M. Casas

2.4k citations
113 papers · 1.8k · h-index 24

Impact in

Papers in

M. Casas

109 papers receiving 1.7k citations

Peers

M. Casas
Comparison fields: 5 of 107
  • Statistical and Nonlinear Physics 467
  • Atomic and Molecular Physics, and Optics 1.1k
  • Radiological and Ultrasound Technology 106
  • Analytical Chemistry 201
  • Artificial Intelligence 575
Replace Wesley C. Campbell with:
Wesley C. Campbell United States
William J. Thompson United States
George I. Fann United States
I. R. Gatland United States
P. E. Toschek Germany
A. N. Proto Argentina
J.E. Schweppe United States
G. G. Luther United States
W. Quint Germany
Ousmanou Motapon Cameroon
M. Casas relative to Wesley C. Campbell United States Wesley C. Campbell's profile →
Citations per field
00.5×3.6×
Wesley C. Campbell · 1×
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 113 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999161
2 2007124
3 2008110
4 201273
5 201062
6 200558
7 199454
8 200953
9 201149
10 200149
11 199048
12 200647
13 201147
14 199144
15 201044
16 201035
17 200231
18 201130
19 201028
20 199625

About M. Casas

M. Casas is a scholar working on Atomic and Molecular Physics, and Optics, Statistical and Nonlinear Physics, Artificial Intelligence, Nuclear and High Energy Physics and Global and Planetary Change, having authored 113 papers that have together received 1.8k indexed citations. Recurring topics across this work include Quantum Mechanics and Applications (31 papers), Quantum Information and Cryptography (25 papers), Quantum Computing Algorithms and Architecture (17 papers), Cold Atom Physics and Bose-Einstein Condensates (16 papers), Quantum Mechanics and Non-Hermitian Physics (14 papers), Advanced Thermodynamics and Statistical Mechanics (13 papers), Statistical Mechanics and Entropy (13 papers) and Nuclear physics research studies (12 papers). The work is most often cited by research in Statistical and Nonlinear Physics (467 citations), Atomic and Molecular Physics, and Optics (1.1k citations), Radiological and Ultrasound Technology (106 citations), Analytical Chemistry (201 citations) and Artificial Intelligence (575 citations). M. Casas has collaborated with scholars based in Spain, Argentina and South Africa. Frequent co-authors include A. Plastino, Josep Amengual i Batle, A. Borrás, F. Garcías, Vı́ctor Cerdà, A. Rigó, A. Puente, Jessica Avivar, Laura Ferrer and A. P. Majtey. Their work appears in journals such as Physical Review A, Physics Letters A, Physica A Statistical Mechanics and its Applications, Nuclear Physics A and Applied Radiation and Isotopes.

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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