Science Explorer Interactive view Map

Nonlinear Dynamics and Pattern Formation

Nonlinear Dynamics and Pattern Formation is a research topic within Computer Networks and Communications. Science Explorer counts 50k research works in it since 1950. 20.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the dynamics of synchronization in complex networks, focusing on phenomena such as chimera states, reaction-diffusion models, coupled oscillators, and pattern formation. The Kuramoto model and phase oscillators are central to understanding the behavior of synchronization in these systems.

  • Synchronization
  • Chimera States
  • Reaction-Diffusion Model
  • Coupled Oscillators
  • Pattern Formation
  • Network Dynamics
  • Kuramoto Model
  • Phase Oscillators
  • Complex Networks
  • Nonlinear Dynamics
Research works
50k
fractional, since 1950
In the world top 10%
10k
per year above
Top-10% rate
20.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
0%
the tick is no change

Which countries lead Nonlinear Dynamics and Pattern Formation research?

By volume, China and the United States publish the most (1.8k and 512 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.8k works
  2. 2 United States 512 works
  3. 3 India 403 works
  4. 4 Russia 352 works
  5. 5 Germany 222 works
  6. 6 Japan 220 works
  7. 7 France 198 works
  8. 8 United Kingdom 166 works
  9. 9 Italy 138 works
  10. 10 Spain 114 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 44.0%United States: 12.3%India: 9.7%Russia: 8.5%6 others listed: 25.5%44%largest
China1,828 · 44.0%United States512 · 12.3%India403 · 9.7%Russia352 · 8.5%6 others listed1,060 · 25.5%

Shares of the rows listed above, not of the whole node.

Which institutions lead Nonlinear Dynamics and Pattern Formation research?

By volume in 2022–2025, Harbin Institute of Technology publishes the most Nonlinear Dynamics and Pattern Formation research, followed by Yaroslavl State University and Southeast University.

Who are the leading researchers in Nonlinear Dynamics and Pattern Formation?

The most-cited researchers publishing on Nonlinear Dynamics and Pattern Formation include H. Eugene Stanley, Guanrong Chen and Peng Shi.

  1. 1 H. Eugene Stanley United States 5.5k citations
  2. 2 Guanrong Chen Hong Kong 5.4k citations
  3. 3 Peng Shi Australia 5k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Nonlinear Dynamics and Pattern Formation research done?

The largest centres of Nonlinear Dynamics and Pattern Formation research in 2022–2025 are Beijing (China), Nanjing (China), Shanghai (China) and Moscow (Russia). Among places with at least 20 works in it, it is an unusually large share of all research in Yaroslavl and Saratov.

Largest cities, 2022–2025

  1. 1 Beijing China 179 works
  2. 2 Nanjing China 127 works
  3. 3 Shanghai China 122 works
  4. 4 Moscow Russia 104 works
  5. 5 Xi'an China 92 works
  6. 6 Wuhan China 81 works
  7. 7 Harbin China 80 works
  8. 8 Tokyo Japan 75 works
  9. 9 Chengdu China 67 works
  10. 10 Guangzhou China 63 works

Where it is the local speciality

  1. YaroslavlRU · 35.0 works43×
  2. SaratovRU · 22.8 works18×
← less than its size predictsmore →

Location quotient: how much more of its research is in Nonlinear Dynamics and Pattern Formation than the world average.

See Nonlinear Dynamics and Pattern Formation on the map

Where is the best place to study Nonlinear Dynamics and Pattern Formation?

Among universities, judged by research, Indian Statistical Institute, Central China Normal University and Université de Dschang score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%25%50%75%mean 31.41%fractional works in this node (log) →share in the world top 10% →Indian Statistical Institute: 12, 71.4%Central China Normal University: 16, 64.2%Université de Dschang: 13, 12.6%Shandong Normal University: 11, 39.3%Amirkabir University of Technology: 11, 29.2%N. I. Lobachevsky State University of Nizhny Novgorod: 15, 11.1%Huaqiao University: 16, 23.0%Yaroslavl State University: 34, 1.0%Qufu Normal University: 9, 29.4%Xinjiang University: 19, 32.9%Indian Statistical I…Central China Normal…Shandong Normal Univ…Université de Dschang
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Indian Statistical InstituteIndia 77.371.4%26.0×12 +609.6%
2 Central China Normal UniversityChina 65.464.2%11.6×16 +6.1%
3 Université de DschangCameroon 54.712.6%23.8×13 +287.4%
4 Shandong Normal UniversityChina 53.739.3%8.1×11 +163.7%
5 Amirkabir University of TechnologyIran 52.629.2%8.4×11 +162.8%
6 N. I. Lobachevsky State University of Nizhny NovgorodRussia 52.511.1%21.0×15 +248.5%
7 Huaqiao UniversityChina 51.923.0%15.9×16 +78.9%
8 Yaroslavl State UniversityRussia 51.31.0%114.6×34 +87.1%
9 Qufu Normal UniversityChina 50.829.4%9.2×9 +187.5%
10 Xinjiang UniversityChina 49.032.9%8.2×19 +20.8%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Nonlinear Dynamics and Pattern Formation research growing?

Output in 2018–2022 was 0% lower than in 2013–2017, peaking in 2013. The fastest-growing topics are Nonlinear Dynamics and Pattern Formation.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.