Michał Studziński

690 citations
27 papers · 456 · h-index 12

Impact in

Papers in

Michał Studziński

24 papers receiving 450 citations

Peers

Michał Studziński
Comparison fields: 5 of 35
  • Atomic and Molecular Physics, and Optics 333
  • Artificial Intelligence 357
  • Statistical and Nonlinear Physics 128
  • Geometry and Topology 30
  • Numerical Analysis 13
Replace Gen Kimura with:
Gen Kimura Japan
Sergii Strelchuk United Kingdom
Martin Fraas Switzerland
Lech Jakóbczyk Poland
Ludovico Lami Germany
Giacomo De Palma Italy
Cambyse Rouzé Germany
M. E. Shirokov Russia
Biswajit Dutta India
Marcelo A. Marchiolli Brazil
Michał Studziński relative to Gen Kimura Japan Gen Kimura's profile →
Citations per field
00.5×2.8×
Gen Kimura · 1×
Citations per year

Countries citing papers authored by Michał Studziński

Since Specialization
Citations

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

Fields of papers citing papers by Michał Studziński

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Michał Studziński, 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 Michał Studziński Line = papers co-authored together Michał Studziński links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015218
2 201733
3 201832
4 202216
5 202016
6 201815
7 201714
8 202112
9 201412
10 202111
11 201311
12 201311
13 201210
14 20149
15 20236
16 20215
17 20215
18 20145
19 20234
20 20134

About Michał Studziński

Michał Studziński is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Geometry and Topology, Algebra and Number Theory and Mathematical Physics, having authored 27 papers that have together received 456 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (18 papers), Quantum Computing Algorithms and Architecture (17 papers), Quantum Mechanics and Applications (11 papers), Algebraic structures and combinatorial models (7 papers), Advanced Topics in Algebra (5 papers), Quantum optics and atomic interactions (3 papers), Advanced Algebra and Geometry (2 papers) and Quantum-Dot Cellular Automata (2 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (333 citations), Artificial Intelligence (357 citations), Statistical and Nonlinear Physics (128 citations), Geometry and Topology (30 citations) and Numerical Analysis (13 citations). Michał Studziński has collaborated with scholars based in Poland, United Kingdom and Spain. Frequent co-authors include Michał Horodecki, Piotr Ćwikliński, Jonathan Oppenheim, Marek Mozrzymas, Sergii Strelchuk, Nilanjana Datta, Paweł Mazurek, Máté Farkas, Andrzej Grudka and Łukasz Pańkowski. Their work appears in journals such as Journal of Physics A Mathematical and Theoretical, New Journal of Physics, Physical review. A, Physical Review Letters and Quantum.

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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