architecture (20 papers), Quantum Mechanics and Applications (19 papers), Quantum-Dot Cellular Automata (4 papers), Advanced Thermodynamics and Statistical Mechanics (2 papers), Statistical Mechanics and Entropy (2 papers), Experimental and Theoretical Physics Studies (2 papers) and Fish biology, ecology, and behavior (1 paper). The work is most often cited by research in Artificial Intelligence (433 citations), Atomic and Molecular Physics, and Optics (291 citations), Computational Theory and Mathematics (92 citations), Computational Mathematics (2 citations) and Statistical and Nonlinear Physics (33 citations). Martin Plesch has collaborated with scholars based in Slovakia, Czechia and Austria. Frequent co-authors include Časlav Brukner, Vladimír Bužek, Matej Pivoluska, Jan Bouda, Marcus Huber, Michal Sedlák, Marcin Pawłowski, Mário Ziman, Oscar Dahlsten and Manik Banik. Their work appears in journals such as Physical Review A, Physical review. A, Scientific Reports, Open Systems & Information Dynamics and The European Physical Journal D.

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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