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Seminars, Colloquia, and Conferences

Colloquium

The colloquium meets on Fridays at 4:00pm in Bromfield-Pearson 101, unless otherwise indicated.

Fall 2014

Date Speaker Title
September 15 Esther Kann
University of Linz, Industrial Mathematics Institute
A Weighted Wavelet Method for Region of Interest Tomography
September 19 James Propp
University of Massachusetts, Lowell
How well can you see the slope of a digital line (and other applications of the "tapering trick")?
September 26 Luis Dorfmann
Tufts University
Modeling of highly deformable materials
October 3 Laure Saint-Raymond
École Normale Supérieure, Paris
From molecular dynamics to kinetic theory and hydrodynamics
October 17 Pham Tiep
University of Arizona
Representations and subgroup structure of simple groups
October 24 Boris Hasselblatt
Tufts University
Statistical properties of deterministic systems by elementary means
October 31 Patricia Garmirian
Tufts University
A New and Direct Proof of the Central Limit Theorem
November 7 Sauro Succi
Istituto per le Applicazioni del Calcolo 'Mauro Picone'
Hydrokinetic approach to complex flows: the legacy of P.L. Bhatnagar
November 14 Margaret Beck Nonlinear stability of coherent structures via pointwise estimates
November 21 Andreas Arvanitoyeorgos
Tufts University
The dynamics of the normalized Ricci flow on some homogeneous spaces
December 5 Wenxiao Pan
Northwestern National Laboratory
Multiscale modeling using Lagrangian particle-based methods

Spring 2015

Date Speaker Title
January 23 Robert Krasny
University of Michigan
Title: Lagrangian Particle Methods for Vortex Dynamics
January 30 Sigurdur Helgason
Massachusetts Institute of Technology
TBA
February 6 Yanlai Chen
University of Massachusetts Dartmouth
Certified reduced basis methods and reduced collocation methods
February 27 Melanie Matchett Wood
University of Wisconsin, Madison
Random groups in number theory and random integral matrices
April 10 Stefan Witzel TBA
April 24 Todd Fisher
Brigham Young University
TBA

Abstracts

September 19, 2014
How well can you see the slope of a digital line (and other applications of the "tapering trick")?
James Propp, University of Massachusetts, Lowell

In many situations, we want to estimate some asymptotic quantity using data taken from a finite window. How can we best compensate for the error introduced by the finiteness of the window?

There is a simple general method for doing this that often gives markedly improved estimates, even though the method requires no information about the relationship between window-size and error. The method is called "tapering" in the signal-processing literature and "smoothing" in the number-theory literature, but outside of these two disciplines it does not seem to have gotten the attention it deserves.

I will discuss applications of tapering related to such topics as computational geometry, almost-periodic functions, lattice-point enumeration, number theory, quasicrystals, and derandomized Markov chains. No special background in any of these fields (or indeed much of anything beyond calculus) is required, though a rudimentary knowledge of Fourier analysis will be helpful for those who want to understand when and why tapering works.

September 26, 2014
Modeling of highly deformable materials
Luis Dorfmann, Tufts University

The seminar starts by reviewing experimental data to illustrate the large deformation stress-strain response of nonlinear elastic materials. This is followed by a summary of the main ingredients of the nonlinear theory of elasticity and of suitable strain-energy functions to describe the isotropic and anisotropic responses of highly deformable materials. The second part of the seminar focuses on the coupling of mechanical and magnetic effects and on the development of constitutive equations for magnetoelastic materials. These smart materials typically consist of an elastomeric matrix and a distribution of nanoscale ferromagnetic particles and have the capability to change their mechanical properties by the application of a magnetic field. We summarize the relevant equations and propose a coupled free-energy formulation, which depends on the deformation gradient and on the magnetic induction. Finally, we discuss how constitutive equations are specialized to isotropic incompressible magneto-sensitive elastomers in either Lagrangian or Eulerian forms.

October 3, 2014
From molecular dynamics to kinetic theory and hydrodynamics
Laure Saint-Raymond, École Normale Supérieure, Paris

A gas can be considered either as a large system of microscopic interacting particles, or as a continuous medium governed by fluid equations. A natural question is therefore to understand whether both kinds of models give consistent predictions of the dynamics.

In this lecture, we will focus on the validity of the fluid approximation in the particular case of rarefied gases, using kinetic theory as an intermediate level of description as suggested by Hilbert in his sixth problem. We will present landmark partial results, both on the low density limit and on the Navier-Stokes limit of the Boltzmann equation, giving an hint of the mathematical tools used to establish these convergences, and discussing the challenging open questions.

October 17, 2014
Representations and subgroup structure of simple groups
Pham Tiep, University of Arizona

What can one say about maximal subgroups, or, more generally, subgroup structure of simple, finite or algebraic, groups? In this talk we will discuss how group representation theory helps us study this classical problem. We will also describe applications of these results to various problems, particularly in number theory and algebraic geometry.

October 24, 2014
Statistical properties of deterministic systems by elementary means
Boris Hasselblatt, Tufts University

The Maxwell-Boltzmann ergodic hypothesis aimed to lay a foundation under statistical mechanics, which is at a microscopic scale a deterministic system. Similar complexity was discovered by Poincaré in celestial mechanics and by Hadamard in the motion of a free particle in a negatively curved space. We start with a guided tour of the history of the subject from various perspectives and then discuss the central mechanism that produces pseudorandom behavior in these deterministic systems, the Hopf argument. It has been known to extend well beyond the scope of its initial application in 1939, and we show that it also leads to much stronger conclusions: Not only do time averages of observables coincide with space averages (which was the purpose for making the ergodic hypothesis), but any finite number of observables will become decorrelated with time. That is, the Hopf argument does not only yield ergodicity but mixing, and often mixing of all orders.

October 31, 2014
A New and Direct Proof of the Central Limit Theorem
Patricia Garmirian, Tufts University

The Central Limit Theorem (CLT) is one of the most fundamental theorems in probability theory. The CLT states that a sequence of appropriately scaled sums of i.i.d. random variables converges weakly to the standard normal distribution. Although mathematicians had worked on the CLT as early as the 1600s, William Feller gave a proof of the CLT in 1935 by employing L\'evy's continuity theorem. L\'evy's continuity theorem, a nontrivial result, establishes the equivalence of weak convergence for a sequence of random variables and the convergence of the characteristic functions for those random variables. In this talk, I will present the main ideas of our direct proof of the CLT which does not employ L\'evy's continuity theorem. In our proof, we transform a random variable into an i.i.d. sequence on [0,1] and then expand this sequence with respect to the Haar wavelet basis.

The theorem of Skorokhod can be applied to the CLT to establish the existence of a sequence of random variables converging almost surely to the standard normal distribution. In this talk, I will also discuss our present research in which we apply Skorokhod's theorem to a sequence of appropriately scaled sums of i.i.d. random variables.

November 7, 2014
Hydrokinetic approach to complex flows: the legacy of P.L. Bhatnagar
Sauro Succi

Kinetic theory was originally devised by Ludwig Boltzmann to deal with rarefied gas dynamics. However, in the last decades it has become increasingly apparent that kinetic theory provides a very powerful and general mathematical framework for studying the dynamic evolution of a broad class of complex systems at large. Instrumental to this success, is the development of model Boltzmann equations capable of relinquishing most mathematical complexities without surrendering the essential physics. In this talk we shall discuss the special role played by lattice versions of the Bhatnagar-Gross-Krook model equation to model a variety of complex flows, ranging from fluid turbulence to quark-gluon plasmas.

November 14, 2014
Nonlinear stability of coherent structures via pointwise estimates
Margaret Beck

Coherent structures, for example traveling waves and periodic patterns, play a key role in determining the behavior of certain types of PDEs, such as reaction diffusion equations and viscous conservation laws. In particular, if they are stable, then they attract nearby initial data and thus qualitatively govern the local dynamics for large times. Determining the stability of coherent structures is often complicated by the presence of continuous spectrum for the associated linearized operator, as well as by details of the nonlinear terms in the PDE. In this talk, I will explain such difficulties in the context of patterns known as defects, and explain how they can be overcome using so-called pointwise estimates for the associated Green's function.

December 5, 2014
Multiscale modeling using Lagrangian particle-based methods
Wenxiao Pan

Lagrangian particle-based methods have advantages for modeling physical phenomena involving multiphase flows, flows with free surfaces, advection-dominated flows, complex fluids, large-deformation of materials and soft matters. In this talk, I will discuss several particle-based methods including smoothed particle hydrodynamics, smoothed dissipative particle dynamics and dissipative particle dynamics. Their various applications in macroscale and mesoscale multiphysical modeling will be demonstrated.

January 23, 2015
Lagrangian Particle Methods for Vortex Dynamics
Robert Krasny

This talk will describe how Lagrangian particle methods are being used to study the dynamics of fluid vortices. These methods track the flow map using adaptive particle discretizations. The Biot-Savart integral is used to recover the velocity from the vorticity, and a tree code is used to reduce the computation time from $O(N^2)$ to $O(N\log N)$, where $N$ is the number of particles. I'll present computations of vortex sheet motion in 2D flow with reference to Kelvin-Helmholtz instability, the Moore singularity, spiral roll-up, and chaotic dynamics. Other examples include vortex rings in 3D flow, and vortex dynamics on a rotating sphere.

February 6, 2015
Certified reduced basis methods and reduced collocation methods
Yanlai Chen

Models of reduced computational complexity is indispensable in scenarios where a large number of numerical solutions to a parametrized partial differential equation are desired in a fast/real-time fashion. These include simulation-based design, parameter optimization, optimal control, multi-model/scale analysis, uncertainty quantification etc. Thanks to an offline-online procedure and the recognition that the parameter-induced solution manifolds can be well approximated by finite-dimensional spaces, reduced basis method (RBM) and reduced collocation method (RCM) can improve efficiency by several orders of magnitudes. The accuracy of the RB/RC solution is maintained through a rigorous a posteriori error estimator whose efficient development is critical.

In this talk, I will give a brief introduction of the RBM and discuss recent and ongoing efforts to develop RCM, and the accompanying parametric analytical preconditioning techniques which are capable of improving the quality of the error estimation uniformly on the parameter domain, and speeding up the convergence of the reduced solution to the truth approximation significantly. New ways of effectively bounding the stability constants for the error estimation will also be discussed. These results are critical in certifying the accuracy of the reduced model and giving it a reliable predictive value.

February 27, 2015
Random groups in number theory and random integral matrices
Melanie Matchett Wood

There are certain finite abelian groups that arise from objects in number theory that are quite mysterious and of great interest, for example the class group arising from a finite extension of the rational numbers, or the Tate-Shafarevich group of an elliptic curve y^2=x^3+ax+b (for some rational numbers a,b). We discuss the question of what a class group of a random extension, or the Tate-Shafarevich group of a random elliptic curve, looks like, and explain heuristics of several authors including Cohen and Lenstra, and Delaunay, for how these random groups behave. Finally we will relate the predictions of these heuristics to phenomena that can be seen and proven about random integral matrices.

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