V. V. Uchaikin
- Modeling and Simulation top 0.1%
- Statistical and Nonlinear Physics top 0.5%
- Numerical Analysis top 2%
- Applied Mathematics top 1%
- Mathematical Physics top 2%
- Co-authors
- В. М. ЗолотаревRenat T. SibatovBernardo SpagnoloA. A. DubkovА. А. ЛагутинDexter CahoyWojbor A. WoyczyńskiVassili N. Kolokoltsov
- Topics
- Fractional Differential Equations Solutions (57 papers)Theoretical and Computational Physics (20 papers)Differential Equations and Numerical Methods (14 papers)
- Journals
- Journal of Power SourcesJournal of Computational PhysicsPhysica A Statistical Mechanics and its Applications
- Partner nations
- RussiaUnited KingdomUnited States
In The Last Decade
V. V. Uchaikin
109 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Modeling and Simulation 1.4k
- Statistical and Nonlinear Physics 866
- Numerical Analysis 427
- Applied Mathematics 392
- Mathematical Physics 317
Countries citing papers authored by V. V. Uchaikin
This map shows the geographic impact of V. V. Uchaikin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by V. V. Uchaikin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. V. Uchaikin more than expected).
Fields of papers citing papers by V. V. Uchaikin
This network shows the impact of papers produced by V. V. Uchaikin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by V. V. Uchaikin. The network helps show where V. V. Uchaikin may publish in the future.
Co-authorship network of co-authors of V. V. Uchaikin
This figure shows the co-authorship network connecting the top 25 collaborators of V. V. Uchaikin. A scholar is included among the top collaborators of V. V. Uchaikin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with V. V. Uchaikin. V. V. Uchaikin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 9 | |
| 7 | 5 | |
| 8 | 17 | |
| 9 | 53 | |
| 10 | 56 | |
| 11 | 10 | |
| 12 | 32 | |
| 13 | If the Universe Were a Levy-Mandelbrot Fractal | 2 |
| 14 | 7 | |
| 15 | Fractional diffusion of cosmic rays | 3 |
| 16 | 303 | |
| 17 | 1 | |
| 18 | 0 | |
| 19 | Adjoint Approach to EAS Problem | 1 |
| 20 | The Radial Distribution of Electromagnetic Cascade Particles in the Air | 1 |
About V. V. Uchaikin
V. V. Uchaikin is a scholar working on Modeling and Simulation, Numerical Analysis and Statistical and Nonlinear Physics, having authored 122 papers that have together received 2.8k indexed citations. Recurring topics across this work include Fractional Differential Equations Solutions (57 papers), Theoretical and Computational Physics (20 papers) and Differential Equations and Numerical Methods (14 papers). The work is most often cited by research in Modeling and Simulation (1.4k citations), Numerical Analysis (427 citations) and Statistical and Nonlinear Physics (866 citations). V. V. Uchaikin has collaborated with scholars based in Russia, United Kingdom and United States. Frequent co-authors include В. М. Золотарев, Renat T. Sibatov, Bernardo Spagnolo, A. A. Dubkov, А. А. Лагутин, Dexter Cahoy, Wojbor A. Woyczyński, Vassili N. Kolokoltsov, V. Yu. Korolev and S. A. Ambrozevich. Their work appears in journals such as Journal of Power Sources, Journal of Computational Physics and Physica A Statistical Mechanics and its Applications.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.