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Corentin Herbert

Researcher at École normale supérieure de Lyon

Publications -  45
Citations -  822

Corentin Herbert is an academic researcher from École normale supérieure de Lyon. The author has contributed to research in topics: Turbulence & Statistical mechanics. The author has an hindex of 15, co-authored 44 publications receiving 737 citations. Previous affiliations of Corentin Herbert include Weizmann Institute of Science & Centre national de la recherche scientifique.

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Mathematical and physical ideas for climate science

TL;DR: In this paper, the Nambu formulation of fluid dynamics and the potential of such a theory for constructing sophisticated numerical models of geophysical fluids are discussed. And the statistical mechanics of quasi-equilibrium flows in a rotating environment are investigated.
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Mathematical and Physical Ideas for Climate Science

TL;DR: In this paper, the Nambu formulation of fluid dynamics is used for constructing sophisticated numerical models of geophysical fluids, and the statistical mechanics of quasi-equilibrium flows in a rotating environment are discussed.
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Computing return times or return periods with rare event algorithms

TL;DR: In this article, an estimator for return times can be built from the extrema of the observable on trajectory blocks, which can be used to estimate return times of the order of the block size.
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Scaling laws for mixing and dissipation in unforced rotating stratified turbulence

TL;DR: In this article, a model for the scaling of mixing in weakly rotating stratified flows characterized by their Rossby, Froude and Reynolds numbers is presented, and smaller buoyancy fluxes together correspond to a decoupling of velocity and temperature fluctuations, the latter becoming passive.
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Turbulence Statistics in a Two-Dimensional Vortex Condensate.

TL;DR: It is shown that the turbulent energy is determined only by mean-flow advection and obtained for the first time a formula describing its profile in the vortex, supporting the first direct evidence supporting this prediction.