Michael Field

906 citations
34 papers · 533 · h-index 15

Impact in

Papers in

Michael Field

34 papers receiving 489 citations

Peers

Michael Field
Comparison fields: 5 of 91
  • Mathematical Physics 166
  • Statistical and Nonlinear Physics 224
  • Geometry and Topology 88
  • Computer Networks and Communications 199
  • Cognitive Neuroscience 68
Replace Jean-René Chazottes with:
Jean-René Chazottes France
Reiner Lauterbach Germany
A. Yu. Kolesov Russia
J. M. Gambaudo France
Н. Х. Розов Russia
Christopher McCord United States
Evelyn Sander United States
Charles Tresser United States
Frederick R. Marotto United States
Andrei Török United States
Michael Field relative to Jean-René Chazottes France Jean-René Chazottes's profile →
Citations per field
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Jean-René Chazottes · 1×
Citations per year

Countries citing papers authored by Michael Field

Since Specialization
Citations

This map shows the geographic impact of Michael Field'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 Michael Field with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Field more than expected).

Fields of papers citing papers by Michael Field

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Field. 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 Michael Field. The network helps show where Michael Field may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Field, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Field Line = papers co-authored together Michael Field links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199953
2 200446
3 197043
4 200337
5 199337
6 200932
7 200731
8 199928
9 199620
10 199519
11 199618
12 199116
13 201014
14 200514
15 199514
16 200514
17 199912
18 200311
19 201010
20 19949

About Michael Field

Michael Field is a scholar working on Mathematical Physics, Statistical and Nonlinear Physics, Computer Networks and Communications, Geometry and Topology and Molecular Biology, having authored 34 papers that have together received 533 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (11 papers), Mathematical Dynamics and Fractals (11 papers), Quantum chaos and dynamical systems (10 papers), Chaos control and synchronization (5 papers), Homotopy and Cohomology in Algebraic Topology (3 papers), Gene Regulatory Network Analysis (3 papers), Geometry and complex manifolds (2 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Mathematical Physics (166 citations), Statistical and Nonlinear Physics (224 citations), Geometry and Topology (88 citations), Computer Networks and Communications (199 citations) and Cognitive Neuroscience (68 citations). Michael Field has collaborated with scholars based in United States, United Kingdom and Romania. Frequent co-authors include Martin Golubitsky, Ian Melbourne, Peter Ashwin, O.A. Asbjørnsen, Andrei Török, William Parry, Nikita Agarwal, Matthew Nicol, R. Friedberg and Ian Stewart. Their work appears in journals such as Nonlinearity, Dynamical Systems, Memoirs of the American Mathematical Society, Ergodic Theory and Dynamical Systems and Journal of Nonlinear Science.

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.

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