Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A magnetospheric magnetic field model with a warped tail current sheet
Countries citing papers authored by N. A. Tsyganenko
Since
Specialization
Citations
This map shows the geographic impact of N. A. Tsyganenko'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 N. A. Tsyganenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. A. Tsyganenko more than expected).
Fields of papers citing papers by N. A. Tsyganenko
This network shows the impact of papers produced by N. A. Tsyganenko. 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 N. A. Tsyganenko. The network helps show where N. A. Tsyganenko may publish in the future.
Co-authorship network of co-authors of N. A. Tsyganenko
This figure shows the co-authorship network connecting the top 25 collaborators of N. A. Tsyganenko.
A scholar is included among the top collaborators of N. A. Tsyganenko 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 N. A. Tsyganenko. N. A. Tsyganenko is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tsyganenko, N. A.. (2013). Data-Based Mapping of Our Dynamical Magnetosphere (Julius Bartels Medal Lecture). EGU General Assembly Conference Abstracts. 14184.1 indexed citations
12.
Brandt, P. C., D. G. Mitchell, D. A. Gurnett, A. M. Persoon, & N. A. Tsyganenko. (2012). Saturn's Periodic Magnetosphere: The Relation Between Periodic Hot Plasma Injections, a Rotating Partial Ring Current, Global Magnetic Field Distortions, Plasmapause Motion, and Radio Emissions. EGUGA. 12906.1 indexed citations
13.
Tsyganenko, N. A. & M. I. Sitnov. (2005). Modeling the dynamics of the inner magnetosphere during strong geomagnetic storms. Journal of Geophysical Research Atmospheres. 110(A3).871 indexed citations breakdown →
14.
Murata, Ken T., Daisuke Matsuoka, Eizen Kimura, et al.. (2005). Development of the Virtual Earth's Magnetosphere System (VEMS). Institutional Repository National Institute of Polar Research (National Institute of Polar Research (Japan)). 19(42). 135–151.2 indexed citations
15.
Khurana, K. K., et al.. (2004). A model of Jupiter's global magnetospheric field: Construction and comparison with data. cosp. 35. 2073.1 indexed citations
16.
Khurana, K. K. & N. A. Tsyganenko. (2002). A Global Model of Jupiter's Magnetospheric Field. AGU Fall Meeting Abstracts. 2002.1 indexed citations
17.
Tsyganenko, N. A.. (2001). A new Model of the Inner/Near Magnetosphere, Based on ISTP Space Magnetometer Data. AGU Spring Meeting Abstracts. 2001.1 indexed citations
18.
Tsyganenko, N. A.. (1989). 'Global' quantitative models of the geomagnetic field in the magnetosphere's prelunar region at different disturbance levels. 12. 5–21.1 indexed citations
19.
Tsyganenko, N. A., et al.. (1982). Large-scale magnetic effects of field-aligned currents in the magnetosphere. 1. 60–64.1 indexed citations
20.
Tsyganenko, N. A.. (1981). Numerical models of quiet and disturbed geomagnetic field in the cislunar part of the magnetosphere.. Annales de Geophysique. 37. 381–391.9 indexed citations
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.