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 1.4k papers published in Potential Analysis in the last decades have received a total of 14.7k indexed citations . Papers published in Potential Analysis usually cover Applied Mathematics (974 papers), Mathematical Physics (735 papers), Finance (263 papers), Computational Theory and Mathematics (480 papers) and Geometry and Topology (226 papers) specifically the topics of Nonlinear Partial Differential Equations (461 papers), Advanced Mathematical Modeling in Engineering (443 papers), Advanced Harmonic Analysis Research (291 papers), Stochastic processes and financial applications (261 papers), Geometric Analysis and Curvature Flows (253 papers), Numerical methods in inverse problems (174 papers), Spectral Theory in Mathematical Physics (167 papers) and advanced mathematical theories (141 papers). The most active scholars publishing in Potential Analysis are Piotr Hajłasz, István Gyöngy, Laurent Decreusefond, Ali Süleyman Üstünel, Tusheng Zhang, Zdzisław Brzeźniak, Erika Hausenblas, Masatoshi Fukushima, Michał Ryznar and Mahamadi Warma.
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.