L.A.C.P. da Mota

423 citations
31 papers · 248 indexed · h-index 9
Topics
Advanced Differential Equations and Dynamical Systems (13 papers)Nonlinear Waves and Solitons (11 papers)Numerical methods for differential equations (11 papers)

In The Last Decade

L.A.C.P. da Mota

31 papers receiving 234 citations

Peers

L.A.C.P. da Mota
Comparison fields: 5 of 41
  • Statistical and Nonlinear Physics 170
  • Geometry and Topology 113
  • Numerical Analysis 74
  • Computational Theory and Mathematics 68
  • Modeling and Simulation 40
Replace Marcus Wunsch with:
Marcus Wunsch Japan
Naoyuki Ishimura Japan
И. В. Островскии Türkiye
Wolfgang Gawronski Germany
Annalisa Cesaroni Italy
Rafael Díaz Colombia
Erik Taflin France
K. Driver South Africa
Neven Elezović Croatia
Nathaël Gozlan France
L.A.C.P. da Mota relative to Marcus Wunsch Japan Marcus Wunsch's profile →
Citations per field
00.5×5.7×
Marcus Wunsch · 1×
Citations per year

Countries citing papers authored by L.A.C.P. da Mota

Since Specialization
Citations

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

Fields of papers citing papers by L.A.C.P. da Mota

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L.A.C.P. da Mota. 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 L.A.C.P. da Mota. The network helps show where L.A.C.P. da Mota may publish in the future.

Co-authorship network of co-authors of L.A.C.P. da Mota

This figure shows the co-authorship network connecting the top 25 collaborators of L.A.C.P. da Mota. A scholar is included among the top collaborators of L.A.C.P. da Mota based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with L.A.C.P. da Mota. L.A.C.P. da Mota is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
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4 12
5 3
6 4
7 1
8 1
9 5
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11 2
12 3
13 7
14 16
15 12
16 63
17 29
18
PATTERNS OF QUARK MASS MATRICES IN A CLASS OF CALABI-YAU MODELS
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About L.A.C.P. da Mota

L.A.C.P. da Mota is a scholar working on Numerical Analysis, Statistical and Nonlinear Physics and Geometry and Topology, having authored 31 papers that have together received 248 indexed citations. Recurring topics across this work include Advanced Differential Equations and Dynamical Systems (13 papers), Nonlinear Waves and Solitons (11 papers) and Numerical methods for differential equations (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (170 citations), Numerical Analysis (74 citations) and Geometry and Topology (113 citations). L.A.C.P. da Mota has collaborated with scholars based in Brazil, United Kingdom and Spain. Frequent co-authors include L.G.S. Duarte, J E F Skea, E.S. Cheb-Terrab, F. del Águila, M. Masip, Niklaus Ursus Wetter, Jaime Frejlich, Mayu Muramatsu, G.D. Coughlan and A.F. Rocha. Their work appears in journals such as Physics Letters B, Computer Physics Communications and Chaos Solitons & Fractals.

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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