Freddy Bouchet

3.2k total citations
71 papers, 1.9k citations indexed

About

Freddy Bouchet is a scholar working on Statistical and Nonlinear Physics, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Freddy Bouchet has authored 71 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Statistical and Nonlinear Physics, 20 papers in Global and Planetary Change and 18 papers in Atmospheric Science. Recurrent topics in Freddy Bouchet's work include Advanced Thermodynamics and Statistical Mechanics (27 papers), Statistical Mechanics and Entropy (26 papers) and Climate variability and models (17 papers). Freddy Bouchet is often cited by papers focused on Advanced Thermodynamics and Statistical Mechanics (27 papers), Statistical Mechanics and Entropy (26 papers) and Climate variability and models (17 papers). Freddy Bouchet collaborates with scholars based in France, Italy and Japan. Freddy Bouchet's co-authors include Thierry Dauxois, Antoine Venaille, Stefano Ruffo, Marc Hlavacek, Eric Simonnet, Yoshiyuki Y. Yamaguchi, David Mukamel, Francesco Ragone, Jeroen Wouters and Shamik Gupta and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and SHILAP Revista de lepidopterología.

In The Last Decade

Freddy Bouchet

68 papers receiving 1.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Freddy Bouchet France 24 1.0k 329 316 278 275 71 1.9k
Tom Solomon United States 19 829 0.8× 412 1.3× 128 0.4× 106 0.4× 128 0.5× 41 1.7k
J.-F. Pinton France 29 435 0.4× 1.2k 3.8× 261 0.8× 267 1.0× 189 0.7× 62 2.7k
В. В. Лебедев Russia 25 349 0.3× 1.0k 3.1× 262 0.8× 65 0.2× 303 1.1× 170 2.5k
L. Ts. Adzhemyan Russia 22 247 0.2× 805 2.4× 286 0.9× 114 0.4× 225 0.8× 90 1.4k
I. V. Kolokolov Russia 20 269 0.3× 795 2.4× 215 0.7× 47 0.2× 239 0.9× 94 1.9k
N. V. Antonov Russia 24 280 0.3× 1.1k 3.2× 403 1.3× 244 0.9× 273 1.0× 92 1.6k
Hua Xia Australia 24 472 0.5× 531 1.6× 124 0.4× 24 0.1× 220 0.8× 87 1.9k
P. Tabeling France 34 331 0.3× 1.6k 4.8× 321 1.0× 98 0.4× 372 1.4× 73 3.4k
S. Großmann Germany 29 822 0.8× 452 1.4× 200 0.6× 121 0.4× 57 0.2× 109 3.0k
J. Maurer United States 18 280 0.3× 397 1.2× 156 0.5× 57 0.2× 163 0.6× 46 1.3k

Countries citing papers authored by Freddy Bouchet

Since Specialization
Citations

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

Fields of papers citing papers by Freddy Bouchet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Freddy Bouchet

This figure shows the co-authorship network connecting the top 25 collaborators of Freddy Bouchet. A scholar is included among the top collaborators of Freddy Bouchet 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 Freddy Bouchet. Freddy Bouchet is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Herbert, Corentin, et al.. (2025). Gaussian Framework and Optimal Projection of Weather Fields for Prediction of Extreme Events. Journal of Advances in Modeling Earth Systems. 17(6). 1 indexed citations
2.
D’Andrea, Fabio, et al.. (2025). Comparing the influence of Atlantic Multidecadal Variability and spring soil moisture on European summer heat waves. SPIRE - Sciences Po Institutional REpository. 5(1). 1 indexed citations
3.
Yiou, Pascal, et al.. (2024). Extreme heat wave sampling and prediction with analog Markov chain and comparisons with deep learning. SHILAP Revista de lepidopterología. 3. 3 indexed citations
4.
Monteiro, Joy Merwin, et al.. (2024). Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia. SHILAP Revista de lepidopterología. 3(4). 45016–45016. 3 indexed citations
5.
Herbert, Corentin, et al.. (2024). Assessing the probability of extremely low wind energy production in Europe at sub-seasonal to seasonal time scales. Environmental Research Letters. 19(4). 44046–44046.
6.
Ragone, Francesco, et al.. (2023). Robust intra-model teleconnection patterns for extreme heatwaves. Frontiers in Earth Science. 11. 5 indexed citations
7.
Abry, Patrice, et al.. (2023). Probabilistic forecasts of extreme heatwaves using convolutional neural networks in a regime of lack of data. Physical Review Fluids. 8(4). 25 indexed citations
8.
Bouchet, Freddy, Roger Tribe, & Oleg Zaboronski. (2023). Sample-path large deviations for stochastic evolutions driven by the square of a Gaussian process. Physical review. E. 107(3). 34111–34111. 3 indexed citations
9.
Westen, René M. van, et al.. (2023). Data-driven methods to estimate the committor function in conceptual ocean models. Nonlinear processes in geophysics. 30(2). 195–216. 9 indexed citations
10.
Herbert, Corentin, et al.. (2022). Coupling rare event algorithms with data-based learned committor functions using the analogue Markov chain. Journal of Statistical Mechanics Theory and Experiment. 2022(8). 83201–83201. 14 indexed citations
11.
Herbert, Corentin, et al.. (2022). Instantons and the Path to Intermittency in Turbulent Flows. Physical Review Letters. 129(3). 34502–34502. 12 indexed citations
12.
Ragone, Francesco & Freddy Bouchet. (2020). Rare event algorithm study of extreme warm summers and heatwaves over Europe. HAL (Le Centre pour la Communication Scientifique Directe). 7 indexed citations
13.
Queirós, Sı́lvio M. Duarte, Pedro G. Lind, Alain Girard, et al.. (2020). Small scale structures of turbulence in terms of entropy and fluctuation theorems. Physical Review Fluids. 5(3). 8 indexed citations
14.
Bouchet, Freddy, et al.. (2019). Rare-event sampling applied to the simulation of extreme mechanical eorts exerted by a turbulent ow on a blu body. HAL (Le Centre pour la Communication Scientifique Directe). 12 indexed citations
15.
Bouchet, Freddy, et al.. (2018). Barotropic theory for the velocity profile of Jupiter’s turbulent jets: an example for an exact turbulent closure. Journal of Fluid Mechanics. 860. 577–607. 6 indexed citations
16.
Nemoto, Takahiro, Freddy Bouchet, Robert L. Jack, & Vivien Lecomte. (2016). Population-dynamics method with a multicanonical feedback control. Physical review. E. 93(6). 62123–62123. 66 indexed citations
17.
Wouters, Jeroen & Freddy Bouchet. (2015). Rare event simulation of the chaotic Lorenz 96 dynamical system. EGUGA. 10421. 1 indexed citations
18.
Bouchet, Freddy, Fabio Cecconi, & Angelo Vulpiani. (2004). Minimal Stochastic Model for Fermi’s Acceleration. Physical Review Letters. 92(4). 40601–40601. 26 indexed citations
19.
Bouchet, Freddy. (2004). Stochastic process of equilibrium fluctuations of a system with long-range interactions. Physical Review E. 70(3). 36113–36113. 29 indexed citations
20.
Bouchet, Freddy, et al.. (2002). Out-of-Equilibrium States as Statistical Equilibria of an Effective Dynamics in a System with Long-Range Interactions. Physical Review Letters. 89(11). 110601–110601. 19 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.

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