Science Explorer Interactive view Map

Theoretical and Computational Physics

Theoretical and Computational Physics is a research topic within Condensed Matter Physics. Science Explorer counts 69k research works in it since 1950. 18.3% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores various aspects of critical phenomena, including phase transitions, random walk algorithms, renormalization-group theory, self-organized criticality, fractal dimension, percolation theory, spin glasses, and Monte Carlo simulations. The research covers a wide range of topics related to the behavior of physical systems near critical points and provides insights into universality classes and complex system dynamics.

  • Phase Transitions
  • Critical Phenomena
  • Random Walk Algorithm
  • Renormalization-group Theory
  • Self-organized Criticality
  • Fractal Dimension
  • Percolation Theory
  • Spin Glasses
  • Monte Carlo Simulation
  • Universality Classes
Research works
69k
fractional, since 1950
In the world top 10%
13k
per year above
Top-10% rate
18.3%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-13%
the tick is no change

Which countries lead Theoretical and Computational Physics research?

By volume, the United States and China publish the most (694 and 507 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 694 works
  2. 2 China 507 works
  3. 3 France 327 works
  4. 4 Germany 290 works
  5. 5 Russia 255 works
  6. 6 Japan 247 works
  7. 7 India 242 works
  8. 8 United Kingdom 179 works
  9. 9 Italy 164 works
  10. 10 Brazil 149 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.

United States: 22.7%China: 16.6%France: 10.7%Germany: 9.5%6 others listed: 40.5%23%largest
United States694 · 22.7%China507 · 16.6%France327 · 10.7%Germany290 · 9.5%6 others listed1,236 · 40.5%

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

Which institutions lead Theoretical and Computational Physics research?

By volume in 2022–2025, Centre National de la Recherche Scientifique publishes the most Theoretical and Computational Physics research, followed by The University of Tokyo and Princeton University.

Who are the leading researchers in Theoretical and Computational Physics?

The most-cited researchers publishing on Theoretical and Computational Physics include John A. Pople, J. Häfner and John P. Perdew.

  1. 1 John A. Pople United States 11k citations
  2. 2 J. Häfner Austria 11k citations
  3. 3 John P. Perdew United States 9.9k citations
  4. 4 H. P. Beck France 7.5k citations

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

Where is Theoretical and Computational Physics research done?

The largest centres of Theoretical and Computational Physics research in 2022–2025 are Paris (France), Beijing (China), Tokyo (Japan) and Moscow (Russia). Among places with at least 20 works in it, it is an unusually large share of all research in Trieste.

Largest cities, 2022–2025

  1. 1 Paris France 144 works
  2. 2 Beijing China 122 works
  3. 3 Tokyo Japan 91 works
  4. 4 Moscow Russia 90 works
  5. 5 Rome Italy 45 works
  6. 6 New York United States 43 works
  7. 7 Shanghai China 40 works
  8. 8 London United Kingdom 36 works
  9. 9 Nanjing China 32 works
  10. 10 Kolkata India 30 works

Where it is the local speciality

  1. TriesteIT · 26.6 works16×
← less than its size predictsmore →

Location quotient: how much more of its research is in Theoretical and Computational Physics than the world average.

See Theoretical and Computational Physics on the map

Where is the best place to study Theoretical and Computational Physics?

Among universities, judged by research, Shenyang University of Technology, Université Paris-Saclay and Indian Institute of Technology Ropar 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%mean 24.48%fractional works in this node (log) →share in the world top 10% →Shenyang University of Technology: 12, 58.3%Université Paris-Saclay: 16, 18.4%Indian Institute of Technology Ropar: 9, 20.7%Princeton University: 20, 25.4%Sorbonne Université: 18, 29.6%Scuola Internazionale Superiore di Studi Avanzati: 10, 16.7%California Institute of Technology: 10, 23.3%Massachusetts Institute of Technology: 19, 24.8%École Polytechnique Fédérale de Lausanne: 13, 22.5%Ural Federal University: 10, 5.1%Shenyang University …Princeton UniversityIndian Institute of …Université Paris-Sac…
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 Shenyang University of TechnologyChina 74.458.3%13.4×12 +231.2%
2 Université Paris-SaclayFrance 53.918.4%10.4×16
3 Indian Institute of Technology RoparIndia 52.620.7%17.9×9 +203.6%
4 Princeton UniversityUnited States 52.425.4%11.2×20 -12.1%
5 Sorbonne UniversitéFrance 52.329.6%9.0×18 -30.1%
6 Scuola Internazionale Superiore di Studi AvanzatiItaly 47.616.7%56.2×10 +48.1%
7 California Institute of TechnologyUnited States 46.523.3%10.0×10 +22.8%
8 Massachusetts Institute of TechnologyUnited States 46.224.8%7.5×19 +5.5%
9 École Polytechnique Fédérale de LausanneSwitzerland 43.822.5%7.6×13 +5.9%
10 Ural Federal UniversityRussia 41.45.1%8.2×10 +281.5%

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 Theoretical and Computational Physics research growing?

Output in 2018–2022 was 13% lower than in 2013–2017, peaking in 2000.

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.