James Turtle
Impact in
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
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- Magnetic properties of thin films
- Quantum and electron transport phenomena
Papers in
-
- COVID-19 epidemiological studies 5
-
- Solar and Space Plasma Dynamics 4
- Ionosphere and magnetosphere dynamics 3
- Co-authors
- Patrick Longhini (3 shared papers)Pete Riley (5 shared papers)Antonio Palacios (3 shared papers)Visarath In (3 shared papers)M. Ben-Nun (5 shared papers)Steven Riley (3 shared papers)David Bacon (2 shared papers)Pietro-Luciano Buono (2 shared papers)
- Journals
- PLoS Computational Biology (2 papers)The Astrophysical Journal (2 papers)Epidemics (1 paper)Physica D Nonlinear Phenomena (1 paper)Journal of Applied Physics (1 paper)
- Partner nations
- United StatesUnited KingdomFinland
In The Last Decade
James Turtle
12 papers receiving 67 citations
Peers
Comparison fields: 5 of 32
- Modeling and Simulation 20
- Atomic and Molecular Physics, and Optics 26
- Statistical and Nonlinear Physics 9
- Condensed Matter Physics 8
- Computer Networks and Communications 14
Countries citing papers authored by James Turtle
This map shows the geographic impact of James Turtle'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 James Turtle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Turtle more than expected).
Fields of papers citing papers by James Turtle
This network shows the impact of papers produced by James Turtle. 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 James Turtle. The network helps show where James Turtle may publish in the future.
Co-authors
The 25 scholars most cited alongside James Turtle, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 18 | |
| 2 | 2019 | 14 | |
| 3 | 2017 | 14 | |
| 4 | 2022 | 4 | |
| 5 | 2021 | 3 | |
| 6 | 2021 | 3 | |
| 7 | 2019 | 3 | |
| 8 | 2024 | 2 | |
| 9 | 2023 | 2 | |
| 10 | 2024 | 2 | |
| 11 | 2024 | 2 | |
| 12 | Numerical exploration of the dynamics of coupled spin torque nano oscillators | 2012 | 1 |
| 13 | 2024 | 0 |
About James Turtle
James Turtle is a scholar working on Modeling and Simulation, Astronomy and Astrophysics, Atomic and Molecular Physics, and Optics, Molecular Biology and Epidemiology, having authored 13 papers that have together received 68 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (5 papers), Solar and Space Plasma Dynamics (4 papers), Ionosphere and magnetosphere dynamics (3 papers), Influenza Virus Research Studies (3 papers), Geomagnetism and Paleomagnetism Studies (3 papers), Magnetic properties of thin films (3 papers), Quantum and electron transport phenomena (2 papers) and Nonlinear Dynamics and Pattern Formation (2 papers). The work is most often cited by research in Modeling and Simulation (20 citations), Atomic and Molecular Physics, and Optics (26 citations), Statistical and Nonlinear Physics (9 citations), Condensed Matter Physics (8 citations) and Computer Networks and Communications (14 citations). James Turtle has collaborated with scholars based in United States, United Kingdom and Finland. Frequent co-authors include Patrick Longhini, Pete Riley, Antonio Palacios, Visarath In, M. Ben-Nun, Steven Riley, David Bacon, Pietro-Luciano Buono, Allison Riley and Cooper Downs. Their work appears in journals such as PLoS Computational Biology, The Astrophysical Journal, Epidemics, Physica D Nonlinear Phenomena and Journal of Applied Physics.
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.