Zobrazeno 1 - 10
of 103
pro vyhledávání: '"Rainer Grauer"'
Publikováno v:
Journal of Physics: Complexity, Vol 4, Iss 1, p 015005 (2023)
We present a novel method for stochastic interpolation of sparsely sampled time signals based on a superstatistical random process generated from a multivariate Gaussian scale mixture. In comparison to other stochastic interpolation methods such as G
Externí odkaz:
https://doaj.org/article/30208537cebb4cf692c9c5817d9bdfa8
Autor:
Jan Friedrich, Rainer Grauer
Publikováno v:
Atmosphere, Vol 11, Iss 9, p 1003 (2020)
We present a generalized picture of intermittency in turbulence that is based on the theory of stochastic processes. To this end, we rely on the experimentally and numerically verified finding by R. Friedrich and J. Peinke [Phys. Rev. Lett. 78, 863 (
Externí odkaz:
https://doaj.org/article/68b511ae37984104a2be32058767b176
Autor:
Simon Lautenbach, Rainer Grauer
Publikováno v:
Frontiers in Physics, Vol 6 (2018)
Collisionless plasmas, mostly present in astrophysical and space environments, often require a kinetic treatment as given by the Vlasov equation. Unfortunately, the six-dimensional Vlasov equation can only be solved on very small parts of the conside
Externí odkaz:
https://doaj.org/article/1a4c22f940214011a31431fd0874bb03
The transport of cosmic rays in turbulent magnetic fields is commonly investigated by solving the Newton-Lorentz equation of test particles in synthetic turbulence fields. These fields are typically generated from superpositions of Fourier modes with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18aab76129c2e1aae31b7e8cd6d9b3cd
https://doi.org/10.5194/egusphere-egu23-14458
https://doi.org/10.5194/egusphere-egu23-14458
Publikováno v:
Journal of Statistical Physics. 190
Sharp large deviation estimates for stochastic differential equations with small noise, based on minimizing the Freidlin-Wentzell action functional under appropriate boundary conditions, can be obtained by integrating certain matrix Riccati different
We present a novel method for stochastic interpolation of sparsely sampled time signals based on a superstatistical random process generated from a multivariate Gaussian scale mixture. In comparison to other stochastic interpolation methods such as G
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86d9d9e247a9f349c71828e35105fda8
http://arxiv.org/abs/2208.01486
http://arxiv.org/abs/2208.01486
Publikováno v:
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 380
We investigate the spatio-temporal structure of the most likely configurations realizing extremely high vorticity or strain in the stochastically forced three-dimensional incompressible Navier–Stokes equations. Most likely configurations are comput
Autor:
Maria Elena Innocenti, Sophia Köhne, Simon Hornisch, Rainer Grauer, Jorge Amaya, Jimmy Raeder, Banafsheh Ferdousi, James \\'Andy\\' Edmond, Giovanni Lapenta
The large amount of data produced by measurements and simulations of space plasmas has made it fertile ground for the application of classification methods, that can support the scientist in preliminary data analysis. Among the different classificati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06f46d8a82d8f628abb092091f556914
https://doi.org/10.5194/egusphere-egu22-12480
https://doi.org/10.5194/egusphere-egu22-12480
Publikováno v:
Physics of Fluids. 34:096607
In this paper, we present a numerical approach to solve the Navier–Stokes equations for arbitrary vessel geometries by combining a Fourier-spectral method with a direct-forcing immersed boundary method, which one allows to consider solid–fluid in
In recent years, instanton calculus has successfully been employed to estimate tail probabilities of rare events in various stochastic dynamical systems. Without further corrections, however, these estimates can only capture the exponential scaling.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::561bb42c527155b6d76968fc7de35607
http://arxiv.org/abs/2103.04887
http://arxiv.org/abs/2103.04887