Matrix Theory and Algorithms
Matrix Theory and Algorithms is a research topic within Computational Theory and Mathematics. Science Explorer counts 50k research works in it since 1950. 12.4% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on matrix algorithms, iterative methods, and numerical techniques for solving eigenvalue problems, preconditioning sparse linear systems, and addressing saddle point problems. It covers topics such as Krylov subspace methods, structured preconditioners, parallel computing, and numerical linear algebra.
- Matrix Computations
- Numerical Linear Algebra
- Preconditioning Techniques
- Iterative Methods
- Eigenvalue Problems
- Sparse Linear Systems
- Krylov Subspace Methods
- Saddle Point Problems
- Structured Preconditioners
- Parallel Computing
- Research works
- 50k fractional, since 1950
- In the world top 10%
- 6.3k per year above
- Top-10% rate
- 12.4% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -6% the tick is no change
Which countries lead Matrix Theory and Algorithms research?
By volume, China and the United States publish the most (1.2k and 756 works in 2022–2025).
By volume, 2022–2025
- 1 China 1.2k works
- 2 United States 756 works
- 3 India 362 works
- 4 Germany 263 works
- 5 Russia 229 works
- 6 France 179 works
- 7 Italy 156 works
- 8 Japan 147 works
- 9 United Kingdom 143 works
- 10 Iran 130 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.
Shares of the rows listed above, not of the whole node.
Which institutions lead Matrix Theory and Algorithms research?
By volume in 2022–2025, University of Nis publishes the most Matrix Theory and Algorithms research, followed by University of Sfax and Shanghai University.
By volume, 2022–2025
- 1 University of NisSerbia 33 works
- 2 University of SfaxTunisia 31 works
- 3 Shanghai UniversityChina 30 works
- 4 Technical University of MunichGermany 29 works
- 5 Lomonosov Moscow State UniversityRussia 25 works
- 6 Southeast UniversityChina 23 works
- 7 University of OxfordUnited Kingdom 22 works
- 8 Centre National de la Recherche ScientifiqueFrance 20 works
- 9 Charles UniversityCzechia 19 works
- 10 University of FreiburgGermany 19 works
Who are the leading researchers in Matrix Theory and Algorithms?
The most-cited researchers publishing on Matrix Theory and Algorithms include Stanley Osher, Guanrong Chen and Peng Shi.
- 1 Stanley Osher United States 8k citations
- 2 Guanrong Chen Hong Kong 5.4k citations
- 3 Peng Shi Australia 5k citations
- 4 P. Diţă Germany 4.5k citations
- 5 Vincent D. Blondel Belgium 4.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Matrix Theory and Algorithms research done?
The largest centres of Matrix Theory and Algorithms research in 2022–2025 are Beijing (China), Shanghai (China), Moscow (Russia) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Niš and Sfax.
Largest cities, 2022–2025
Where it is the local speciality
- NišRS · 33.4 works37×
- SfaxTN · 31.5 works15×
Location quotient: how much more of its research is in Matrix Theory and Algorithms than the world average.
Where is the best place to study Matrix Theory and Algorithms?
Among universities, judged by research, Jadavpur University, University of Jordan and Shanghai 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.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Jadavpur UniversityIndia | 72.6 | 34.5% | 9.5× | 14 | +121.6% |
| 2 | University of JordanJordan | 69.4 | 25.7% | 10.5× | 14 | +91.8% |
| 3 | Shanghai UniversityChina | 68.9 | 30.2% | 7.7× | 30 | +10.7% |
| 4 | University of SfaxTunisia | 66.3 | 4.4% | 23.1× | 32 | +165.7% |
| 5 | University of FreiburgGermany | 64.4 | 9.7% | 9.9× | 19 | +450.7% |
| 6 | National Institute of Technology KarnatakaIndia | 64.1 | 20.4% | 12.1× | 12 | +206.7% |
| 7 | Cameron UniversityUnited States | 59.7 | 11.3% | 425.0× | 12 | +199.8% |
| 8 | University of NisSerbia | 58.9 | 9.3% | 37.3× | 33 | -2.9% |
| 9 | Universitat Politècnica de ValènciaSpain | 54.9 | 14.5% | 9.5× | 18 | -1.4% |
| 10 | Indian Institute of Science BangaloreIndia | 52.6 | 26.9% | 6.7× | 14 | -4.2% |
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 Matrix Theory and Algorithms research growing?
Output in 2018–2022 was 6% lower than in 2013–2017, peaking in 2025. The fastest-growing topics are Matrix Theory and Algorithms.
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.