Past

In this talk we present a new type of Soblev norm defined in the space of functions of continuous paths. Under the Wiener probability measure the corresponding norm is suitable to prove the existence and uniqueness for a large type of system of path dependent quasi-linear parabolic partial differential equations (PPDE). We have establish 1-1 correspondence between this new type of PPDE and the classical backward SDE (BSDE). For fully nonlinear PPDEs, the corresponding Sobolev norm is under a sublinear expectation called G-expectation, in the place of Wiener expectation. The canonical process becomes a new type of nonlinear Brownian motion called G-Brownian motion. A similar 1-1 correspondence has been established. We can then apply the recent results of existence, uniqueness and principle of comparison for BSDE driven by G-Brownian motion to obtain the same result for the PPDE.

Let $K\subset {\mathbb R}$ be a compact definable set in an o-minimal structure over $\mathbb R$, e.g. a semi-algebraic or a real analytic set. A definable family $\{S_\delta\ |  0<\delta\in{\mathbb R}\}$ of compact subsets of $K$, is called a monotone family if $S_\delta\subset S_\eta$ for all sufficiently small $\delta>\eta>0$. The main result in the talk is that when $\dim K=2$ or $\dim K=n=3$ there exists a definable triangulation of $K$ such that for each (open) simplex $\Lambda$ of the triangulation and each small enough $\delta>0$, the intersections $S_\delta\cap\Lambda$ is equivalent to one of five (respectively, nine) standard families in the standard simplex (the equivalence relation and a standard family will be formally defined). As a consequence, we prove the two-dimensional case of the topological conjecture on approximation of definable sets by compact families.

This is joint work with Andrei Gabrielov (Purdue).

The moduli space of G-Higgs bundles carries a natural Hyperkahler structure, through which we can study Lagrangian subspaces (A-branes) or holomorphic subspaces (B-branes) with respect to each structure. Notably, these A and B-branes have gained significant attention in string theory.

We shall begin the talk by first introducing G-Higgs bundles for reductive Lie groups and the associated Hitchin fibration, and sketching how to realize Langlands duality through spectral data. We shall then look at particular types of branes (BAA-branes) which correspond to very interesting geometric objects, hyperholomorphic bundles (BBB-branes). 

The presentation will be introductory and my goal is simply to sketch some of the ideas relating these very interesting areas. 

In 1989, Selberg defined what came to be known as the "Selberg class" of $L$-functions, giving rise to a new subfield of analytic number theory in the intervening quarter century. Despite its popularity, a few things have always bugged me about the definition of the Selberg class. I will discuss these nitpicks and describe some modest attempts at overcoming them, with new applications.

New simple methods of simulating multivariate diffusion bridges, approximately and exactly, are presented. Diffusion bridge simulation plays a fundamental role in simulation-based likelihood inference for stochastic differential equations. By a novel application of classical coupling methods, the new approach generalizes the one-dimensional bridge-simulation method proposed by Bladt and Sørensen (2014) to the multivariate setting. A method of simulating approximate, but often very accurate, diffusion bridges is proposed. These approximate bridges are used as proposal for easily implementable MCMC algorithms that produce exact diffusion bridges. The new method is more generally applicable than previous methods because it does not require the existence of a Lamperti transformation, which rarely exists for multivariate diffusions. Another advantage is that the new method works well for diffusion bridges in long intervals because the computational complexity of the method is linear in the length of the interval. The usefulness of the new method is illustrated by an application to Bayesian estimation for the multivariate hyperbolic diffusion model.

The lecture is based on joint work presented in Bladt, Finch and Sørensen (2014).References:

Bladt, M. and Sørensen, M. (2014): Simple simulation of diffusion bridges with application to likelihood inference for diffusions. Bernoulli, 20, 645-675.

Bladt, M., Finch, S. and Sørensen, M. (2014): Simulation of multivariate diffusion bridges. arXiv:1405.7728, pp. 1-30.

Particle-based stochastic reaction diffusion methods have become a 
popular approach for studying the behavior of cellular processes in 
which both spatial transport and noise in the chemical reaction process 
can be important. While the corresponding deterministic, mean-field 
models given by reaction-diffusion PDEs are well-established, there are 
a plethora of different stochastic models that have been used to study 
biological systems, along with a wide variety of proposed numerical 
solution methods.

In this talk I will motivate our interest in such methods by first 
summarizing several applications we have studied, focusing on how the 
complicated ultrastructure within cells, as reconstructed from X-ray CT 
images, might influence the dynamics of cellular processes. I will then 
introduce our attempt to rectify the major drawback to one of the most 
popular particle-based stochastic reaction-diffusion models, the lattice 
reaction-diffusion master equation (RDME). We propose a modified version 
of the RDME that converges in the continuum limit that the lattice 
spacing approaches zero to an appropriate spatially-continuous model. 
Time-permitting, I will discuss several questions related to calibrating 
parameters in the underlying spatially-continuous model.

Some problems in scientific computing, like the forward simulation of electromagnetic waves in geophysical prospecting, can be
solved via approximation of f(A)b, the action of a large matrix function f(A) onto a vector b. Iterative methods based on rational Krylov
spaces are powerful tools for these computations, and the choice of parameters in these methods is an active area of research.
We provide an overview of different approaches for obtaining optimal parameters, with an emphasis on the exponential and resolvent function, and the square root. We will discuss applications of the rational Arnoldi method for iteratively generating near-optimal absorbing boundary layers for indefinite Helmholtz problems, and for rational least squares vector fitting.

We consider the layer potentials associated with operators $L=-\mathrm{div}A \nabla$ acting in the upper half-space $\mathbb{R}^{n+1}_+$, $n\geq 2$, where the coefficient matrix $A$ is complex, elliptic, bounded, measurable, and $t$-independent. A "Calder\'{o}n--Zygmund" theory is developed for the boundedness of the layer potentials under the assumption that solutions of the equation $Lu=0$ satisfy interior De Giorgi-Nash-Moser type estimates. In particular, we prove that $L^2$ estimates for the layer potentials imply sharp $L^p$ and endpoint space estimates. The method of layer potentials is then used to obtain solvability of boundary value problems. This is joint work with Steve Hofmann and Marius Mitrea.

This talk will give an almost complete proof of the h-cobordism theorem, paying special attention to the sources of the dimensional restrictions in the theorem. If time allows, the alterations needed to prove its cousin, the s-cobordism theorem, will also be sketched.

Manifolds have been a central object of study for over a century, and the classification of them has been a core theme for the whole of this time. This talk will give an overview of the successes and failures in this effort, with some illustrative examples.

D-finite functions are solutions of linear differential equations with polynomial coefficients.  They have drawn a lot of attention, both in Computer Algebra--because of their numerous (algorithmic) closure properties--but also in Numerical Analysis, because their defining ODEs can be numerically solved very efficiently.  In this talk, I will show how a mix of symbolic and numerical methods yields fast and well-conditioned spectral methods on various domains and using different bases of functions.

The Number Field Sieve is the current practical and theoretical state of the art algorithm for factoring. Unfortunately, there has been no rigorous analysis of this type of algorithm. We randomise key aspects of the number theory, and prove that in this variant congruences of squares are formed in expected time $L(1/3, 2.88)$. These results are tightly coupled to recent progress on the distribution of smooth numbers, and we provide additional tools to turn progress on these problems into improved bounds.

It is well-known that a matrix $A$ is Hurwitz stable if and only if there exists a positive definite solution to the Lyapunov matrix equation $A X + X A^* = B$, where $B$ is Hermitian negative definite. We present a verified numerical algorithm to rigorously prove the stability of a given matrix $A$ in the presence of rounding errors.  The computational cost of the algorithm is cubic and it is fast since we can cast almost all operations in level 3 BLAS for which interval arithmetic can be implemented very efficiently.  This is a joint work with Andreas Frommer and the results are already published in ETNA in 2013.

1)      The Hardt-Lin's problem and a new approximation of a relaxed energy for harmonic maps.

We introduce a new approximation for  the relaxed energy $F$ of the Dirichlet energy and prove that the minimizers of the approximating functional converge to a minimizer $u$ of the relaxed energy for harmonic maps, and that $u$ is  partially regular without using the concept of Cartesian currents.

2)  Partial regularity in liquid crystals  for  the Oseen-Frank model:  a new proof of the result of Hardt, Kinderlehrer and Lin.

Hardt, Kinderlehrer and Lin (\cite {HKL1}, \cite {HKL2}) proved that a minimizer $u$ is smooth on some open subset
$\Omega_0\subset\Omega$ and moreover $\mathcal H^{\b} (\Omega\backslash \Omega_0)=0$ for some positive $\b <1$, where
$\mathcal H^{\b}$ is the Hausdorff measure.   We will present a new proof of Hardt, Kinderlehrer and Lin.

 3)      Global existence of solutions of the Ericksen-Leslie system for  the Oseen-Frank model.

The dynamic flow of liquid crystals is described by the Ericksen-Leslie system. The Ericksen-Leslie system is a system of  the Navier-Stokes equations coupled with the gradient flow for the Oseen-Frank model,   which generalizes the heat flow for harmonic maps  into the $2$-sphere.   In this talk, we will outline a proof of global existence of solutions of the Ericksen-Leslie system for a general Oseen-Frank  model in 2D.

In this talk, we consider two disparate questions involving wave equations: (1) how singularities of solutions of subconformal focusing nonlinear wave equations form, and (2) when solutions of (linear and nonlinear) wave equations are determined by their data at infinity. In particular, we will show how tools from solving the second problem - a new family of global nonlinear Carleman estimates - can be used to establish some new results regarding the first question. Previous theorems by Merle and Zaag have established both upper and lower bounds on the local H¹-norm near noncharacteristic blow-up points for subconformal focusing NLW. In our main result, we show that this H¹-norm cannot concentrate along past timelike cones emanating from the blow-up point, i.e., that a significant amount of the action must occur near the corresponding past null cones.

These are joint works with Spyros Alexakis.

The  study of closed geodesics on a Riemannian manifold is a classical and important part of differential geometry. In 1969 Gromoll and Meyer used Morse - Bott theory to give a topological condition on the loop space of compact manifold M which ensures that any Riemannian metric on M has an infinite number of closed geodesics.  This makes a very close connection between closed geodesics and the topology of loop spaces.  

Nowadays it is known that there is a rich algebraic structure associated to the topology of loop spaces — this is the theory of string homology initiated by Chas and Sullivan in 1999.  In recent work, in collaboration with John McCleary, we have used the ideas of string homology to give new results on the existence of an infinite number of closed  geodesics. I will explain some of the key ideas in our approach to what has come to be known as the closed geodesics problem.

Spectral volume and surface measures via the Dixmier trace for local symmetric Dirichlet spaces with Weyl type eigenvalue asymptotics

The purpose of this talk is to present the author's recent results of on an

operator theoretic way of looking atWeyl type Laplacian eigenvalue asymptotics

for local symmetric Dirichlet spaces.

For the Laplacian on a d-dimensional Riemannian manifoldM, Connes' trace

theorem implies that the linear functional  coincides with

(a constant multiple of) the integral with respect to the Riemannian volume

measure of M, which could be considered as an operator theoretic paraphrase

of Weyl's Laplacian eigenvalue asymptotics. Here  denotes a Dixmier trace,

which is a trace functional de_ned on a certain ideal of compact operators on

a Hilbert space and is meaningful e.g. for compact non-negative self-adjoint

operators whose n-th largest eigenvalue is comparable to 1/n.

The first main result of this talk is an extension of this fact in the framework

of a general regular symmetric Dirichlet space satisfying Weyl type asymptotics

for the trace of its associated heat semigroup, which was proved for Laplacians

on p.-c.f. self-simiar sets by Kigami and Lapidus in 2001 under a rather strong

assumption.

Moreover, as the second main result of this talk it is also shown that, given a

local regular symmetric Dirichlet space with a sub-Gaussian heat kernel upper

bound and a (sufficiently regular) closed subset S, a “spectral surface measure"

on S can be obtained through a similar linear functional involving the Lapla-

cian with Dirichlet boundary condition on S. In principle, corresponds to the

second order term for the eigenvalue asymptotics of this Dirichlet Laplacian, and

when the second order term is explicitly known it is possible to identify  For

example, in the case of the usual Laplacian on Rd and a Lipschitz hypersurface S,is a constant multiple of the usual surface measure on S.

Maximal couplings are couplings of Markov processes where the tail probabilities of the coupling time attain the total variation lower bound (Aldous bound) uniformly for all time. Markovian couplings are coupling strategies where neither process is allowed to look into the future of the other before making the next transition. These are easier to describe and play a fundamental role in many branches of probability and analysis. Hsu and Sturm proved that the reflection coupling of Brownian motion is the unique Markovian maximal coupling (MMC) of Brownian motions starting from two different points. Later, Kuwada proved that to have a MMC for Brownian motions on a Riemannian manifold, the manifold should have a reflection structure, and thus proved the first result connecting this purely probabilistic phenomenon (MMC) to the geometry of the underlying space.

Kodaira dimension provides a very successful classification scheme for complex manifolds. The notion was extended to symplectic 4-manifolds. In this talk, we will define the Kodaira dimension for 3-manifolds through Thurston’s eight geometries. This is compatible with other Kodaira dimensions in the sense of “additivity”. This idea could be extended to dimension 4. Finally, we will see how it is sitting in a potential classification of 4-manifolds by exploring its relations with various Kodaira dimensions and other invariants like Gromov norm.

The chiral scalar superfield has interesting BRST cohomology, but the relevant cohomology objects all  have spinor indices. So they cannot occur in an action. They need to be coupled to a chiral dotted spinor superfield. Until now, this has been very problematic, since no sensible action for a chiral dotted spinor superfield was known.  The most obvious such action contains higher derivatives and tachyons.

Now,  a sensible  action has been found. When coupled to the cohomology, this action removes the supersymmetry charge from the theory while maintaining the rigidity and power of supersymmetry.The simplest example of this phenomenon has exactly the fermion content of the Leptons or the Quarks.  The mechanism has the potential to get around the cosmological constant problem, and also the problem of the sum rules of spontaneously broken supersymmetry.

One of the main obstacles to forecasting sea level rise over the coming centuries is the problem of predicting changes in the flow of ice sheets, and in particular their fast-flowing outlet glaciers. While numerical models of ice sheet flow exist, they are often hampered by a lack of input data, particularly concerning the bedrock topography beneath the ice. Measurements of this topography are relatively scarce, expensive to obtain, and often error-prone. In contrast, observations of surface elevations and velocities are widespread and accurate.

In an ideal world, we could combine surface observations with our understanding of ice flow to invert for the bed topography. However, this problem is ill-posed, and solutions are both unstable and non-unique. Conventionally, this problem is circumvented by the use of regularization terms in the inversion, but these are often arbitrary and the numerical methods are still somewhat unstable.

One philosophically appealing option is to apply a fully Bayesian framework to the problem. Although some success has been had in this area, the resulting distributions are extremely difficult to work with, both from an interpretive standpoint and a numerical one. In particular, certain forms of prior information, such as constraints on the bedrock slope and roughness, are extremely difficult to represent in this framework.

A more profitable avenue for exploration is a semi-Bayesian approach, whereby a classical inverse method is regularized using terms derived from a Bayesian model of the problem. This allows for the inclusion of quite sophisticated forms of prior information, while retaining the tractability of the classical inverse problem. In particular, we can account for the severely non-Gaussian error distribution of many of our measurements, which was previously impossible.