Daniel Reitzner

543 citations
20 papers · 370 · h-index 11

Impact in

Papers in

Daniel Reitzner

19 papers receiving 359 citations

Peers

Daniel Reitzner
Comparison fields: 5 of 26
  • Artificial Intelligence 356
  • Computational Theory and Mathematics 131
  • Atomic and Molecular Physics, and Optics 222
  • Statistical and Nonlinear Physics 44
  • History and Philosophy of Science 4
Replace Alessandro Tosini with:
Alessandro Tosini Italy
Sophie Laplante France
John van de Wetering Netherlands
Hakop Pashayan Canada
A. Auyuanet Uruguay
Leonardo Novo Portugal
Ashutosh Rai India
Garry Bowen United Kingdom
Carl A. Miller United States
B. C. Travaglione Australia
Daniel Reitzner relative to Alessandro Tosini Italy Alessandro Tosini's profile →
Citations per field
00.5×1.5×2.5×
Alessandro Tosini · 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 19 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
#Work
1 200951
2 201550
3 201544
4 200841
5 201134
6 201027
7 201022
8 201320
9 201219
10 201915
11 201612
12 20178
13 20108
14 20147
15 20186
16 20143
17 20231
18 20231
19 20041
20 20240

About Daniel Reitzner

Daniel Reitzner is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 370 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (19 papers), Quantum Computing Algorithms and Architecture (15 papers), Quantum Mechanics and Applications (10 papers), Quantum-Dot Cellular Automata (7 papers), Advanced Thermodynamics and Statistical Mechanics (3 papers), Neural dynamics and brain function (1 paper), Image Processing and 3D Reconstruction (1 paper) and Computability, Logic, AI Algorithms (1 paper). The work is most often cited by research in Artificial Intelligence (356 citations), Computational Theory and Mathematics (131 citations), Atomic and Molecular Physics, and Optics (222 citations), Statistical and Nonlinear Physics (44 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 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, Physical review. A, Journal of Physics A Mathematical and Theoretical, Quantum Information Processing and Foundations of Physics.

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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