Search results for "65L05"

showing 3 items of 3 documents

Stochastic Galerkin method for cloud simulation

2018

AbstractWe develop a stochastic Galerkin method for a coupled Navier-Stokes-cloud system that models dynamics of warm clouds. Our goal is to explicitly describe the evolution of uncertainties that arise due to unknown input data, such as model parameters and initial or boundary conditions. The developed stochastic Galerkin method combines the space-time approximation obtained by a suitable finite volume method with a spectral-type approximation based on the generalized polynomial chaos expansion in the stochastic space. The resulting numerical scheme yields a second-order accurate approximation in both space and time and exponential convergence in the stochastic space. Our numerical results…

010504 meteorology & atmospheric sciencesComputer scienceuncertainty quantificationQC1-999cloud dynamicsFOS: Physical sciencesCloud simulation65m15010103 numerical & computational mathematics01 natural sciencespattern formationMeteorology. ClimatologyFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsStochastic galerkin0105 earth and related environmental sciencesnavier-stokes equationsPhysics65m2565l05Numerical Analysis (math.NA)65m06Computational Physics (physics.comp-ph)stochastic galerkin method35l4535l65finite volume schemesQC851-999Physics - Computational Physicsimex time discretization
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Existence of dynamical low-rank approximations to parabolic problems

2021

The existence and uniqueness of weak solutions to dynamical low-rank evolution problems for parabolic partial differential equations in two spatial dimensions is shown, covering also non-diagonal diffusion in the elliptic part. The proof is based on a variational time-stepping scheme on the low-rank manifold. Moreover, this scheme is shown to be closely related to practical methods for computing such low-rank evolutions.

Algebra and Number TheoryPartial differential equationRank (linear algebra)Applied MathematicsNumerical Analysis (math.NA)010103 numerical & computational mathematics01 natural sciencesManifold010101 applied mathematics35K15 35R01 (Primary) 15A69 65L05 (Secondary)Computational MathematicsMathematics - Analysis of PDEsScheme (mathematics)FOS: MathematicsApplied mathematicsUniquenessMathematics - Numerical Analysisddc:5100101 mathematicsDiffusion (business)Analysis of PDEs (math.AP)Mathematics
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Efficient numerical integration of neutrino oscillations in matter

2016

A special purpose solver, based on the Magnus expansion, well suited for the integration of the linear three neutrino oscillations equations in matter is proposed. The computations are speeded up to two orders of magnitude with respect to a general numerical integrator, a fact that could smooth the way for massive numerical integration concomitant with experimental data analyses. Detailed illustrations about numerical procedure and computer time costs are provided.

Physics010308 nuclear & particles physicsComputationNumerical analysisFOS: Physical sciencesNumerical Analysis (math.NA)65L05 65L20Computational Physics (physics.comp-ph)Solver01 natural sciencesNumerical integrationHigh Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Classical mechanicsIntegratorMagnus expansion0103 physical sciencesFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis010306 general physicsNeutrino oscillationPhysics - Computational PhysicsNumerical stability
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