Daniel Reitzner

632 citations
21 papers · 396 · h-index 11

Impact in

Papers in

Daniel Reitzner

19 papers receiving 389 citations

Peers

Daniel Reitzner
Comparison fields: 5 of 28
  • Artificial Intelligence 374
  • Computational Theory and Mathematics 140
  • Atomic and Molecular Physics, and Optics 232
  • Statistical and Nonlinear Physics 45
  • History and Philosophy of Science 4
Replace Leonardo Novo with:
Leonardo Novo Portugal
Anirudh Krishna Canada
Hakop Pashayan Canada
Carl A. Miller United States
A. Auyuanet Uruguay
Vincent Nesme France
Garry Bowen United Kingdom
Dennis Kretschmann Germany
Andrea Coladangelo United States
Neil B. Lovett United Kingdom
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Citations per field
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Leonardo Novo · 1×
Citations per year

Countries citing papers authored by Daniel Reitzner

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Reitzner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200953
2 201551
3 201550
4 200845
5 201138
6 201029
7 201023
8 201322
9 201219
10 201917
11 201612
12 20179
13 20109
14 20146
15 20185
16 20144
17 20232
18 20231
19 20041
20
Quantum Incompatibility in Collective Measurements
20220

About Daniel Reitzner

Daniel Reitzner is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics, Statistical and Nonlinear Physics and Cognitive Neuroscience, having authored 21 papers that have together received 396 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (20 papers), Quantum Computing Algorithms and Architecture (15 papers), Quantum Mechanics and Applications (11 papers), Quantum-Dot Cellular Automata (7 papers), Advanced Thermodynamics and Statistical Mechanics (4 papers), Image Processing and 3D Reconstruction (1 paper), Neural dynamics and brain function (1 paper) and Advancements in Semiconductor Devices and Circuit Design (1 paper). The work is most often cited by research in Artificial Intelligence (374 citations), Computational Theory and Mathematics (140 citations), Atomic and Molecular Physics, and Optics (232 citations), Statistical and Nonlinear Physics (45 citations) and History and Philosophy of Science (4 citations). Daniel Reitzner has collaborated with scholars based in Slovakia, Finland and United States. Frequent co-authors include Teiko Heinosaari, Vladimír Bužek, Mark S. Hillery, Jukka Kiukas, Edgar Feldman, Peter Stano, Jussi Schultz, Daniel Nagaj, Mário Ziman and Takayuki Miyadera. Their work appears in journals such as Physical Review A, Quantum Information Processing, Journal of Physics A Mathematical and Theoretical, Foundations of Physics and The European Physical Journal Plus.

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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