8,736 research outputs found
Polynomial Chaos Expansion of random coefficients and the solution of stochastic partial differential equations in the Tensor Train format
We apply the Tensor Train (TT) decomposition to construct the tensor product
Polynomial Chaos Expansion (PCE) of a random field, to solve the stochastic
elliptic diffusion PDE with the stochastic Galerkin discretization, and to
compute some quantities of interest (mean, variance, exceedance probabilities).
We assume that the random diffusion coefficient is given as a smooth
transformation of a Gaussian random field. In this case, the PCE is delivered
by a complicated formula, which lacks an analytic TT representation. To
construct its TT approximation numerically, we develop the new block TT cross
algorithm, a method that computes the whole TT decomposition from a few
evaluations of the PCE formula. The new method is conceptually similar to the
adaptive cross approximation in the TT format, but is more efficient when
several tensors must be stored in the same TT representation, which is the case
for the PCE. Besides, we demonstrate how to assemble the stochastic Galerkin
matrix and to compute the solution of the elliptic equation and its
post-processing, staying in the TT format.
We compare our technique with the traditional sparse polynomial chaos and the
Monte Carlo approaches. In the tensor product polynomial chaos, the polynomial
degree is bounded for each random variable independently. This provides higher
accuracy than the sparse polynomial set or the Monte Carlo method, but the
cardinality of the tensor product set grows exponentially with the number of
random variables. However, when the PCE coefficients are implicitly
approximated in the TT format, the computations with the full tensor product
polynomial set become possible. In the numerical experiments, we confirm that
the new methodology is competitive in a wide range of parameters, especially
where high accuracy and high polynomial degrees are required.Comment: This is a major revision of the manuscript arXiv:1406.2816 with
significantly extended numerical experiments. Some unused material is remove
The large core limit of spiral waves in excitable media: A numerical approach
We modify the freezing method introduced by Beyn & Thuemmler, 2004, for
analyzing rigidly rotating spiral waves in excitable media. The proposed method
is designed to stably determine the rotation frequency and the core radius of
rotating spirals, as well as the approximate shape of spiral waves in unbounded
domains. In particular, we introduce spiral wave boundary conditions based on
geometric approximations of spiral wave solutions by Archimedean spirals and by
involutes of circles. We further propose a simple implementation of boundary
conditions for the case when the inhibitor is non-diffusive, a case which had
previously caused spurious oscillations.
We then utilize the method to numerically analyze the large core limit. The
proposed method allows us to investigate the case close to criticality where
spiral waves acquire infinite core radius and zero rotation frequency, before
they begin to develop into retracting fingers. We confirm the linear scaling
regime of a drift bifurcation for the rotation frequency and the core radius of
spiral wave solutions close to criticality. This regime is unattainable with
conventional numerical methods.Comment: 32 pages, 17 figures, as accepted by SIAM Journal on Applied
Dynamical Systems on 20/03/1
Penta-hepta defect chaos in a model for rotating hexagonal convection
In a model for rotating non-Boussinesq convection with mean flow we identify
a regime of spatio-temporal chaos that is based on a hexagonal planform and is
sustained by the {\it induced nucleation} of dislocations by penta-hepta
defects. The probability distribution function for the number of defects
deviates substantially from the usually observed Poisson-type distribution. It
implies strong correlations between the defects inthe form of density-dependent
creation and annihilation rates of defects. We extract these rates from the
distribution function and also directly from the defect dynamics.Comment: 4 pages, 5 figures, submitted to PR
Scattering theory for lattice operators in dimension
This paper analyzes the scattering theory for periodic tight-binding
Hamiltonians perturbed by a finite range impurity. The classical energy
gradient flow is used to construct a conjugate (or dilation) operator to the
unperturbed Hamiltonian. For dimension the wave operator is given by
an explicit formula in terms of this dilation operator, the free resolvent and
the perturbation. From this formula the scattering and time delay operators can
be read off. Using the index theorem approach, a Levinson theorem is proved
which also holds in presence of embedded eigenvalues and threshold
singularities.Comment: Minor errors and misprints corrected; new result on absense of
embedded eigenvalues for potential scattering; to appear in RM
Spin-orbit coupling in curved graphene, fullerenes, nanotubes, and nanotube caps
A continuum model for the effective spin orbit interaction in graphene is
derived from a tight-binding model which includes the and bands.
We analyze the combined effects of the intra-atomic spin-orbit coupling,
curvature, and applied electric field, using perturbation theory. We recover
the effective spin-orbit Hamiltonian derived recently from group theoretical
arguments by Kane and Mele. We find, for flat graphene, that the intrinsic
spin-orbit coupling \Hi \propto \Delta^ 2 and the Rashba coupling due to a
perpendicular electric field , ,
where is the intra-atomic spin-orbit coupling constant for carbon.
Moreover we show that local curvature of the graphene sheet induces an extra
spin-orbit coupling term . For the values of
and curvature profile reported in actual samples of graphene, we find
that \Hi < \Delta_{\cal E} \lesssim \Delta_{\rm curv}. The effect of
spin-orbit coupling on derived materials of graphene, like fullerenes,
nanotubes, and nanotube caps, is also studied. For fullerenes, only \Hi is
important. Both for nanotubes and nanotube caps is in the
order of a few Kelvins. We reproduce the known appearance of a gap and
spin-splitting in the energy spectrum of nanotubes due to the spin-orbit
coupling. For nanotube caps, spin-orbit coupling causes spin-splitting of the
localized states at the cap, which could allow spin-dependent field-effect
emission.Comment: Final version. Published in Physical Review
Empirical macromodels under test: a comparative simulation study of the employment effects of a revenue neutral cut in social security contributions
In the paper we simulate a revenue-neutral cut in the social security contribution rate using five different types of macro- / microeconomic models, namely two models based on time-series data where the labour market is modelled basically demand oriented, two models of the class of computable equilibrium models which are supply oriented and finally a firm specific model for international tax burden comparisons. Our primary interest is in the employment effects the models predict due to the cut in the contribution rate. It turns out that qualitatively all models considered predict an increase in employment three years after the cut. But the employment effects differ considerably in magnitude, which follows immediately from the different behavioral assumptions underlying the different models. -- In dem Beitrag wird der BeschĂ€ftigungseffekt infolge einer aufkommensneutralen Senkung der SozialversicherungsbeitrĂ€ge simuliert. Zu diesem Zweck werden fĂŒnf unterschiedliche ökonomische Modelle verwendet, namentlich zwei Modelle, die auf Zeitreihendaten aufbauen und in denen der Arbeitsmarkt ĂŒberwiegend von der Nachfrageseite dominiert wird, zwei Modelle aus der Klasse der computable equilibrium models, die typischerweise angebotsorientiert sind, und ein mikroökonomisches, firmenspezifisches Steuerbelastungsvergleichsmodell. Alle Simulationsergebnisse der Modelle weisen auf einen, wenngleich teilweise kleinen, positiven BeschĂ€ftigungseffekt hin, der sich allerdings betrĂ€chtlich in seiner GröĂenordnung unterscheidet. Dies ist eine unmittelbare Folge aus den unterschiedlichen Verhaltensannahmen, die den einzelnen Modellen unterliegen.
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