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Topic · Statistical and Nonlinear Physics

Chaos control and synchronization

Chaos control and synchronization is a research topic within Statistical and Nonlinear Physics. Science Explorer counts 27k research works in it since 1950. 20.4% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on chaos synchronization and control in complex systems, exploring topics such as nonlinear dynamics, time series analysis, recurrence plots, and the synchronization of chaotic systems. It covers applications in various fields such as communication, finance, and engineering.

  • Chaos
  • Synchronization
  • Complex Systems
  • Nonlinear Dynamics
  • Time Series Analysis
  • Control
  • Recurrence Plots
  • Attractors
  • Fractional Order Systems
  • Adaptive Synchronization
Research works
27k
fractional, since 1950
In the world top 10%
5.5k
per year above
Top-10% rate
20.4%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+0%
the tick is no change

Which countries lead Chaos control and synchronization research?

By volume, China and India publish the most (1.4k and 286 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.4k works
  2. 2 India 286 works
  3. 3 United States 160 works
  4. 4 Russia 113 works
  5. 5 Japan 82 works
  6. 6 France 80 works
  7. 7 Türkiye 78 works
  8. 8 Brazil 78 works
  9. 9 Mexico 75 works
  10. 10 Iran 71 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: 57.0%India: 12.0%United States: 6.7%Russia: 4.8%6 others listed: 19.5%57%largest
China1,352 · 57.0%India286 · 12.0%United States160 · 6.7%Russia113 · 4.8%6 others listed463 · 19.5%

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

Which institutions lead Chaos control and synchronization research?

By volume in 2022–2025, Heilongjiang University publishes the most Chaos control and synchronization research, followed by Northwest Normal University and Central South University.

By volume, 2022–2025

  1. 1 Heilongjiang UniversityChina 27 works
  2. 2 Northwest Normal UniversityChina 26 works
  3. 3 Central South UniversityChina 21 works
  4. 4 Northeastern UniversityChina 20 works
  5. 5 Harbin Institute of TechnologyChina 18 works
  6. 6 Guangdong University of TechnologyChina 17 works
  7. 7 Nanjing University of Information Science and TechnologyChina 16 works
  8. 8 Southwest UniversityChina 16 works
  9. 9 Université de DschangCameroon 16 works
  10. 10 Nanjing University of Aeronautics and AstronauticsChina 15 works

Who are the leading researchers in Chaos control and synchronization?

The most-cited researchers publishing on Chaos control and synchronization 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
  4. 4 Zidong Wang United Kingdom 4.4k citations
  5. 5 Jinde Cao China 4.2k citations
  6. 6 Leon O. Chua United States 4.1k citations
  7. 7 Qing‐Long Han Australia 3.8k citations

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

Where is Chaos control and synchronization research done?

The largest centres of Chaos control and synchronization research in 2022–2025 are Beijing (China), Nanjing (China), Xi'an (China) and Harbin (China).

Largest cities, 2022–2025

  1. 1 Beijing China 104 works
  2. 2 Nanjing China 91 works
  3. 3 Xi'an China 73 works
  4. 4 Harbin China 64 works
  5. 5 Changsha China 56 works
  6. 6 Guangzhou China 55 works
  7. 7 Chongqing China 52 works
  8. 8 Wuhan China 51 works
  9. 9 Jinan China 50 works
  10. 10 Shanghai China 48 works
See Chaos control and synchronization on the map

Where is the best place to study Chaos control and synchronization?

Among universities, judged by research, Changzhou University, Xiangtan University and Northwest Normal University 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 37.69%fractional works in this node (log) →share in the world top 10% →Changzhou University: 11, 64.7%Xiangtan University: 9, 51.9%Northwest Normal University: 26, 32.8%Xi'an University of Technology: 11, 46.0%Heilongjiang University: 27, 31.5%Université de Dschang: 16, 14.2%Nanjing University of Information Science and Technology: 16, 26.9%East China Jiaotong University: 11, 46.3%Southwest University: 16, 24.2%Saint Petersburg State Electrotechnical University: 10, 38.4%Changzhou UniversityXiangtan UniversityXi'an University of …Northwest Normal Uni…
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 Changzhou UniversityChina 75.864.7%12.7×11 +386.2%
2 Xiangtan UniversityChina 67.251.9%11.5×9 +378.6%
3 Northwest Normal UniversityChina 65.832.8%33.4×26 —
4 Xi'an University of TechnologyChina 63.946.0%10.3×11 +146.4%
5 Heilongjiang UniversityChina 63.831.5%47.6×27 +16.5%
6 Université de DschangCameroon 62.614.2%47.4×16 +359.0%
7 Nanjing University of Information Science and TechnologyChina 61.826.9%12.3×16 +99.7%
8 East China Jiaotong UniversityChina 58.446.3%25.7×11 —
9 Southwest UniversityChina 56.724.2%8.9×16 +128.0%
10 Saint Petersburg State Electrotechnical UniversityRussia 53.238.4%33.0×10 —

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 Chaos control and synchronization research growing?

Output in 2018–2022 was 0% higher than in 2013–2017, peaking in 2025.

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.