Nicolas Dirr

31 papers receiving 249 citations

Peers

Nicolas Dirr
Comparison fields: 5 of 43
  • Applied Mathematics 95
  • Mathematical Physics 82
  • Computational Theory and Mathematics 107
  • Statistical and Nonlinear Physics 58
  • Condensed Matter Physics 53
Replace Maria G. Reznikoff with:
Maria G. Reznikoff United States
Matías G. Delgadino United States
Stanislaus Maier‐Paape Germany
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Charles K. Smart United States
Simone Di Marino Italy
Frédéric Hérau France
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Citations per year

Countries citing papers authored by Nicolas Dirr

Since Specialization
Citations

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

Fields of papers citing papers by Nicolas Dirr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Nicolas Dirr, 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 Nicolas Dirr Line = papers co-authored together Nicolas Dirr links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200636
2
2 Large deviations and gradient flows
201233
3 200125
4 200822
5 200514
6 201014
7 201913
8 201812
9 200611
10 20118
11 20068
12 20127
13 20086
14 20166
15 20066
16 20245
17 20105
18 20195
19 20104
20 20044

About Nicolas Dirr

Nicolas Dirr is a scholar working on Mathematical Physics, Computational Theory and Mathematics, Applied Mathematics, Condensed Matter Physics and Statistical and Nonlinear Physics, having authored 36 papers that have together received 268 indexed citations. Recurring topics across this work include Advanced Mathematical Modeling in Engineering (17 papers), Stochastic processes and statistical mechanics (13 papers), Nonlinear Partial Differential Equations (11 papers), Theoretical and Computational Physics (9 papers), Geometric Analysis and Curvature Flows (9 papers), Markov Chains and Monte Carlo Methods (6 papers), Solidification and crystal growth phenomena (5 papers) and Stochastic processes and financial applications (4 papers). The work is most often cited by research in Applied Mathematics (95 citations), Mathematical Physics (82 citations), Computational Theory and Mathematics (107 citations), Statistical and Nonlinear Physics (58 citations) and Condensed Matter Physics (53 citations). Nicolas Dirr has collaborated with scholars based in United Kingdom, Germany and Italy. Frequent co-authors include Nung Kwan Yip, Johannes Zimmer, Matteo Novaga, Stephan Luckhaus, Stefan Adams, Mark A. Peletier, Panagiotis E. Souganidis, Georgia Karali, Celia Reina and Anna De Masi. Their work appears in journals such as SIAM Journal on Mathematical Analysis, Interfaces and Free Boundaries Mathematical Analysis Computation and Applications, Journal of the Mechanics and Physics of Solids, Communications in Mathematical Physics and Journal of Statistical 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.

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