Martin V. Day
- Statistical and Nonlinear Physics top 5%
- Mathematical Physics top 10%
- Computational Theory and Mathematics top 10%
- Control and Systems Engineering
- Computer Networks and Communications
- Co-authors
- Joseph A. BallPushkin KachrooThomas A. DardenGuodong PangJohn R. HallWilliam M. McEneaney
- Topics
- Stochastic processes and statistical mechanics (9 papers)Quantum chaos and dynamical systems (9 papers)stochastic dynamics and bifurcation (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaAutomaticaJournal of Mathematical Analysis and Applications
- Partner nations
- United StatesRussia
In The Last Decade
Martin V. Day
32 papers receiving 330 citations
Peers
Comparison fields: 5 of 51
- Statistical and Nonlinear Physics 190
- Mathematical Physics 101
- Computational Theory and Mathematics 61
- Control and Systems Engineering 60
- Computer Networks and Communications 59
Countries citing papers authored by Martin V. Day
This map shows the geographic impact of Martin V. Day'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 Martin V. Day with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin V. Day more than expected).
Fields of papers citing papers by Martin V. Day
This network shows the impact of papers produced by Martin V. Day. 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 Martin V. Day. The network helps show where Martin V. Day may publish in the future.
Co-authorship network of co-authors of Martin V. Day
This figure shows the co-authorship network connecting the top 25 collaborators of Martin V. Day. A scholar is included among the top collaborators of Martin V. Day 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 Martin V. Day. Martin V. Day is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 6 | |
| 4 | 2 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 14 | |
| 9 | On Lagrange Manifolds and Viscosity Solutions | 18 |
| 10 | 12 | |
| 11 | 10 | |
| 12 | 12 | |
| 13 | 24 | |
| 14 | 10 | |
| 15 | 56 | |
| 16 | 1 | |
| 17 | 15 | |
| 18 | 10 | |
| 19 | 2 | |
| 20 | 19 |
About Martin V. Day
Martin V. Day is a scholar working on Mathematical Physics, Statistical and Nonlinear Physics and Theoretical Computer Science, having authored 34 papers that have together received 374 indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (9 papers), Quantum chaos and dynamical systems (9 papers) and stochastic dynamics and bifurcation (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (190 citations), Mathematical Physics (101 citations) and Finance (40 citations). Martin V. Day has collaborated with scholars based in United States and Russia. Frequent co-authors include Joseph A. Ball, Pushkin Kachroo, Thomas A. Darden, Guodong Pang, John R. Hall and William M. McEneaney. Their work appears in journals such as SHILAP Revista de lepidopterología, Automatica and Journal of Mathematical Analysis and Applications.
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.