Institute for Mathematics and its Applications University of Minnesota 400 Lind Hall 207 Church Street SE Minneapolis, MN 55455 |

Web: http://www.ima.umn.edu |
Email: ima-staff@ima.umn.edu |
Telephone: (612) 624-6066 |
Fax: (612) 626-7370

This month's talks available at http://www.ima.umn.edu/newsletters

This month's talks available at http://www.ima.umn.edu/newsletters

2004-2005 Program

See http://www.ima.umn.edu/matter for a full description of the
2004-2005 program on

Mathematics of Materials and Macromolecules: Multiple Scales, Disorder, and Singularities

and http://www.ima.umn.edu/schedule for schedule updates.

News and Notes

The third IMA

The allied workshop *Career Options for Women in Mathematical Sciences*,
which took place February 4-5, provided more than seventy women mathematicians
with an opportunity to share experiences and insights.
Graduate student Yelda Aydin wrote “Getting to know these women who were very
successful and happy with their different choices made me feel more optimistic.”
Postdoc Suzanne Lynch Hruska elaborated “I
learned (to my pleasant surprise) that obtaining a job in
industry is very possible for an academic with a pure math
background. I left many of the talks feeling as though I could quite
happily be an employee in the speaker’s company in the future,” while
senior researcher Pam Binns found “the candor of the participants was exceptionally
impressive—providing insight into ‘real’ experiences—opposed
to the marketing pitches typically presented.” Graduate student
Paola Vera Licona captured the spirit of the meeting:
“One thing that I have learned from this workshop is that I
am capable of helping other women by sharing my experiences
and that I can learn so much from listening to others’
experiences. In fact, after the workshop I decided to enroll
in the AWM Mentor Network.”

IMA Events

Schedule

11:15a-12:10p | Bifurcation and stability of multilattices with applications to martensitic transformations in shape memory alloys | Ryan S. Elliott University of Michigan | Lind Hall 409 | PS |

11:15a-12:15p | Stable and finite Morse index solutions on bounded domains with small diffusion | Norman Dancer University of Sydney | Lind Hall 409 | MS |

11:15a-12:15p | Natural cost functions for contact point selection in grasping | Paul R Schrater University of Minnesota | Lind Hall 409 | MS |

11:15a-12:15p | Mathematical models for biaxial liquid crystals phases | Epifanio G. Virga Universita di Pavia | Lind Hall 409 | MS |

1:25p-2:25p | Medical image segmentation using deformable models | Chenyang Xu Siemens Corporate Research | Vincent Hall 570 | IPS |

11:15a-12:15p | Higher order corrections to the KdV approximation for water waves | Doug Wright University of Minnesota | Lind Hall 409 | PS |

2:30p-3:30p | Multiscale approaches to molecular dynamics and sampling | Jesus A. Izaguirre University of Notre Dame | Lind Hall 409 | MS |

11:15a-12:15p | Critical intensities for phase transitions in a 3D Smoluchowski equation | Hailiang Liu Iowa State University | Lind Hall 409 | MS |

2:30p-3:30p | Informal discussion of molecular dynamics | Jesus A. Izaguirre University of Notre Dame Brian Laird University of Kansas | Lind Hall 409 | MS |

12:25p-1:25p | Multiscale photon-limited image analysis | Rebecca Willett University of Minnesota | Lind Hall 409 | iPAWS |

2:30p-3:30p | Direct calculation of crystal-melt interfacial free energies from molecular simulation | Brian Laird University of Kansas | Lind Hall 409 | MS |

11:15a-12:15p | A variational model of dislocations in the line tension limit | Stefan Mueller Max Planck Institute for Math in the Sciences | Lind Hall 409 | MS |

11:15a-12:15p | TBA | Maria-Carme Calderer University of Minnesota | Lind Hall 409 | MS |

11:15a-12:15p | Stretching of polymers on sub-Kolmogorov scales in a turbulent flow | Joerg Schumacher Philipps University Marburg | Lind Hall 409 | MS |

12:25p-1:25p | Volumetric computed tomography and its applications | Xiaochuan Pan University of Chicago | Lind Hall 409 | iPAWS |

1:25p-2:25p | Solid modeling: Math at work in design | Jan Vandenbrande Boeing | Vincent Hall 570 | IPS |

8:30a-9:15a | Coffee and Registration | EE/CS 3-176 | T3.28-30.05 | |

9:15a-9:30a | Welcome and Introduction | Douglas N. Arnold University of Minnesota Robert V. Kohn New York University - Courant Institute | EE/CS 3-180 | T3.28-30.05 |

9:30a-10:30a | Lecture 1: Advances in advancing interfaces: Level set methods, fast marching methods, and beyond | James A. Sethian University of California | EE/CS 3-180 | T3.28-30.05 |

10:30a-11:00a | Coffee | EE/CS 3-176 | T3.28-30.05 | |

11:00a-12:00p | Lecture 1: Fast multipole methods and their applications | Leslie F. Greengard New York University | EE/CS 3-180 | T3.28-30.05 |

12:00p-1:30p | Lunch | T3.28-30.05 | ||

1:30p-2:30p | Lecture 1: Overview of multiscale methods | Weinan E Princeton University | EE/CS 3-180 | T3.28-30.05 |

2:30p-3:00p | Coffee | EE/CS 3-176 | T3.28-30.05 | |

3:00p-4:30p | Industrial problems presentations | EE/CS 3-180 | T3.28-30.05 |

8:45a-9:00a | Coffee | T3.28-30.05 | ||

9:30a-10:30a | More industrial problem presentations | EE/CS 3-180 | T3.28-30.05 | |

10:30a-11:00a | Coffee | EE/CS 3-176 | T3.28-30.05 | |

11:00a-12:00p | Lecture 2: Advances in advancing interfaces: Level set methods, fast marching methods, and beyond | James A. Sethian University of California | EE/CS 3-180 | T3.28-30.05 |

12:00p-1:30p | Lunch | T3.28-30.05 | ||

1:00p-2:30p | Lecture 2: Fast multipole methods and their applications | Leslie F. Greengard New York University | EE/CS 3-180 | T3.28-30.05 |

2:30p-3:00p | Coffee | EE/CS 3-176 | T3.28-30.05 | |

3:00p-4:00p | Group Photo | EE/CS 3-180 | T3.28-30.05 | |

3:00p-4:00p | Lecture 2: Problems with multiple time scales | Weinan E Princeton University | EE/CS 3-180 | T3.28-30.05 |

4:00p-5:30p | IMA Tea and more (with POSTER SESSION) 400 Lind Hall | Lind Hall 400 | T3.28-30.05 | |

A graph-theoretic method for the discretization of gene expression measurements | Elena Dimitrova Virginia Tech | |||

Phase field modeling and simulation of cell membranes | Qiang Du Pennsylvania State University | |||

High-dimensional finite elements for elliptic problems with multiple scales | Viet Ha Hoang Cambridge University | |||

Generalized Galerkin variational integrators: Lie group, multiscale and spectral methods | Melvin Leok University of Michigan |

8:50a-9:00a | Coffee | EE/CS 3-176 | T3.28-30.05 | |

9:00a-12:00p | Structured discussion of industrial problem areas | EE/CS 3-180 | T3.28-30.05 | |

12:00p-1:30p | Lunch | T3.28-30.05 | ||

1:30p-3:00p | Breakout sessions | EE/CS 3-180 | T3.28-30.05 | |

5:00p-6:30p | Reception for Thomas C. Hales | Lind Hall 400 | PUB3.30.05 | |

7:00p-8:00p | IMA Public Lecture: Computers and the Future of Mathematical Proof | Thomas C. Hales University of Pittsburgh | EE/CSci 3-210 | PUB3.30.05 |

12:25p-1:25p | Centroidal Voronoi tesselations and their applications | Qiang Du Pennsylvania State University | Lind Hall 409 | iPAWS |

Abstracts

Elena Dimitrova (Virginia Tech) | A graph-theoretic method for the discretization of gene expression measurements |

Abstract: The paper introduces a method for the discretization of experimental data into a finite number of states. While it is of interest in various fields, this method is particularly useful in bioinformatics for reverse engineering of gene regulatory networks built from gene expression data. Many of these applications require discrete data, but gene expression measurements are continuous. Statistical methods for discretization are not applicable due to the prohibitive cost of obtaining sample sets of sufficient size. We have developed a new method of discretizing the variables of a network into the same optimal number of states while at the same time maintaining high information content. We employ a graph-theoretic clustering method to affect the discretization of gene expression measurements. Our C++ program takes as an input one or more time series of gene expression data and discretizes these values into a number of states that best fits the data. The method is being validated by incorporating it into the recently published computational algebra approach to the reverse engineering of gene regulatory networks by Laubenbacher and Stigler. | |

Qiang Du (Pennsylvania State University) | Phase field modeling and simulation of cell membranes |

Abstract: Recently, we have produced a series of works on the phase field modeling and simulation of vesicle bio-membranes formed by lipid bilayers. We have considered both the shape deformation of vesicles minimizing the elastic bending energy with volume and surface area constraints and those moving in an incompressible viscous fluid. Rigorous mathematical analysis have been carried out along with extensive numerical experiments. We have also developed useful computational techniques for detecting the topological changes within a broad phase field framework. References: 1. A Phase Field Approach in the Numerical Study of the Elastic Bending Energy for Vesicle Membranes, Q. Du, C. Liu and X. Wang, J. Computational Physics, 198, pp. 450-468, 2004 2.Retrieving topological information for phase field models, Q. Du, C. Liu and X. Wang, 2004, to appear in SIAM J. Appl. Math 3. Phase field modeling of the spontaneous curvature effect in cell membranes, Q. Du C. Liu, R. Ryham and X. Wang, 2005, to appear in CPAA 4. A phase field formulation of the Willmore problem. Q. Du, C. Liu, R. Ryham and X. Wang, 2005, to appear in Nonlinearity | |

Weinan E (Princeton University) | Lecture 1: Overview of Multiscale Methods |

Abstract: We will begin by reviewing the basic issues and concepts in multiscale modeling, including the various models of multi-physics, serial and concurrent coupling strategies, and the essential features of the kind of multiscale problems that we would like to deal with. We then discuss some representative examples of successful multiscale methods, including the Car-Parrinello method and the quasi-continuum method. Finally we discuss several general methodologies for multiscale, multi-physics modeling, such as the domain decomposition methods, adaptive model refinement and heterogeneous multiscale methods. These different methodologies are illustrated on one example, the contact line problem. Throughout this presentation, we will emphasize the interplay between physical models and numerical methods, which is the most important theme in modern multiscale modeling. | |

Weinan E (Princeton University) | Lecture 2: Problems with multiple time scales |

Abstract: We will discuss the mathematical background and numerical techniques for three types of problems with multiple time scales: stiff ODEs, Markov chains with disparate rates and rare events. | |

Ryan S. Elliott (University of Michigan) | Bifurcation and stability of multilattices with applications to martensitic transformations in shape memory alloys |

Abstract: Some of the most interesting and technologically important solid--solid transformations are the first order diffusionless transformations that occur in certain ordered multi-atomic crystals. These include the reconstructive martensitic transformations (where no group--subgroup symmetry relationship exists between the phases) found in steel and ionic compounds such as CsCl, as well as the thermally-induced, reversible, proper (group--subgroup relationships exist) martensitic transformations that occur in shape memory alloys such as NiTi. Shape memory alloys are especially interesting, for engineering applications, due to their strong thermomechanical (multi-physics) coupling. The mechanism responsible for these temperature-induced transformations is a change in stability of the crystal's lattice structure as the temperature is varied. To model these changes in lattice stability, a continuum-level thermoelastic energy density for a bi-atomic multilattice is derived from a set of temperature-dependent atomic potentials. The Cauchy-Born kinematic assumption is employed to ensure, by the introduction of internal atomic shifts, that each atom is in equilibrium with its neighbors. Stress-free equilibrium paths as a function of temperature are numerically investigated, and an asymptotic analysis is used to identify the paths emerging from "multiple bifurcation" points that are encountered. The stability of each path against all possible bounded perturbations is determined by calculating the phonon spectra of the crystal. The advantage of this approach is that the stability criterion includes perturbations of all wavelengths instead of only the long wavelength information that is available from the stability investigation of homogenized continuum models. The above methods will be reviewed, and results corresponding to both reconstructive and proper martensitic transformations will be presented. Of particular interest is the prediction of a transformation that has been experimentally observed in CuAlNi, AuCd, and other shape memory alloys. | |

Leslie F. Greengard (New York University) | Lecture 1: Fast multipole methods and their applications |

Abstract: In these lectures, we will describe the analytic and computational foundations of fast multipole methods (FMMs), as well as some of their applications. They are most easily understood, perhaps, in the case of particle simulations, where they reduce the cost of computing all pairwise interactions in a system of N particles from O(N²) to O(N) or O(N log N) operations. FMMs are equally useful, however, in solving partial differential equations by first recasting them as integral equations. We will present examples from electromagnetics, elasticity, and fluid mechanics. | |

Thomas C. Hales (University of Pittsburgh) | IMA Public Lecture: Computers and the Future of Mathematical Proof |

Abstract: Computers crash, hang, succumb to viruses, run buggy programs, and harbor spyware. By contrast, mathematics is free of all imperfection. Why are imperfect computational devices so vital for the future of mathematics? | |

Viet Ha Hoang (Cambridge University) | High-dimensional finite elements for elliptic problems with multiple scales |

Abstract: Joint work with Christoph Schwab. Elliptic homogenization problems in a d dimensional domain with n+1 separated scales are reduced to elliptic one-scale problems in dimension (n+1)d. These one-scale problems are discretized by a sparse tensor product finite element method (FEM). We prove that this sparse FEM has accuracy, work and memory requirement comparable to standard FEM for single scale problems in while it gives numerical approximations of the correct homogenized limit as well as of all first order correctors, throughout the physical domain with performance independent of the physical problem's scale parameters. Numerical examples for model diffusion problems with two and three scales confirm our results. | |

Jesus A. Izaguirre (University of Notre Dame) | Multiscale approaches to molecular dynamics and sampling |

Abstract: In the first part of this talk, I will survey some approaches for producing multiscale models for molecular dynamics (MD) and sampling. I will consider two parts of the problem: finding coarsened variables, and then integrating or propagating the coarsened model. I will discuss the approach of Brandt and collaborators to semi-automatically determine the coarsened variables, and the more ad-hoc approach of Gear and collaborators, who assume a reaction-coordinate is known which produces a natural separation of scales. Both methods attempt to sample the fast scales, and then to do an accurate integration of the slow scales. Related approaches will be mentioned, such as Leimkuhler's and Reich's reversible integrators. | |

Brian Laird (University of Kansas) | Direct calculation of crystal-melt interfacial free energies from molecular simulation |

Abstract: The crystal-melt interfacial free energy, the work required to create a unit area of interface between a crystal and its own melt, is a controlling property in the kinetics and morphology of crystal growth and nucleation, especially in the case of dendritic growth. Despite the technological importance of this quantity, accurate experimental data is difficult to obtain. The paucity of experimental measurements has motivated the development of a variety of novel computational methods to determine the interfacial free energy via molecular simulation. After a short tutorial on thermodynamic integration techniques for free energy calculation, I will introduce our method of cleaving walls for the calculation of the crystal-melt interfacial free energy, and a competing method based on fluctuation spectra. Results for a variety of simple systems will be presented to give a broad picture of the interaction and crystal structure dependence of the interfacial free energy. The results will be discussed in relation to popular empirical theories of the interfacial free energy. | |

Melvin Leok (University of Michigan) | Generalized Galerkin variational integrators: Lie group, multiscale and spectral methods |

Abstract: Geometric mechanics involves the study of Lagrangian and Hamiltonian mechanics using geometric and symmetry techniques. Computational algorithms obtained from a discrete Hamilton's principle yield a discrete analogue of Lagrangian mechanics, and they exhibit excellent structure-preserving properties that can be ascribed to their variational derivation. We propose a natural generalization of discrete variational mechanics, whereby the discrete action, as opposed to the discrete Lagrangian, is the fundamental object. This is achieved by appropriately choosing a finite dimensional function space to approximate sections of the configuration bundle and numerical quadrature techniques to approximate the action integral. We will discuss how this general framework allows us to recover high-order Galerkin variational integrators, asynchronous variational integrators, and symplectic-energy-momentum integrators. In addition, we will also introduce generalizations such as high-order symplectic-energy-momentum integrators, Lie group integrators, high-order Euler-Poincare integrators, multiscale variational integrators, and pseudospectral variational integrators. This framework will be illustrated by an application of Lie group variational integrators to rigid body dynamics wherein the discrete trajectory evolves in the space of 3x3 matrices, while automatically staying on the rotation group, without the use of local coordinates, constraints, or reprojection. This is joint work with Taeyoung Lee and Harris McClamroch. | |

Hailiang Liu (Iowa State University) | Critical intensities for phase transitions in a 3D Smoluchowski equation |

Abstract: We study the structure of equilibrium solutions to a Smoluchowski equation on a sphere, which arises in the modelling of rigid rod-like molecules of polymers. A complete classification of intensities for phase transitions to equilibrium solutions is obtained. It is shown that the number of equilibrium solutions hinges on whether the potential intensity crosses two critical values alpha_1 approximately 6.731393 and alpha_2 = 7.5. Furthermore, we present explicit formulas for all equilibrium solutions. These solutions consist of a set of axially symmetric functions and all those which are obtained from this set by rotation. In this joint work with Hui Zhang and Pingwen Zhang, we solve the Onsager's 1949 conjecture on phase transitions in rigid rodlike polymers. | |

Stefan Mueller (Max Planck Institute for Math in the Sciences) | A variational model of dislocations in the line tension limit |

Abstract: We study the (Gamma) limit of a dislocation model proposed by Ortiz et al., in which slip occurs only on one plane. Mathematically the core is an extension of the Alberti-Bouchitte-Seppecher results for 1/eps nonconvex two-well energy + H^{1/2} norm squared to an periodic array of wells (hence no naive coercivity). From the analysis point of view H^{1/2} is interesting since it leads to a logarithnmic rescaling. | |

Xiaochuan Pan (University of Chicago) | Volumetric computed tomography and its applications |

Abstract: Computed tomography (CT) is one of the most widely used imaging modality in medicine and other areas. In this lecture, following the introduction of the basic principle of CT, I will describe what physical quantity is measured and how an image is reconstructed from the measured data in CT. Based upon such knowledge about CT, I will tour recent advances of CT technology and their new biomedical applications. One of such important advances is the advent of helical cone-beam CT and the breakthroughs in imaging theory associated with it. These technological and theoretical advances in CT have brought immediate important impact on medical and other applications of CT, offering tremendous opportunities to design innovative imaging protocols and applications that are otherwise impossible. One of the important trends in CT imaging is the so-called targeted imaging of a region of interest (ROI) within the subject from truncated data. Such a strategy for targeted imaging would substantially reduce the radiation dose delivered to the subject and scanning effort. I will discuss the theory and algorithms that we have developed recently for exact reconstruction of ROI images. Finally, I will touch upon the implications of these new developments in CT imaging theory for other tomographic imaging modalities. | |

Paul R Schrater (University of Minnesota) | Natural cost functions for contact point selection in grasping |

Abstract: When reaching to touch or lift an object, how are contact points visually selected? In this talk I will formulate the issue as a statistical decision theory problem that requires minimizing the expectation over a suitable loss function. However, it is the nature of this loss function that is the heart of the presentation. In the first part of the talk, I will show how contact points for two fingered grasp can be optimally chosen, given a plan for the grasped object's motion. The basic assumption is that the minimum control framework used to predict hand trajectories should also apply to the control of the grasped object. The cost function on the object's motion can then be rewritten in terms of finger placement and contact, inducing a cost function on finger contact points. I will present human reaching data that supports this idea. In the second part of the talk, I will present evidence for a decomposition of the natural cost function for reaching into task completion and motor control components. The issue can be framed as follows: In many reaching tasks there are a set of contact points that are equivalent in terms of task completion cost -- touching a line, for example. In generating a path, the ambiguity is broken by motor control cost, which distinguishes the minimum control point of the set (e.g. the closest point on the line). This unique target point could be selected to generate a simple feedback control strategy of minimizing distance to the target. Alternatively, a feedback control strategy could be based directly on a lumped cost function. These two strategies behave differently under a perturbing force field mid-reach: the first corrects the perturbations, while the second "goes with the flow" to contact the new minimum control point within the task completion set. I will present data supports the idea that reaches "go with the flow", adapting to external perturbations. This suggests that the brain visually encodes and adaptively uses the set of viable contact points. Finally, I will discuss why the contact point selection problem is important for understanding the sensory demands made by the motor control system during reaching. | |

Joerg Schumacher (Philipps University Marburg) | Stretching of polymers on sub-Kolmogorov scales in a turbulent flow |

Abstract: First results on numerical studies of the stretching of Hookean dumbbells on scales below the viscous length of the advecting turbulent flow are presented. Direct numerical simulations of the Navier-Stokes turbulence are combined with Brownian dynamics simulations for simple polymer chains. The role of extreme stretching events on the overall statistics is discussed. Our findings are compared with recent analytical models for the polymer advection in Gaussian random flow without time-correlation. | |

James A. Sethian (University of California) | Lecture 1: Advances in advancing interfaces: Level set methods, fast marching methods, and beyond |

Abstract: Propagating interfaces occur in a variety of settings, including semiconductor manufacturing in chip production, the fluid mechanics of ink jet plotters, segmentation in cardiac medical imaging, computer-aided-design, optimal navigation in robotic assembly, and geophysical wave propagation. Over the past 25 years, a collection of numerical techniques have come together, including Level Set Methods and Fast Marching Methods for computing such problems in interface phenomena in which topological change, geometry-driven physics, and three-dimensional complexities play important roles. These algorithms, based on the interplay between schemes for hyperbolic conservation laws and their connection to the underlying theory of curve and surface evolution, offer a unified approach to computing a host of interface prn this tutorial, the author will cover (i) the development of these methods, (ii) the fundamentals of Level Set Methods and Fast Marching Methods, including efficient, adaptive versions, and the coupling of these schemes to complex physics, and (iii) new approaches to tackling more demanding interface problems. The emphasis in this tutorial will be on a practical, "hands-on" view, and the methods and algorithms will be discussed in the context of on-going collaborative projects, including work on semiconductor processing, industrial ink jet design, and medical and bio-medical imaging. | |

Jan Vandenbrande (Boeing) | Solid modeling: Math at work in design |

Abstract: Design is the art of creating something new and predicting how it will perform before it is ever build. One of the major breakthroughs in the last 25 years is the ability to describe a design as a virtual artifact in a computer, and simulate its physical characteristics accurately to enable designers to make better decisions. The core technology that underlies these mechanical Computer Aided Design and Manufacturing (CAD/CAM) systems is solid modeling, whose theoretical underpinnings are grounded in mathematics. This talk will cover some of these mathematical concepts, including point set topology, regularized set operations, Constructive Solid Geometry (CSG), representation schemes, algorithms and geometry. We will cover the impact of solid modeling in industry, and discuss some of the remaining open issues such as the ambiguity between the topological representation and the computed geometric boundary. | |

Epifanio G. Virga (Universita di Pavia) | Mathematical models for biaxial liquid crystals phases |

Abstract: The search for thermotropic biaxial phases has recently found some firm evidence of their existence. It has rightly been remarked that this "announcement has created considerable excitement, for it opens up new areas of both fundamental and applied research. It seems that a Holy Grail of liquid-crystal science has at last been found" (see G.R. Luckhurst, Nature 430, 413 (2004)). In this lecture, I shall present a mean-field model that has the potential to describe such an evanescent phase of matter. More specifically, I show the outcomes of a bifurcation analysis of the equilibrium equations and I illuminate the complete phase diagram, which exhibits two tricritical points. The predictions of this analysis are also qualitatively confirmed by a Monte Carlo simulation study. One of the main conclusions is that two order parameters suffice to label all equilibrium phases, though they exhibit different bifurcation patterns. | |

Rebecca Willett (University of Minnesota) | Multiscale photon-limited image analysis |

Abstract: Many critical scientific and engineering applications rely upon the accurate reconstruction of spatially or temporally distributed phenomena from photon-limited data. However, a number of information processing challenges arise routinely in these problems: Sensing is often indirect in nature, such as tomographic projections in medical imaging, resulting in complicated inverse reconstruction problems. Limited system resources, such as data acquisition time and image storage requirements, lead to complex tradeoffs between communications, sensing and processing. Furthermore, the measurements are often "noisy" due to low photon counts. In addition, the behavior of the underlying photon intensity functions can be very rich and complex, and consequently difficult to model a priori. All of these issues combine to make accurate reconstruction a complicated task, involving a myriad of system-level and algorithm tradeoffs. In this talk, I will demonstrate that nonparametric multiscale reconstruction methods can overcome all the challenges above and provide a theoretical framework for assessing tradeoffs between reconstruction accuracy and system resources. First, the theory supporting these methods facilitates characterization of fundamental performance limits. Examples include lower bounds on the best achievable error performance in photon-limited image reconstruction and upper bounds on the data acquisition time required to achieve a target reconstruction accuracy. Second, existing reconstruction methods can often be enhanced with multiscale techniques, resulting in significant improvements in a number of application domains. Underlying these methods are ideas drawn from the theory of multiscale analysis, statistical learning, nonlinear approximation theory, and iterative reconstruction algorithms. I will demonstrate the effectiveness of the theory and methods in several important applications, including superresolution imaging and medical image reconstruction. | |

Doug Wright (University of Minnesota) | Higher order corrections to the KdV approximation for water waves |

Abstract: In order to investigate corrections to the common KdV approximation to long waves, we derive modulation equations for the evolution of long wavelength initial data for the water wave and Boussinesq equations. The equations governing the corrections to the KdV approximation are identical for both systems and are explicitly solvable. We prove estimates showing that they do indeed give a significantly better approximation than the KdV equation alone. We also present the results of numerical experiments which show that the error estimates we derive for the correction to the Boussinesq equation are essentially optimal. | |

Chenyang Xu (Siemens Corporate Research) | Medical image segmentation using deformable models |

Abstract: In the past four decades, computerized image segmentation has played an increasingly important role in medical imaging. Segmented images are now used routinely in a multitude of different applications, such as the quantification of tissue volumes, diagnosis, localization of pathology, study of anatomical structure, treatment planning, partial volume correction of functional imaging data, and computer-assisted surgery. Image segmentation remains a difficult task, however, due to both the tremendous variability of object shapes and the variation in image quality. In particular, medical images are often corrupted by noise and sampling artifacts, which can cause considerable difficulties when applying classical segmentation techniques such as edge detection and thresholding. As a result, these techniques either fail completely or require some kind of postprocessing step to remove invalid object boundaries in the segmentation results. To address these difficulties, deformable models have been extensively studied and widely used in medical image segmentation, with promising results. Deformable models are curves or surfaces defined within an image domain that can move under the influence of internal forces, which are defined within the curve or surface itself, and external forces, which are computed from the image data. By constraining extracted boundaries to be smooth and incorporating other prior information about the object shape, deformable models offer robustness to both image noise and boundary gaps and allow integrating boundary elements into a coherent and consistent mathematical description. Such a boundary description can then be readily used by subsequent applications. Since its introduction 15 years ago, deformable models have grown to be one of the most active and successful research areas in image segmentation. There are basically two types of deformable models: parametric deformable models and geometric deformable models. Parametric deformable models represent curves and surfaces explicitly in their parametric forms during deformation. This representation allows direct interaction with the model and can lead to a compact representation for fast real-time implementation. Adaptation of the model topology, however, such as splitting or merging parts during the deformation, can be difficult using parametric models. Geometric deformable models, on the other hand, can handle topological changes naturally. These models, based on the theory of curve evolution and the level set method, represent curves and surfaces implicitly as a level set of a higher-dimensional scalar function. Their parameterizations are computed only after complete deformation, thereby allowing topological adaptivity to be easily accommodated. Despite this fundamental difference, the underlying principles of both methods are very similar. In this talk, I will present an overall description of the development in deformable models research and their applications in medical imaging. I will first introduce parametric deformable models, and then describe geometric deformable models. Next, I will present an explicit mathematical relationship between parametric deformable models and geometric deformable models. Finally, I will present several extensions to these deformable models by various researchers and point out future research directions. |

Visitors in Residence

Stuart Antman | University of Maryland | 3/20/2005 - 4/1/2005 |

Douglas N. Arnold | University of Minnesota | 7/15/2001 - 8/31/2006 |

Donald G. Aronson | University of Minnesota | 9/1/2002 - 8/31/2005 |

Gerard Awanou | University of Minnesota | 9/2/2003 - 8/31/2005 |

John Ball | Oxford University | 3/13/2005 - 3/25/2005 |

Daniel E. Bentil | University of Vermont | 3/26/2005 - 4/16/2005 |

Paolo Biscari | Politecnico di Milano | 3/16/2005 - 4/2/2005 |

Sandstede Bjorn | University of Surrey-England | 2/21/2005 - 3/1/2005 |

Maria-Carme Calderer | University of Minnesota | 9/1/2004 - 6/30/2005 |

Carsten Carstensen | Humboldt Universität zu Berlin | 3/8/2005 - 3/21/2005 |

Qianyong Chen | University of Minnesota | 9/1/2004 - 8/31/2006 |

Giovanni Ciccotti | University of Rome "La Sapienza" | 3/20/2005 - 4/20/2005 |

Fabrizio Cleri | Universita di Perugia | 3/20/2005 - 5/23/2005 |

L. Pamela Cook | University of Delaware | 3/18/2005 - 3/20/2005 |

Norman Dancer | University of Sydney | 2/20/2005 - 3/22/2005 |

Antonio DeSimone | SISSA-Italy | 3/10/2005 - 7/15/2005 |

Brian DiDonna | University of Minnesota | 9/1/2004 - 8/31/2006 |

Elena Dimitrova | Virginia Tech | 3/27/2005 - 3/30/2005 |

Charles Doering | University of Michigan | 3/19/2005 - 3/20/2005 |

Qiang Du | Pennsylvania State University | 3/26/2005 - 4/1/2005 |

Weinan E | Princeton University | 3/27/2005 - 3/31/2005 |

Charles M. Elliott | University of Sussex | 3/20/2005 - 4/15/2005 |

Ryan S. Elliott | University of Michigan | 1/1/2005 - 6/30/2005 |

Ralf Everaers | Max-Planck-Institut for Physics of Complex Systems | 3/28/2005 - 5/1/2005 |

Wilfrid Gangbo | Georgia Institute of Technology | 3/13/2005 - 3/22/2005 |

Tim Garoni | University of Minnesota | 8/25/2003 - 8/31/2005 |

Eugene C. Gartland Jr. | Kent State University | 1/10/2005 - 6/30/2005 |

Dmitry Golovaty | University of Akron | 3/1/2005 - 3/31/2005 |

Jian Ping Gong | Hokkaido University | 3/21/2005 - 3/26/2005 |

Leslie F. Greengard | New York University | 3/27/2005 - 3/30/2005 |

Jean-Luc Guermond | Texas A & M University | 3/25/2005 - 3/31/2005 |

Robert Gulliver | University of Minnesota | 9/1/2004 - 6/30/2005 |

Rohit Gupta | University of Minnesota | 3/28/2005 - 3/30/2005 |

Thomas C. Hales | University of Pittsburgh | 3/29/2005 - 3/31/2005 |

Chuan-Hsiang Han | University of Minnesota | 9/1/2004 - 8/31/2005 |

Viet Ha Hoang | Cambridge University | 3/5/2005 - 4/16/2005 |

Jesus A. Izaguirre | University of Notre Dame | 3/3/2005 - 3/16/2005 |

Richard D. James | University of Minnesota | 9/1/2004 - 6/30/2005 |

Shi Jin | University of Wisconsin | 1/4/2005 - 6/30/2005 |

Sookyung Joo | University of Minnesota | 9/1/2004 - 8/31/2006 |

Lili Ju | University of South Carolina | 3/27/2005 - 3/30/2005 |

Chiu Yen Kao | University of Minnesota | 9/1/2004 - 8/31/2006 |

Robert V. Kohn | New York University - Courant Institute | 3/17/2005 - 3/20/2005 |

Richard Kollar | University of Minnesota | 9/1/2004 - 8/31/2005 |

Matthias Kurzke | University of Minnesota | 9/1/2004 - 8/31/2006 |

Brian Laird | University of Kansas | 3/6/2005 - 3/11/2005 |

Namyong Lee | Mankato State University | 3/27/2005 - 3/30/2005 |

Frederic Legoll | University of Minnesota | 9/3/2004 - 8/31/2006 |

Benedict Leimkuhler | University of Leicester | 2/1/2005 - 6/2/2005 |

Melvin Leok | University of Michigan | 3/27/2005 - 3/30/2005 |

Debra Lewis | University of Minnesota | 7/15/2004 - 8/31/2006 |

Xiantao Li | University of Minnesota | 8/3/2004 - 8/31/2006 |

Hua Lin | Purdue University | 3/27/2005 - 3/30/2005 |

Chun Liu | Pennsylvania State University | 9/1/2004 - 6/30/2005 |

Hailiang Liu | Iowa State University | 1/1/2005 - 6/30/2005 |

Irene Livshits | Ball State University | 3/8/2005 - 3/13/2005 |

Mitchell Luskin | University of Minnesota | 9/1/2004 - 6/30/2005 |

Stefan Mueller | Max Planck Institute for Math in the Sciences | 3/9/2005 - 3/25/2005 |

David Nicholls | University of Notre Dame | 3/26/2005 - 4/1/2005 |

Felix Otto | University of Bonn | 3/21/2005 - 4/16/2005 |

Peter Palffy-Muhoray | Kent State University | 3/15/2005 - 5/15/2005 |

Xiaochuan Pan | University of Chicago | 3/24/2005 - 3/24/2005 |

Alexander Panchenko | Washington State University | 3/12/2005 - 3/24/2005 |

Peter Philip | University of Minnesota | 8/22/2004 - 8/31/2006 |

Petr Plechac | University of Warwick | 3/21/2005 - 4/15/2005 |

Lea Popovic | University of Minnesota | 9/2/2003 - 8/31/2005 |

Kumbakonam Rajagopal | Texas A & M University | 3/14/2005 - 3/20/2005 |

S.S. Ravindran | University of Alabama - Huntsville | 3/27/2005 - 3/30/2005 |

Maria Reznikoff | Courant Institute, New York University | 3/27/2005 - 4/17/2005 |

Rolf Ryham | Pennsylvania State University | 9/1/2004 - 6/30/2005 |

Arnd Scheel | University of Minnesota | 7/15/2004 - 8/31/2006 |

Anja Schloemerkemper | University of Stuttgart | 3/6/2005 - 3/17/2005 |

Paul R Schrater | University of Minnesota | 3/3/2005 - 3/3/2005 |

Joerg Schumacher | Philipps University Marburg | 3/18/2005 - 3/18/2005 |

George R Sell | University of Minnesota | 9/1/2004 - 6/30/2005 |

Shaun Sellers | Washington University - St. Louis | 3/5/2005 - 3/12/2005 |

James A. Sethian | University of California | 3/27/2005 - 3/30/2005 |

Jie Shen | Purdue University | 3/22/2005 - 4/2/2005 |

Tien-Tsan Shieh | Indiana University | 9/1/2004 - 6/30/2005 |

Devashish Shrivastava | University of Minnesota | 3/28/2005 - 3/30/2005 |

Valery P. Smyshlyaev | University of Bath-UK | 2/1/2005 - 3/3/2005 |

Daniel Spirn | University of Minnesota | 9/1/2004 - 6/30/2005 |

Peter J. Sternberg | Indiana University | 8/15/2004 - 6/15/2005 |

Vladimir Sverak | University of Minnesota | 9/1/2004 - 6/30/2005 |

Chris R. Sweet | University of Leicester | 2/7/2005 - 3/15/2005 |

Eugene Terentjev | Cambridge University | 3/13/2005 - 4/30/2005 |

K. Thangavel | Gandhigram Rural Institute-Deemed University | 3/27/2005 - 3/30/2005 |

Philippe Tondeur | University of Illinois - Urbana-Champaign | 3/19/2005 - 3/20/2005 |

Yoshihiro Tonegawa | Hokkaido University | 3/16/2005 - 3/25/2005 |

Miroslav Trajkovic | Symbol Technologies | 3/31/2005 - 4/1/2005 |

Igor Tsukerman | University of Akron | 3/27/2005 - 3/30/2005 |

Jan Vandenbrande | Boeing | 3/24/2005 - 3/25/2005 |

Shankar Venkataramani | University of Arizona | 2/19/2005 - 3/12/2005 |

Epifanio G. Virga | Universita di Pavia | 2/26/2005 - 3/25/2005 |

Qi Wang | Florida State University | 1/31/2005 - 5/15/2005 |

Stephen J. Watson | Northwestern University | 9/1/2004 - 6/30/2005 |

Rebecca Willett | University of Minnesota | 3/10/2005 - 3/10/2005 |

Ruth Williams | University of California - San Diego | 3/19/2005 - 3/20/2005 |

Doug Wright | University of Minnesota | 2/15/2005 - 8/31/2005 |

Chenyang Xu | Siemens Corporate Research | 3/3/2005 - 3/4/2005 |

Baisheng Yan | Michigan State University | 9/1/2004 - 6/30/2005 |

Mihalis Yannakakis | Columbia University | 3/19/2005 - 3/20/2005 |

Aaron Nung Kwan Yip | Purdue University | 1/16/2005 - 6/30/2005 |

Emmanuel Yomba | University of Ngaoundéré | 10/6/2004 - 8/31/2005 |

Pingwen Zhang | Peking University | 3/16/2005 - 3/31/2005 |

Erik van der Giessen | University of Groningen | 3/19/2005 - 3/26/2005 |

Legend:
Postdoc or Industrial Postdoc
Long-term Visitor

Participating Institutions:
Carnegie Mellon University, Consiglio Nazionale delle Ricerche (CNR), Georgia Institute of Technology, Indiana University, Iowa State University, Kent State University, Lawrence Livermore National Laboratories, Los Alamos National Laboratory, Michigan State University, Mississippi State University, Northern Illinois University, Ohio State University, Pennsylvania State University, Purdue University, Rice University, Sandia National Laboratories, Seoul National University (BK21), Seoul National University (SRCCS), Texas A & M University, University of Chicago, University of Cincinnati, University of Delaware, University of Houston, University of Illinois - Urbana-Champaign, University of Iowa, University of Kentucky, University of Maryland, University of Michigan, University of Minnesota, University of Notre Dame, University of Pittsburgh, University of Texas - Austin, University of Wisconsin, University of Wyoming, Wayne State University

Participating Corporations:
3M, Boeing, Corning, ExxonMobil, Ford Motor Company, General Electric, General Motors, Honeywell, IBM Corporation, Johnson & Johnson, Lockheed Martin, Lucent Technologies, Motorola, Schlumberger-Doll Research, Siemens, Telcordia Technologies