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Rarefaction waves in nonlocal convection-diffusion equations

Anna Pudełko (2014)

Colloquium Mathematicae

We consider a nonlocal convection-diffusion equation u t = J * u - u - u u x , where J is a probability density. We supplement this equation with step-like initial conditions and prove the convergence of the corresponding solutions towards a rarefaction wave, i.e. a unique entropy solution of the Riemann problem for the inviscid Burgers equation.

Recent progress in attractors for quintic wave equations

Anton Savostianov, Sergey Zelik (2014)

Mathematica Bohemica

We report on new results concerning the global well-posedness, dissipativity and attractors for the quintic wave equations in bounded domains of 3 with damping terms of the form ( - Δ x ) θ t u , where θ = 0 or θ = 1 / 2 . The main ingredient of the work is the hidden extra regularity of solutions that does not follow from energy estimates. Due to the extra regularity of solutions existence of a smooth attractor then follows from the smoothing property when θ = 1 / 2 . For θ = 0 existence of smooth attractors is more complicated and follows...

Recent results on stationary critical Kirchhoff systems in closed manifolds

Emmanuel Hebey, Pierre-Damien Thizy (2013/2014)

Séminaire Laurent Schwartz — EDP et applications

We report on results we recently obtained in Hebey and Thizy [11, 12] for critical stationary Kirchhoff systems in closed manifolds. Let ( M n , g ) be a closed n -manifold, n 3 . The critical Kirchhoff systems we consider are written as a + b j = 1 p M | u j | 2 d v g Δ g u i + j = 1 p A i j u j = U 2 - 2 u i for all i = 1 , , p , where Δ g is the Laplace-Beltrami operator, A is a C 1 -map from M into the space M s p ( ) of symmetric p × p matrices with real entries, the A i j ’s are the components of A , U = ( u 1 , , u p ) , | U | : M is the Euclidean norm of U , 2 = 2 n n - 2 is the critical Sobolev exponent, and we require that u i 0 in M for all i = 1 , , p . We...

Reconstruction of map projection, its inverse and re-projection

Tomáš Bayer, Milada Kočandrlová (2018)

Applications of Mathematics

This paper focuses on the automatic recognition of map projection, its inverse and re-projection. Our analysis leads to the unconstrained optimization solved by the hybrid BFGS nonlinear least squares technique. The objective function is represented by the squared sum of the residuals. For the map re-projection the partial differential equations of the inverse transformation are derived. They can be applied to any map projection. Illustrative examples of the stereographic and globular Nicolosi projections...

Recovering quantum graphs from their Bloch spectrum

Ralf Rueckriemen (2013)

Annales de l’institut Fourier

We define the Bloch spectrum of a quantum graph to be the map that assigns to each element in the deRham cohomology the spectrum of an associated magnetic Schrödinger operator. We show that the Bloch spectrum determines the Albanese torus, the block structure and the planarity of the graph. It determines a geometric dual of a planar graph. This enables us to show that the Bloch spectrum indentifies and completely determines planar 3 -connected quantum graphs.

Recovering the total singularity of a conormal potential from backscattering data

Mark S. Joshi (1998)

Annales de l'institut Fourier

The problem of recovering the singularities of a potential from backscattering data is studied. Let Ω be a smooth precompact domain in n which is convex (or normally accessible). Suppose V i = v + w i with v C c ( n ) and w i conormal to the boundary of Ω and supported inside Ω then if the backscattering data of V 1 and V 2 are equal up to smoothing, we show that w 1 - w 2 is smooth.

Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems

Philippe Moireau, Dominique Chapelle (2011)

ESAIM: Control, Optimisation and Calculus of Variations

We propose a general reduced-order filtering strategy adapted to Unscented Kalman Filtering for any choice of sampling points distribution. This provides tractable filtering algorithms which can be used with large-dimensional systems when the uncertainty space is of reduced size, and these algorithms only invoke the original dynamical and observation operators, namely, they do not require tangent operator computations, which of course is of considerable benefit when nonlinear operators are considered....

Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems

Philippe Moireau, Dominique Chapelle (2011)

ESAIM: Control, Optimisation and Calculus of Variations

We propose a general reduced-order filtering strategy adapted to Unscented Kalman Filtering for any choice of sampling points distribution. This provides tractable filtering algorithms which can be used with large-dimensional systems when the uncertainty space is of reduced size, and these algorithms only invoke the original dynamical and observation operators, namely, they do not require tangent operator computations, which of course is of considerable benefit when nonlinear operators are considered....

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