Countries where authors publish in Potential Analysis
Since Specialization
Citations
This map shows the geographic impact of research published in Potential Analysis. 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 papers published in Potential Analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Potential Analysis more than expected).
This network shows the impact of papers published in Potential Analysis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Potential Analysis.
About Potential Analysis
The 1.3k papers published in Potential Analysis in the last decades have received a total of 13.9k indexed citations . Papers published in Potential Analysis usually cover Applied Mathematics (914 papers), Mathematical Physics (694 papers), Computational Theory and Mathematics (443 papers), Finance (254 papers) and Geometry and Topology (214 papers) specifically the topics of Nonlinear Partial Differential Equations (427 papers), Advanced Mathematical Modeling in Engineering (408 papers), Advanced Harmonic Analysis Research (271 papers), Stochastic processes and financial applications (252 papers), Geometric Analysis and Curvature Flows (237 papers), Numerical methods in inverse problems (165 papers), Spectral Theory in Mathematical Physics (159 papers) and Differential Equations and Boundary Problems (135 papers). The most active scholars publishing in Potential Analysis are István Gyöngy, Piotr Hajłasz, Laurent Decreusefond, Ali Süleyman Üstünel, Tusheng Zhang, Zdzisław Brzeźniak, Masatoshi Fukushima, Erika Hausenblas, Michał Ryznar and Mingshang Hu.
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.