M. Casas

156 papers receiving 2.5k citations

Peers

M. Casas
Comparison fields: 5 of 83
  • Statistical and Nonlinear Physics 490
  • Atomic and Molecular Physics, and Optics 1.1k
  • Radiological and Ultrasound Technology 90
  • Artificial Intelligence 757
  • Analytical Chemistry 233
Replace Marvin M. Miller with:
Marvin M. Miller United States
C. Cosmelli Italy
R. Janik Switzerland
Meng Wang China
Guofu Cao China
David Robert Smith United States
S. Moriyama Japan
Moorad Alexanian United States
K. B. Luk United States
M. Casas relative to Marvin M. Miller United States Marvin M. Miller's profile →
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Citations per year

Countries citing papers authored by M. Casas

Since Specialization
Citations

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

Fields of papers citing papers by M. Casas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M. Casas, 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 M. Casas Line = papers co-authored together M. Casas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 160 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999176
2 2007129
3 2008127
4 201278
5 201066
6 200565
7 200959
8 200156
9 199055
10 199455
11 201154
12 200652
13 201150
14 201049
15 199148
16 200745
17 199544
18 200243
19 200242
20 200039

About M. Casas

M. Casas is a scholar working on Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics, Artificial Intelligence, Condensed Matter Physics and Nuclear and High Energy Physics, having authored 160 papers that have together received 2.6k indexed citations. Recurring topics across this work include Quantum Mechanics and Applications (44 papers), Quantum Information and Cryptography (43 papers), Statistical Mechanics and Entropy (38 papers), Physics of Superconductivity and Magnetism (16 papers), Spectral Theory in Mathematical Physics (10 papers), Quantum chaos and dynamical systems (10 papers), Nuclear physics research studies (10 papers) and Radioactive element chemistry and processing (10 papers). The work is most often cited by research in Statistical and Nonlinear Physics (490 citations), Atomic and Molecular Physics, and Optics (1.1k citations), Radiological and Ultrasound Technology (90 citations), Artificial Intelligence (757 citations) and Analytical Chemistry (233 citations). M. Casas has collaborated with scholars based in Spain, Argentina and South Africa. Frequent co-authors include Angel Ricardo Plastino, Josep Amengual i Batle, Antoni Borràs, F. Garcías, Vı́ctor Cerdà, Antonio Puente, A. Rigó, Claudia Zander, Jessica Avivar and Laura Ferrer. Their work appears in journals such as Physical Review A, Physics Letters A, Physica A Statistical Mechanics and its Applications, Physica C Superconductivity and Journal of Physics A Mathematical and Theoretical.

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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