P. Ruján

1.1k citations
41 papers · 720 · h-index 14

Impact in

Papers in

P. Ruján

39 papers receiving 680 citations

Peers

P. Ruján
Comparison fields: 5 of 66
  • Condensed Matter Physics 272
  • Statistical and Nonlinear Physics 119
  • Artificial Intelligence 243
  • Mathematical Physics 50
  • Cognitive Neuroscience 100
Replace P. Péretto with:
P. Péretto France
Isaac Pérez Castillo United Kingdom
Carlo Lucibello Italy
P.‐M. Binder United States
Itay Hen United States
Nicolas Macris Switzerland
Ch. Schütte Germany
Paul H. Bryant United States
Masatoshi Shiino Japan
Sébastien Racanière United States
P. Ruján relative to P. Péretto France P. Péretto's profile →
Citations per field
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P. Péretto · 1×
Citations per year

Countries citing papers authored by P. Ruján

Since Specialization
Citations

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

Fields of papers citing papers by P. Ruján

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside P. Ruján, 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 P. Ruján Line = papers co-authored together P. Ruján links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200295
2 199087
3 199068
4 199366
5 198140
6 198136
7 198435
8 199728
9 198327
10 197822
11 199321
12 199317
13 198516
14
Learning by Minimizing Resources in Neural Networks
198915
15 200112
16 198612
17 199712
18 198511
19 197911
20 198111

About P. Ruján

P. Ruján is a scholar working on Condensed Matter Physics, Atomic and Molecular Physics, and Optics, Statistical and Nonlinear Physics, Artificial Intelligence and Mathematical Physics, having authored 41 papers that have together received 720 indexed citations. Recurring topics across this work include Theoretical and Computational Physics (22 papers), Quantum many-body systems (10 papers), Neural Networks and Applications (10 papers), Physics of Superconductivity and Magnetism (7 papers), Stochastic processes and statistical mechanics (5 papers), Material Dynamics and Properties (4 papers), Advanced Chemical Physics Studies (3 papers) and Quantum chaos and dynamical systems (3 papers). The work is most often cited by research in Condensed Matter Physics (272 citations), Statistical and Nonlinear Physics (119 citations), Artificial Intelligence (243 citations), Mathematical Physics (50 citations) and Cognitive Neuroscience (100 citations). P. Ruján has collaborated with scholars based in Germany, Hungary and United States. Frequent co-authors include Mario Marchand, Wolfgang Kinzel, Josef Ammermüller, Mostefa Golea, Martin Greschner, G. Györgyi, W. Selke, A. Patkós, G. Uimin and H. L. Frisch. Their work appears in journals such as Physical review. B, Condensed matter, Physics Letters B, Physica A Statistical Mechanics and its Applications, Europhysics Letters (EPL) and Network Computation in Neural Systems.

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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