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Nonlinear Partial Differential Equations

Nonlinear Partial Differential Equations is a research topic within Applied Mathematics. Science Explorer counts 25k research works in it since 1956. 17.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the theory of fractional Laplacian operators, including topics such as Sobolev spaces, nonlinear equations, regularity theory, variational problems, critical exponents, ground state solutions, elliptic equations, nonlocal operators, and Hamiltonian estimates.

  • Fractional Laplacian
  • Sobolev Spaces
  • Nonlinear Equations
  • Regularity Theory
  • Variational Problems
  • Critical Exponents
  • Ground State Solutions
  • Elliptic Equations
  • Nonlocal Operators
  • Hamiltonian Estimates
Research works
25k
fractional, since 1956
In the world top 10%
4.5k
per year above
Top-10% rate
17.9%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+19%
the tick is no change

Which countries lead Nonlinear Partial Differential Equations research?

By volume, China and Italy publish the most (1.5k and 377 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.5k works
  2. 2 Italy 377 works
  3. 3 United States 335 works
  4. 4 Brazil 198 works
  5. 5 France 178 works
  6. 6 Germany 164 works
  7. 7 Morocco 150 works
  8. 8 Japan 145 works
  9. 9 Spain 117 works
  10. 10 Russia 109 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: 45.9%Italy: 11.5%United States: 10.2%Brazil: 6.1%6 others listed: 26.3%46%largest
China1,505 · 45.9%Italy377 · 11.5%United States335 · 10.2%Brazil198 · 6.1%6 others listed862 · 26.3%

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

Which institutions lead Nonlinear Partial Differential Equations research?

By volume in 2022–2025, Southwest University publishes the most Nonlinear Partial Differential Equations research, followed by Université Sultan Moulay Slimane and Central South University.

Who are the leading researchers in Nonlinear Partial Differential Equations?

The most-cited researchers publishing on Nonlinear Partial Differential Equations include Terence Tao, Louis Nirenberg and Élliott H. Lieb.

  1. 1 Terence Tao United States 3.1k citations
  2. 2 Louis Nirenberg United States 2.9k citations
  3. 3 Élliott H. Lieb United States 2.5k citations
  4. 4 Shing–Tung Yau United States 2.1k citations
  5. 5 Xiaodong Wang United States 2k citations
  6. 6 Liqun Zhang China 2k citations
  7. 7 Pierre‐Louis Lions France 1.7k citations

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

Where is Nonlinear Partial Differential Equations research done?

The largest centres of Nonlinear Partial Differential Equations research in 2022–2025 are Beijing (China), Chongqing (China), Shanghai (China) and Wuhan (China). Among places with at least 20 works in it, it is an unusually large share of all research in Beni Mellal and Qazvin.

Largest cities, 2022–2025

  1. 1 Beijing China 255 works
  2. 2 Chongqing China 78 works
  3. 3 Shanghai China 75 works
  4. 4 Wuhan China 72 works
  5. 5 Changsha China 64 works
  6. 6 Paris France 60 works
  7. 7 Guangzhou China 58 works
  8. 8 Nanjing China 55 works
  9. 9 Moscow Russia 47 works
  10. 10 Rome Italy 47 works

Where it is the local speciality

  1. Beni MellalMA · 44.8 works74×
  2. QazvinIR · 20.7 works36×
← less than its size predictsmore →

Location quotient: how much more of its research is in Nonlinear Partial Differential Equations than the world average.

See Nonlinear Partial Differential Equations on the map

Where is the best place to study Nonlinear Partial Differential Equations?

Among universities, judged by research, Marche Polytechnic University, Université Sultan Moulay Slimane and Bielefeld 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%20%40%60%mean 27.83%fractional works in this node (log) →share in the world top 10% →Marche Polytechnic University: 11, 53.4%Université Sultan Moulay Slimane: 45, 37.3%Bielefeld University: 11, 44.0%Beijing Normal University: 37, 29.6%Shandong University of Science and Technology: 21, 22.0%Sidi Mohamed Ben Abdellah University: 26, 13.2%Tunis El Manar University: 16, 14.8%Guangzhou University: 22, 24.6%National Institute for Mathematical Sciences: 8, 26.6%Southwest University: 50, 12.8%Marche Polytechnic U…Bielefeld UniversityUniversité Sultan Mo…Beijing Normal Unive…
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 Marche Polytechnic UniversityItaly 76.853.4%13.3×11 +248.6%
2 Université Sultan Moulay SlimaneMorocco 72.637.3%74.2×45
3 Bielefeld UniversityGermany 64.744.0%10.9×11 +96.1%
4 Beijing Normal UniversityChina 64.229.6%12.3×37 +5.9%
5 Shandong University of Science and TechnologyChina 62.522.0%9.6×21 +377.2%
6 Sidi Mohamed Ben Abdellah UniversityMorocco 62.113.2%21.8×26 +649.5%
7 Tunis El Manar UniversityTunisia 60.914.8%21.2×16 +256.2%
8 Guangzhou UniversityChina 60.624.6%13.8×22 +82.7%
9 National Institute for Mathematical SciencesSouth Korea 59.926.6%180.9×8 +456.4%
10 Southwest UniversityChina 58.812.8%21.0×50 +36.8%

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 Partial Differential Equations research growing?

Output in 2018–2022 was 19% higher than in 2013–2017, peaking in 2022. The fastest-growing topics are Nonlinear Partial Differential Equations.

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.