Past

This is a review of hep-th/0912.4912

McBurnie: “Sound propagation through bubbly liquids”.

Hewett: "Switching on a time-harmonic acoustic source".

When the human eye looks at a distant object, the lens is held in a state of tension by a set of fibres (known as zonules) that connect the lens to the ciliary body. To view a nearby object, the ciliary muscle (which is part of the ciliary body) contracts. This reduces the tension in the zonules, the lens assumes a thicker and more rounded shape and the optical power of the eye increases.

This process is known as accommodation.

With increased age, however, the accommodation mechanism becomes increasingly ineffective so that, from an age of about 50 years onwards, it effectively ceases to function. This condition is known as presbyopia. There is considerable interest in the ophthalmic community on developing a better understanding of the ageing processes that cause presbyopia. As well as being an interesting scientific question in its own right, it is hoped that this improved understanding will lead to improved surgical procedures (e.g. to re-start the accommodation process in elderly cataract patients).

Let R be a number field (or a recursive subring of anumber field) and consider the polynomial ring R[T].

We show that the set of polynomials with integercoefficients is diophantine (existentially definable) over R[T].

Applying a result by Denef, this implies that everyrecursively enumerable subset of R[T]^k is diophantine over R[T].

Some years ago Hall and Smith in a number of papers developed a theory governing the interaction of vortices and waves in shear flows. In recent years immense interest has been focused on so-called self-sustained processes in turbulent shear flows where the importance of waves interacting with streamwise vortex flows has been elucidated in a number of; see for example the work of Waleffe and colleagues, Kerswell, Gibson, etc. These processes have a striking resemblance to coherent structures observed in turbulent shear flow and for that reason they are often referred to as exact coherent structures. It is shown that the structures associated with the so-called 'lower branch' state, which has been shown to play a crucial role in these self-sustained process, is nothing but a Rayleigh wave vortex interaction with a wave system generating streamwise vortices inside a critical layer. The theory enables the reduction of the 3D Navier Stokes equations to a coupled system for a steady streamwise vortex and an inviscid wave system. The reduced system for the streamwise vortices must be solved with jump conditions in the shear across the critical layer and the position of that layer constitutes a nonlinear pde eigenvalue problem. Remarkable agreement between the asymptotic theory and numerical simulations is found thereby demonstrating the importance of vortex-wave interaction theory in the mathematical description of coherent structures in turbulent shear flows. The theory offers the possibility of drag reduction in turbulent shear flows by controlling the flow to the neighborhood of the lower branch state. The relevance of the work to more general shear flows is also discussed.

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In the last few years, there has been renewed interest in stochastic

finite element methods (SFEMs), which facilitate the approximation

of statistics of solutions to PDEs with random data. SFEMs based on

sampling, such as stochastic collocation schemes, lead to decoupled

problems requiring only deterministic solvers. SFEMs based on

Galerkin approximation satisfy an optimality condition but require

the solution of a single linear system of equations that couples

deterministic and stochastic degrees of freedom. This is regarded as

a serious bottleneck in computations and the difficulty is even more

pronounced when we attempt to solve systems of PDEs with

random data via stochastic mixed FEMs.

In this talk, we give an overview of solution strategies for the

saddle-point systems that arise when the mixed form of the Darcy

flow problem, with correlated random coefficients, is discretised

via stochastic Galerkin and stochastic collocation techniques. For

the stochastic Galerkin approach, the systems are orders of

magnitude larger than those arising for deterministic problems. We

report on fast solvers and preconditioners based on multigrid, which

have proved successful for deterministic problems. In particular, we

examine their robustness with respect to the random diffusion

coefficients, which can be either a linear or non-linear function of

a finite set of random parameters with a prescribed probability

distribution.

After reviewing the salient details from last week's seminar, I will construct an explicit example of a spectral curve, using co-Higgs bundles of rank 2. The role of the spectral curve in understanding the moduli space will be made clear by appealing to the Hitchin fibration, and from there inferences (some of them very concrete) can be made about the structure of the moduli space. I will make some conjectures about the higher-dimensional picture, and also try to show how spectral varieties might live in that picture.

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I will describe some more of the deformation theory necessary for the first talk. This leads to a number of natural questions and counterexamples. This talk requires a strong stomach, or a fanatical devotion to symmetric obstruction theories.

In this talk we describe a general framework for deriving

modified equations for stochastic differential equations with respect to

weak convergence. We will start by quickly recapping of how to derive

modified equations in the case of ODEs and describe how these ideas can

be generalized in the case of SDEs. Results will be presented for first

order methods such as the Euler-Maruyama and the Milstein method. In the

case of linear SDEs, using the Gaussianity of the underlying solutions,

we will derive a SDE that the numerical method solves exactly in the

weak sense. Applications of modified equations in the numerical study

of Langevin equations and in the calculation of effective diffusivities

will also be discussed.

Canonical quantization of gravitational field will beconsidered. Examples for which the procedure can be completed (without reducingthe degrees of freedom) will be presented and discussed. The frameworks appliedwill be: Loop Quantum Gravity, relational construction of the Dirac observablesand deparametrization.

In the talk we discuss some results of [1]. We apply our previous methods [2] to geometry and to the mappings with bounded distortion.

\textbf{Theorem 1}.  Let $v:\Omega\to\mathbb{R}$ be a $C^1$-smooth function on a domain (open connected set) $\Omega\subset\mathbb{R}^2$. Suppose

$$ (1)\qquad \operatorname{Int} \nabla v(\Omega)=\emptyset. $$

Then $\operatorname{meas}\nabla v(\Omega)=0$.

Here $\operatorname{Int}E$ is the interior of ${E}$, $\operatorname{meas} E$ is the Lebesgue measure of ${E}$. Theorem 1 is a straight consequence of the following two results.

\textbf{ Theorem 2 [2]}.  Let $v:\Omega\to\mathbb{R}$ be a $C^1$-smooth function on a domain $\Omega\subset\mathbb{R}^2$. Suppose (1) is fulfilled. Then the graph of $v$ is a normal developing surface. 

Recall that a $C^1$-smooth manifold $S\subset\mathbb{R}^3$ is called  a normal developing surface [3] if for any $x_0\in S$ there exists a straight segment $I\subset S$ (the point $x_0$ is an interior point of $I$) such that the tangent plane to $S$ is stationary along $I$.

\textbf{Theorem 3}.  The spherical image of any $C^1$-smooth normal developing surface $S\subset\mathbb{R}^3$ has the area (the Lebesgue measure) zero.

Recall that the spherical image of a surface $S$ is the set $\{\mathbf{n}(x)\mid x\in S\}$, where $\mathbf{n}(x)$ is the unit normal vector to $S$ at the point~$x$. From Theorems 1--3 and the classical results of A.V. Pogorelov (see [4, Chapter 9]) we obtain the following corollaries Corollary 4. Let the spherical image of a $C^1$-smooth surface $S\subset\mathbb{R}^3$ have no interior points. Then this surface is a surface of zero extrinsic curvature in the sense of Pogorelov.

\textbf{ Corollary 5}. Any $C^1$-smooth normal developing surface $S\subset\mathbb{R}^3$ is a surface of zero extrinsic curvature in the sense of Pogorelov.

\textbf{Theorem 6}. Let $K\subset\mathbb{R}^{2\times 2}$ be a compact set and the topological dimension of $K$ equals 1. Suppose there exists $\lambda> 0$ such that $\forall A,B\in K, \, \, |A-B|^2\le\lambda\det(A-B).$

Then for any Lipschitz mapping $f:\Omega\to\mathbb R^2$ on a domain $\Omega\subset\mathbb R^2$ such that $\nabla f(x)\in K$ a.e. the identity $\nabla f\equiv\operatorname{const}$ holds.

Many partial cases of Theorem 6 (for instance, when $K=SO(2)$ or $K$ is a segment) are well-known (see, for example, [5]).

The author was supported by the Russian Foundation for Basic Research (project no. 08-01-00531-a).

[1] {Korobkov M.\,V.,} {``Properties of the $C^1$-smooth functions whose gradient range has topological dimension~1,'' Dokl. Math., to appear.}

[2] {Korobkov M.\,V.} {``Properties of the $C^1$-smooth functions with nowhere dense gradient range,'' Siberian Math. J., \textbf{48,} No.~6, 1019--1028 (2007).}

[3] { Shefel${}'$ S.\,Z.,} {``$C^1$-Smooth isometric imbeddings,'' Siberian Math. J., \textbf{15,} No.~6, 972--987 (1974).}

[4] {Pogorelov A.\,V.,} {Extrinsic geometry of convex surfaces, Translations of Mathematical Monographs. Vol. 35. Providence, R.I.: American Mathematical Society (AMS). VI (1973).}

[5] {M\"uller ~S.,} {Variational Models for Microstructure and Phase Transitions. Max-Planck-Institute for Mathematics in the Sciences. Leipzig (1998) (Lecture Notes, No.~2. http://www.mis.mpg.de/jump/publications.html).}

In this talk, we will focus on the asymptotic behavior in time of the solution of a model equation for Bose-Einstein condensation, in the case where the trapping potential varies randomly in time.

The model is the so called Gross-Pitaevskii equation, with a quadratic potential with white noise fluctuations in time whose amplitude tends to zero.

The initial condition is a standing wave solution of the unperturbed equation We prove that up to times of the order of the inverse squared amplitude the solution decomposes into the sum of a randomly modulatedmodulation parameters.

In addition, we show that the first order of the remainder, as the noise amplitude goes to zero, converges to a Gaussian process, whose expected mode amplitudes concentrate on the third eigenmode generated by the Hermite functions, on a certain time scale, as the frequency of the standing wave of the deterministic equation tends to its minimal value.