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IMA Newsletter #346

August 2005

News and Notes

NSF announces record funding for the IMA

The IMA has been awarded a $19.5 million renewal grant by the National Science Foundation for the period 2005‒2010, the largest single research investment in mathematics ever made by NSF and a 77% increase over the IMA's previous level of NSF support. NSF math director William Rundell made the announcement at the IMA on July 20.

Press coverage: U of M (article, press release) · Star Tribune (article, graphic) · MPR · PhysOrg.com

Fall 2005: Sensors to Images

The 2005‒2006 thematic program Imaging opens with the tutorial Radar and Optical Imaging, September 19‒23. The tutorial will consist of two lecture series providing background on imaging techniques for two different regions of the electromagnetic spectrum–the microwave and optical regions. The lectures will provide background on radar imaging, computational optical imaging, and spectroscopy.

The theme of the fall semester is Sensors to Images. Progress in sensor technology is generating new types of data and creating new research areas offering exciting opportunities for mathematicians, including quantum state imaging, nanoscale imaging, and network tomography. Data obtained from wave propagation phenomena will receive special attention, with examples from radar, ultrasound, and seismic prospecting. Another focus will be the emerging area of Integrated Sensing and Processing, i.e. intelligent integration of detection and processing in a systems approach.

There will be three workshops in the fall semester:

IMA Events

Mathematical Modeling in Industry IX – A Workshop for Graduate Students

August 1‒10, 2005

Organizers: Richard J. Braun (University of Delaware), Fernando Reitich (University of Minnesota), Fadil Santosa (University of Minnesota)

http://www.ima.umn.edu/modeling/mm05.html

The IMA's ninth workshop on Mathematical Modeling in Industry will provide graduate students and qualified advanced undergraduates with first hand experience in industrial research. Students will work in teams of five to six students under the guidance of a mentor from industry, who will guide the students in the modeling process, analysis and computational work associated with a real-world industrial problem. Each team will give an oral mid-program progress report and final presentation, and submit a written final report.

New Directions in Probability Theory

August 5‒6, 2005

Organizer: Maury Bramson (University of Minnesota)

http://www.imstat.org/meetings/NDPT05/

The meeting is co-sponsored by the Institute of Mathematical Statistics (IMS) and the IMA. It is intended for a general probability audience interested in recent developments in probability theory. The session topics are Flows and Random Media; Probability, Combinatorics, and Statistical Mechanics; Stochastic Integration; Stochastic Partial Differential Equations; and Random Walk in Random Environment.

New Directions Short Course: Quantum Computation

August 15‒26, 2005

Instructors: Peter Shor (MIT) and Alexei Kitaev (Caltech)

http://www.ima.umn.edu/matter/ND8.15-26.05/index.html

The third New Directions Short Course will provide a select group of midcareer mathematicians with the basic knowledge prerequisite to research in quantum computation. The course will begin with an introduction to quantum mechanics and quantum computation. It will then pursue two tracks: quantum algorithms and error correction led by Peter Shor, and topological quantum computation, led by Alexei Kitaev. A typical day during the two weeks course will consist of two general lectures, one by the principal speakers in the morning, each one-and-a-half hours in duration. Afternoons will be used for topical lectures by guest speakers, and for problem solving and brain-storming sessions.

IMA New Directions Short Courses are limited to 25 participants, with an application deadline of April 1.

Schedule

Monday, August 1

MorningPosing of problems by the industry mentors. EE/CS 3-180 MM8.1-10.05
9:00a-9:30aCoffee and RegistrationEE/CS 3-176 MM8.1-10.05
9:30a-9:40aWelcome and IntroductionDouglas N. Arnold (University of Minnesota)
Richard J. Braun (University of Delaware)
Fernando Reitich (University of Minnesota)
Fadil Santosa (University of Minnesota)
EE/CS 3-180 MM8.1-10.05
9:40a-10:00aTeam 1: Sparse Aperture ImagingD. Gregory Arnold (Air Force Research Laboratory)EE/CS 3-180 MM8.1-10.05
10:00a-10:20aTeam 2: Uncertainty Quantification in Geophysical Inverse ProblemsNicholas Bennett (Schlumberger-Doll Research)EE/CS 3-180 MM8.1-10.05
10:20a-10:40aTeam 3: Contact Algorithms for Dry Granular Flow with Elastic GrainsPetri Fast (Lawrence Livermore National Laboratories)EE/CS 3-180 MM8.1-10.05
10:40a-11:00aBreak EE/CS 3-176 MM8.1-10.05
11:00a-11:20aTeam 4: Integrated Circuit Layout ReconstructionEdward Keyes (Semiconductor Insights)EE/CS 3-180 MM8.1-10.05
11:20a-11:40aTeam 5: Models of Human Physiology, and Randomized Clinical TrialsDavid S. Ross (Kaiser Permanente)EE/CS 3-180 MM8.1-10.05
11:40a-12:00pTeam 6: Algorithms for Digital HalftoningChai Wah Wu (IBM Corporation)EE/CS 3-180 MM8.1-10.05
12:00p-1:00p Lunch Orchid Cafe, Thai Cuisine 304 Oak Street Minneapolis Phone: 612-331-4061 MM8.1-10.05
1:30p-4:30pGroups start work on projects. Mentors guide their groups through the modeling process, leading discussion sessions, suggesting references, and assigning work. EE/CS 3-180 MM8.1-10.05

Tuesday, August 2

All DayStudents and mentors work on the projects. EE/CS 3-180 MM8.1-10.05

Wednesday, August 3

All DayStudents and mentors work on the projects. EE/CS 3-180 MM8.1-10.05

Thursday, August 4

All DayStudents and mentors work on the projects. EE/CS 3-180 MM8.1-10.05

Friday, August 5

MorningInformal progress reports. Lind Hall 305 MM8.1-10.05
8:15a-8:45aCoffee and registrationEE/CS 3-176 W8.5-6.05
8:45a-10:30aSession: Probability, Combinatorics, and Statistical Mechanics
Organizer:
Russell Lyons (Indiana University)EE/CS 3-180 W8.5-6.05
Infinite volume limit of the Abelian sandpile model on ZdAntal Jarai (Carleton University)
Simple random surfacesRichard Kenyon (University of British Columbia)
Tug of war and the infinity LaplacianScott Sheffield (New York University)
9:30a-9:50aTeam 2 Progress ReportLind Hall 305 MM8.1-10.05
9:50a-10:10aTeam 4 Progress ReportLind Hall 305 MM8.1-10.05
10:10a-10:30aTeam 3 Progress ReportLind Hall 305 MM8.1-10.05
10:30a-11:00aBreakEE/CS 3-176 W8.5-6.05
10:30a-10:50aBreak Lind Hall 400 MM8.1-10.05
10:50a-11:10aTeam 6 Progress ReportLind Hall 305 MM8.1-10.05
11:00a-12:00pInvited Lecture: Rough paths: a top down description of controlsTerence Lyons (Oxford University)EE/CS 3-180 W8.5-6.05
11:30a-12:50pTeam 1 Progress ReportLind Hall 305 MM8.1-10.05
12:00p-1:30pLunch W8.5-6.05
12:15p-2:00pPicnicTBA MM8.1-10.05
1:30p-2:30pMedallion Lecture: Recent results and open problems concerning motion in random mediaOfer Zeitouni (University of Minnesota)EE/CS 3-180 W8.5-6.05
2:30p-2:45pBreak W8.5-6.05
2:45p-4:30pSession: Flows and Random Media
Organizer:
Michael Cranston (University of California - Irvine)EE/CS 3-180 W8.5-6.05
The pinning transition for a polymer in the presence of a random potentialKen Alexander (University of Southern California)
Spectral asymptotics of Laplacians on bond-percolation graphsPeter Mueller (University of Goettingen)
Spatial inhomogeneities and large scale behavior of the asymmetric exclusion processTimo Seppalainen (University of Wisconsin)
4:30p-4:45pBreakEE/CS 3-176 W8.5-6.05
4:45p-6:00pMedallion Lecture: The disconnection time of the random walk on a discrete cylinderAmir Dembo (Stanford University)EE/CS 3-180 W8.5-6.05
6:00p-8:00pReception and poster sessionLind Hall 400 W8.5-6.05
A state machine approach to study pattern frequencies in Markovian sequencesManuel Lladser (University of Colorado)
Sub-independence for stable random variablesAdel Mohammadpour (Universite Paris-Sud)

Saturday, August 6

All DayStudents and mentors work on the projects. EE/CS 3-180 MM8.1-10.05
8:45a-10:30aSession:Stochastic Integration
Organizer:
Terence Lyons (Oxford University)EE/CS 3-180 W8.5-6.05
Anticipating stochastic calculus via good rough path sequencesPeter Friz (Courant Institute)
Applications of rough paths to speech recognitionAnastasia Papavasiliou (Princeton University)
Stochastic integrals for processes with long-time memoryZhongmin Qian (Oxford University)
10:30a-11:00aBreakEE/CS 3-176 W8.5-6.05
11:00a-12:00pInvited Lecture: Unimodularity and stochastic processesRussell Lyons (Indiana University)EE/CS 3-180 W8.5-6.05
12:00p-1:30pLunch W8.5-6.05
1:30p-3:15pSession:Random Walk in Random Environment
Organizer:
Ofer Zeitouni (University of Minnesota)EE/CS 3-180 W8.5-6.05
Random walk in random sceneryNina Gantert (Universitaet Karlsruhe)
Growth in dynamic random environmentVladas Sidoravicius (IMPA, Brazil)
On some self-interacting random walks in random environmentMartin Zerner (University of Tuebingen)
3:15p-3:45pBreakEE/CS 3-176 W8.5-6.05
3:45p-5:30pSession:Stochastic Partial Differential Equations
Organizer:
Jonathan C. Mattingly (Duke University)EE/CS 3-180 W8.5-6.05
Stochastic modulation equationsMartin Hairer (University of Warwick)
On the foundation of the Lp-theory of SPDEsNicolai Krylov (University of Minnesota)
Ergodicity of the degenerately forced stochastic fluid equationsJonathan C. Mattingly (Duke University)

Sunday, August 7

All DayStudents and mentors work on the projects. EE/CS 3-180 MM8.1-10.05

Monday, August 8

All DayStudents and mentors work on the projects. EE/CS 3-180 MM8.1-10.05

Tuesday, August 9

All DayStudents and mentors work on the projects. EE/CS 3-180 MM8.1-10.05

Wednesday, August 10

MorningFinal presentations and submission of written reports. EE/CS 3-180 MM8.1-10.05
9:00a-9:30aTeam 6 Final ReportEE/CS 3-180 MM8.1-10.05
9:30a-10:00aTeam 3 Final ReportEE/CS 3-180 MM8.1-10.05
10:00a-10:30aTeam 4 Final Report MM8.1-10.05
10:30a-11:00a Break EE/CS 3-180 MM8.1-10.05
11:00a-11:30aTeam 1 Final ReportEE/CS 3-180 MM8.1-10.05
11:30a-12:00pTeam 5 Final ReportEE/CS 3-180 MM8.1-10.05
12:00p-12:30pTeam 2 Final ReportEE/CS 3-180 MM8.1-10.05
12:30p-2:00pPizza party Lind Hall 400 MM8.1-10.05

Monday, August 15

8:30a-10:00aLecture: Introduction, quantum states, operations, etc.Peter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: OverviewAlexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05
2:30p-3:00pGroup Photo ND8.15-26.05
3:00p-4:00pReceptionLind Hall 409 ND8.15-26.05

Tuesday, August 16

8:30a-10:00aLecture: Teleportation, superdense coding, introduction to quantum error correcting codes Peter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: The toric code and its variationsAlexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30p Problem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05

Wednesday, August 17

8:30a-10:00aLecture: Algorithms - periodicityPeter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: Spin Hamiltonians, ground states and excitationsAlexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05

Thursday, August 18

8:30a-10:00aLecture: Algorithms - Grover's algorithm and quantum walk algorithmsPeter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: Lattice models based on discrete groupsAlexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05

Friday, August 19

8:30a-10:00aLecture: Measures of entanglementPeter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: Quantum computation with S_3 anyonsAlexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming Session Lind Hall 409 ND8.15-26.05

Monday, August 22

8:30a-10:00aLecture: Quantum channel capacitiesPeter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture:The honeycomb lattice model Alexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming Session Lind Hall 409 ND8.15-26.05

Tuesday, August 23

8:30a-10:00aLecture: Channel capacities and additivityPeter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: Algebraic theory of anyons Alexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
11:30a-1:00pLunch ND8.15-26.05
1:30p-2:30pGuest Lecturer, Topic: TBAJohn Watrous (University of Calgary)Lind Hall 409 ND8.15-26.05
2:30p-3:30pProblem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05

Wednesday, August 24

8:30a-10:00aLecture: Quantum error correcting codesPeter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: Algebraic theory of anyons, cont. Alexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05

Thursday, August 25

8:30a-10:00aLecture: Quantum fault tolerancePeter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture:Computation with Fibonacci anyons Alexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05

Friday, August 26

8:30a-10:00aLecture: TBA Peter W. Shor (Massachusetts Institute of Technology)Lind Hall 409 ND8.15-26.05
10:00a-10:30aBreakLind Hall 400 ND8.15-26.05
10:30a-12:00pLecture: More models and the physical perspective Alexei Kitaev (California Institute of Technology)Lind Hall 409 ND8.15-26.05
12:00p-1:30pLunch ND8.15-26.05
1:30p-2:30pProblem Solving and Brain Storming SessionLind Hall 409 ND8.15-26.05
2:30p-2:45pWrap upLind Hall 409 ND8.15-26.05

Event Legend:

MM8.1-10.05Mathematical Modeling in Industry IX - A Workshop for Graduate Students
ND8.15-26.05Quantum Computation
W8.5-6.05New Directions in Probability Theory
Abstracts
Ken Alexander (University of Southern California) The pinning transition for a polymer in the presence of a random potential
Abstract: We consider a polymer, with monomer locations modeled by the trajectory of a Markov chain, in the presence of a potential that interacts with the polymer when it visits a particular site 0. We assume the probability of an excursion of length n from 0, in the absence of the potential, decays like n-c for some c>1. Disorder is introduced by, having the interaction vary from one monomer to another, as a constant u plus i.i.d. mean-0 randomness. There is a critical value of u above which the polymer is pinned, placing a positive fraction, called the contact fraction, of its monomers at 0 with high probability. We obtain bounds for the contact fraction near the critical point and examine the effect of the disorder on the specific heat exponent, which describes the approach to 0 of the contact fraction at the critical point. Our results are consistent with predictions in the physics literature that the effect of disorder is quite different in the cases c<3/2 and c>3/2.
D. Gregory Arnold (Air Force Research Laboratory) Team 1: Sparse Aperture Imaging
Abstract: Standard 2-D SAR image formation techniques require data samples that have been collected on a regular rectangular grid (with respect to the viewpoint). A target that happened to move through the imaged scene will be displaced and smeared across the final image. Imaging a moving target is equivalent to collecting data that is not on a regular grid (although more generally this generates data in a cube, rather than data in a square). Surprisingly little is understood about how to form an image in this more general case. This topic encompasses a myriad of research areas. One starting point would be to use standard scattering center models to predict the scattering at new locations. This approach requires the ability to extract viewpoint stable features from the measured data. Filtering, tracking, and dynamic programming are key elements to this approach. Alternately, knowing the final product is a 3D image, it may be possible produce the end result without requiring explicit feature extraction. Data will be available to test newly developed approaches.

Nicholas Bennett (Schlumberger-Doll Research) (Team 2) Uncertainty Quantification in Geophysical Inverse Problems
Abstract: Solving an inverse problem means determining the parameters of a model given a set of measurements. In solving many practical inverse problems, accounting for the uncertainty of the solution is very important to aid in decision-making. A standard approach to do this begins by choosing a model parametrization and then using a Bayesian approach to make inferences on the model parameters from measurement data. However, this quantified uncertainty is a function of the model parametrization and for many inverse problems, there are many model parametrizations that account for the data equally well. A well known approach to accounting for model uncertainty is Bayesian Model Averaging where many model parametrizations are considered. Wavelet model updates provide an efficient means of sifting through a family of model parametrizations given by decimated wavelet bases. By decimated wavelet basis we mean a subset of the model's coordinates in a wavelet basis. When working with measurement data sets which are particularly noisy or large in terms of their data storage size, it is natural to consider denoising or compressing the data also using a decimated wavelet representation. Kalman filters can be used to update the solution (including its uncertainty) when denoising or locally changing the resolution of the measurement data by changing the decimation. We shall explore how to compute likely representations of both model and measurements in the context of solving a few model geophysical inverse problems.
Amir Dembo (Stanford University) Medallion Lecture: The disconnection time of the random walk on a discrete cylinder
Abstract: Consider the simple random walk on the discrete cylinder whose base is the d-dimnesional torus with side-length N, and whose height is the set of all integers. When d>1, the time the walk needs to disconnect the discrete cylinder is very roughly of order N to the power 2d, and comparable to the cover time of the slice of height 0. Further, by the time disconnection occurs, a massive "clogging'' takes place in the truncated cylinders of height N to power d' for any d'
Petri Fast (Lawrence Livermore National Laboratories) (Team 3) Contact Algorithms for Dry Granular Flow with Elastic Grains
Abstract: Consider the dynamics of interacting elastic disks in the plane. This is an experimentally realizable 2-d model of dry granular flow where the stresses can be visualized using the photoelastic effect. As the elastic disks move in a vacuum they interact through collisions with each other and with the surrounding geometry. Because of the finite propagation speed of deformations inside each grain it can be difficult to capture computationally even simple experiments involving just a few interacting grains. The goal of this project is to improve our ability to simulate dense granular flow in complex geometry. Some project ideas: (A) Pursue full numerical simulations of of the interacting elastic disks driven by contact mechanics. (B) Develop simplified discrete element models for tracking the center of mass of each disk using classical mechanics including heuristics for the delay arising from the finite propagation speed of elastic deformations in each disk. (C) Compare with experimental data.
Peter Friz (Courant Institute) Anticipating stochastic calculus via good rough path sequences
Abstract: We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process (not necessarily a semi-martingale). No adaptedness of initial point or vector fields is assumed. Under a simple condition on the stochastic process, the unique solution of the above SDE understoof in the rough path sense is actually a Stratonovich solution. This condition is satisfied by Brownian motion and fractional Brownian motion with Hurst parameter greater than 1/4.
Nina Gantert (Universitaet Karlsruhe) Random walk in random scenery
Abstract: Let (Z_n)_{n in N_0} be a d-dimensional random walk in random scenery, i.e., Z_n=sum_{k=0}^{n-1}Y(S_k) with (S_k)_{k in N_0} a random walk in Z^d and (Y(z))_{z in Z^d} an i.i.d. scenery, independent of the walk. The walker's steps have mean zero and finite variance. We identify the speed and the rate of the logarithmic decay of P(1/n Z_n > b_n) for various choices of sequences (b_n)_n in [1,infty). Depending on (b_n)_n and the upper tails of the scenery, we identify different regimes for the speed of decay and different variational formulas for the rate functions. In contrast to recent work by A.~Asselah and F.~Castell, we consider sceneries unbounded to infinity. It turns out that there are interesting connections to large deviation properties of self-intersections of the walk, which have been studied recently by X. Chen. The talk is based on joint work with Wolfgang Koenig, Remco van der Hofstad and Zhan Shi.
Martin Hairer (University of Warwick) Stochastic modulation equations
Abstract: We consider the stochastic Swift-Hohenberg equation on a large domain near its change of stability. We show that, under the appropriate scaling, its solutions can be approximated by a periodic wave, which is modulated by the solutions to a stochastic Ginzburg-Landau equation. Unlike in the deterministic case, this approximation holds for all times and extends to the respective invariant measures.
Antal Jarai (Carleton University) Infinite volume limit of the Abelian sandpile model on Zd
Abstract: The Abelian 'sandpile' model was introduced by physicists as a basic example of self-organized criticality (SOC). Roughly speaking, SOC arises when a stochastic dynamics drives a system towards a stationary state characterized by power laws. We study existence of the infinite volume limit for the model, and properties of this limit, giving insight into the asymptotic behaviour of large 'sandpiles'. Most progress can be made above the upper critical dimension d > 4. We discuss some open problems related to extending these results to lower dimensions.
Richard Kenyon (University of British Columbia) Simple random surfaces
Abstract: This is joint work with David Brydges and Jessica Young. We study a model of random surfaces coming with an immersion into an arbitrary two-complex. Certain probabilistic quantities can be computed using the Green's function for the Laplacian on 1-forms.
Edward Keyes (Semiconductor Insights) (Team 4) Integrated Circuit Layout Reconstruction
Abstract: Integrated Circuits are designed using a polygon representations of the wiring and transistors layers known as "layout". Layout must conform to strict design rules. Typically the design rules describes the minimum width of any polygon, minimum spacing between adjacent polygons, directionality (normally only vertical or horizontal runs are allowed) and corner angles (normally only 90 degrees). Multiple wiring layers are common, with modern ICs having as many as ten wiring levels. Different wiring layers are connected through a contact or "via" level. The via levels must also obey their own set of design rules on size and spacing.

The process of analyzing the design of an integrated circuit involves imaging the various layers and then using image processing to reconstruct the layout of the different layers. Built-in biases, both in the manufacturing process and the analysis process prevent the reconstructed layout from being a faithful representation of the original layout. For example, sharp corners become rounded, line widths may either expand or contract and straight lines become roughened with many false vertices. Typical extracted layout is shown in figure 1.

Our problem is, given the raw polygon data from image processing, how can we as faithfully as possible recreate the original layout?

There are a number of potential errors that must be avoided in any reconstruction scheme including: creation of shorts between adjacent polygons, creation of a break or "open" in an existing polygon, creation of self intersecting polygons, creation of "via opens" (a break in the connection to an upper or lower layer).

The ideal algorithm should also significantly compaction the layout data by eliminating spurious vertices.

The layout reconstruction problem has significant overlap with the general problem of line simplification which has been extensively studied for Geographic Information Systems (GIS). One of the first and most effective methods for line simplification is the algorithm proposed by Douglas and Peucker[1] in 1973. A straightforward implementation of the algorithm runs in time O(k2) for a chain of size k; Hershberger and Snoeyink[2] show how to improve this to O(k log k). This algorithm is very efficient, however it is a general line simplification solution and not optimized to the highly specific characteristics of IC layout.

Unique features of our problem are the strict design rules governing permissible polygon shapes as well as the constraints imposed by the via points.

---------------------------

[1] DOUGLAS, D. H., AND PEUCKER, T. K. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. The Canadian Cartographer 10 (1973), 112-122.

[2] HERSHBERGER, J., AND SNOEYINK, J. Speeding up the Douglas-Peucker line simplification algorithm. Proc. 5th Internat. Sympos. Spatial Data Handling (1992), pp. 134-143.

Nicolai Krylov (University of Minnesota) On the foundation of the Lp-theory of SPDEs
Abstract: We discuss a detailed proof of a generalization of the Littlewood-Paley inequality upon which the Lp-theory of SPDEs is based.
Manuel Lladser (University of Colorado) A state machine approach to study pattern frequencies in Markovian sequences
Abstract: We present a general method to compute the distribution of the number of occurrences of various patterns in a random string produced by a Markov process in a finite size alphabet. The key idea to the method is the observation that the probability of occurrence of a single pattern in a random string of length N corresponds to the probability that a random walk on a state machine (also known as automaton) visits a terminal state within N steps. Through a synchronization argument the method can be extended to study the occurrence of none, some, or all of a list of patterns in a random string generated by a homogeneous Markov Process with a bounded amount of memory. Within this framework the use of generating functions and matrix methods are readily available to determine explicitly or asymptotically the probability of simultaneous occurrence of various patterns in a random string of arbitrary length.
Russell Lyons (Indiana University) Invited Lecture: Unimodularity and stochastic processes
Abstract: Stochastic processes on vertex-transitive graphs, especially Cayley graphs of groups, have been studied for 50 years (not counting the special case of integer lattices, which goes back hundreds of years). The assumption of invariance under graph automorphisms plays a key role, but investigations of the last 15 years have shown that an additional assumption is also extremely useful. This newer assumption is the property of unimodularity, which is equivalent to the Mass-Transport Principle. We shall review some well-known applications and also discuss recent work with David Aldous.
Terence Lyons (Oxford University) Invited Lecture: Rough paths: a top down description of controls
Abstract: The theory of rough paths as developed by the Author (and several others including those speaking at this workshop as well as others such as Hambly, Ledoux, Coutin, ..) aims to study the differential equations used to model the situation where a system responds to external control or forcing. The theory describes a robust approach to these equations that allows the forcing to be far from differentiable. The methodology permits the main probabilistic classes as well as many new types of stochastic forcing that do not fit into the classical semi-martingale setting directly. The key to this theory is to answer the question - when do two controls produce similar responses. This is also a core question for the problem for multi-scale analysis where one needs to summarise small scale behaviour in a way that large scale responses can be predicted from the summarised information. The question can be translated into one asking that one characterises the continuity properties of the It? map. This is indeed possible and the Universal Limit theorem proves the (uniform) continuity of the map taking the forcing control to response for a wide class of metrics on smooth paths - and the completions of the space under these metrics give the so called rough paths - giving insight into the control problem. The approach is quite structured, and allows one to give a top down analysis of a control in terms of a sequence of algebraic coefficients we call the signature of the control (which have similarity to a child's pr?cis of a complicated text by a simpler one and are a non-commutative analogue of Fourier coefficients) with refinements giving more accurate information about the control. Hambly and Lyons recently proved that this "signature" of a control completely characterises the control up to the appropriate null sets. The talk will summarise some of this work.
Jonathan C. Mattingly (Duke University) Ergodicity of the degenerately forced stochastic fluid equations
Abstract: I will present a theory which allows one to prove the uniqueness of the stationary measure for a large class of SPDEs with additive noise. To do so, I will discuss Malliavin Calculus in the SPDE setting and a generalization of Hormander's hypo-elliptic theory to the SPDEs. I will also discuss a new generalization of the strong Feller property which seems to be use full in infinite dimensions.
Peter Mueller (University of Goettingen) Spectral asymptotics of Laplacians on bond-percolation graphs
Abstract: Bond-percolation graphs are random subgraphs of the d-dimensional integer lattice generated by a standard Bernoulli bond-percolation process. The associated graph Laplacians, subject to Dirichlet or Neumann conditions at cluster boundaries, represent bounded, self-adjoint, ergodic random operators. They possess almost surely the non-random spectrum [0,4d] and a self-averaging integrated density of states. This integrated density of states is shown to exhibit Lifshits tails at both spectral edges in the non-percolating phase. Depending on the boundary condition and on the spectral edge, the Lifshits tail discriminates between different cluster geometries (linear clusters versus cube-like clusters) which contribute the dominating eigenvalues. Lifshits tails arising from cube-like clusters continue to show up above the percolation threshold. In contrast, the other type of Lifshits tails cannot be observed in the percolating phase any more because they are hidden by van Hove singularities from the percolating cluster.
Anastasia Papavasiliou (Princeton University) Applications of rough paths to speech recognition
Abstract: It is a well known fact that when someone speaks, the signal reaching the human ear is the original signal produced by the speaker and several delays. We think of this as a multidimensional rough path. Using tools coming from the theory of rough paths, I will construct much simpler rough paths (piecewise linear) approximating the one containing the speech signal and its delays, which still cause a similar response. Thus, the constructed rough paths contain all the information relevant to the response. If we think of the "meaning" of the speech signal as the response, the constructed rough paths will contain the "meaning" in a much more robust way than the signal itself, and thus can be used to construct a likelihood function for each word.
Zhongmin Qian (Oxford University) Stochastic integrals for processes with long-time memory
Abstract: Stochastic processes with long-time memory have been used extensively in modelling random phenomena. In this talk I will discuss the theory of rough paths and its application to a class of stochastic dynamical systems driven by such long-time memory.
David S. Ross (Kaiser Permanente) (Team 5) Models of Human Physiology, and Randomized Clinical Trials
Abstract: Randomized clinical trials are the central feature of modern medical methodology. In an RCT, two or more populations of patients who are statistically identical on the relevant dimensions are given different medical treatments. The results are then recorded, and are used to establish medical practice. The Archimedes Project of Kaiser Permanente has undertaken the development of a mathematical model of human physiology that will complement RCTs. The purpose of the model is to integrate data from various RCTs, then to predict health outcomes for populations not specifically considered in any particular RCT, perhaps for treatments not specifically considered in any particular RCT. What sort of model(s) of human physiology are appropriate for this purpose? References: Eddy, D., and Schlessinger, L.,Diabetes Care 26:3102-3110, 2003 Eddy, D., and Schlessinger, L.,Diabetes Care 26:3093-3101, 2003
Timo Seppalainen (University of Wisconsin) Spatial inhomogeneities and large scale behavior of the asymmetric exclusion process
Abstract: This talk describes some results and open problems for the one-dimensional asymmetric exclusion process in situations where spatial inhomogeneities, either deterministic or random, are added to the model.
Scott Sheffield (New York University) Tug of war and the infinity Laplacian
Abstract: The infinity Laplacian (informally, the "second derivative in the gradient direction") is a simple yet mysterious operator with many applications. "Tug of war" is a two player random turn game played as follows: SETUP: Assign each player one of two disjoint target sets T_1 and T_2 in the plane, and fix a starting position x and a constant epsilon. Place the game token at x. GAME PLAY: Toss a fair coin and allow the player who wins the coin toss to move the game token up to epsilon units in the direction of his or her choice. Repeat the above until the token reaches a target set T_i. The ith player is then declared the winner. Given parameters epsilon and x, write u_epsilon(x) for the probability that player one wins when both players play optimally. We show that as epsilon tends to zero, the functions u_epsilon(x) converge to the infinity harmonic function with boundary conditions 1 on T_1 and 0 on T_2. Our strategic analysis of tug of war leads to new formulations and significant generalizations of several classical results about infinity laplacians. The game theoretic arguments are simpler and more elementary than the original proofs. This talk is based on joint work with Yuval Peres, Oded Schramm, and David Wilson.
Vladas Sidoravicius (IMPA, Brazil) Growth in dynamic random environment
Abstract: We consider the following model for the spread of an infection: There is a "gas" of so-called A-particles, each of which performs a continuous time simple random walk on Z^d, with jumprate D_A. We assume that initially the number of A-particles at x is independent, mean mu_A Poisson distribution. In addition, there are B-particles which perform continuous time simple random walks with jumprate D_B. Initially we start with only one B-particle in the system, located at the origin. The B-particles move independently of each other, and the only interaction is that when a B-particle and an A-particle coincide, the latter instantaneously turns into a B-particle. For different values of the parameters D_A and D_B one obtains several interesting evolutions, raging from stochastic sandpile type dynamics (activated random walkers) to contact process like evolution and DLA-type growth. The difficult aspect of all these models is the absence of useful subadditive quantities. I briefly discuss these models before going to our main results: Consider the set C(t):= {x in Z^d: a B-particle visits x during [0,t]}. If D_A=D_B, then B(t) := C(t) + [- 1/2, 1/2]^d grows linearly in time with an asymptotic shape, i.e., there exists a non-random set B_0 such that (1/t)B(t) \to B_0, in a sense which will be made precise. Moreover, if the "recuperation'' transition form A to B occurs at the rate lambda>0, for each particle independently, then we show that there is a phase transition between survival and extiction of B particles. I also briefly present the key ideas of the proof. The talk is based on joint works with H. Kesten.
Chai Wah Wu (IBM Corporation) (Team 6) Algorithms for Digital Halftoning
Abstract: If you have ever looked closely at an image in a magazine or a newspaper, you will see that the image, which looks like it has many shades and colors, is actually composed of dots of ink of only a handful of colors. Digital halftoning is the art of representing a full color picture with only a few colors and is necessary in all digital printers. Halftoning is possible due to the low-pass frequency characteristic of the human visual system. Several types of algorithms exist in modern digital printers with usually a tradeoff between speed and quality. This tradeoff is important since digital printers can operate at speeds of a few pages a minute (an inkjet printer for home use) to thousands of pages a minute (a production class digital printer). This project studies some questions regarding the stability and efficiency of algorithms used to perform digital halftoning. One of the goals of this project is to design an algorithm which has superior output quality, yet operates at speeds close to speedier algorithms. The type of mathematics used include linear algebra, dynamical systems theory, convex analysis, and mathematical programming.

Ofer Zeitouni (University of Minnesota) Medallion Lecture: Recent results and open problems concerning motion in random media
Abstract: The talk will describe the current knowledge and some of the challenges in the study of motion in random environment, focusing on the model of random walk in random environment and the related model of diffusions in random environments. For the latter, I will describe a CLT in the case where the environment is a small perturbation of the constant environment.
Visitors in Residence
Henry De-Graft Acquah University of Gottingen 8/4/2005 - 8/6/2005
Ken Alexander University of Southern California 8/4/2005 - 8/6/2005
Ismail Ali Kuwait University 8/4/2005 - 8/6/2005
Mina Aminghafari Universite Paris-Sud 8/4/2005 - 8/6/2005
D. Gregory Arnold Air Force Research Laboratory 7/31/2005 - 8/10/2005
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
Marton Balazs University of Wisconsin–Madison 8/4/2005 - 8/6/2005
Antar Bandyopadhyay Chalmers University of Technology–Sweden 8/1/2005 - 8/6/2005
Katherine Bartley University of Nebraska–Lincoln 7/31/2005 - 8/10/2005
John Baxter University of Minnesota 8/14/2005 - 8/26/2005
Christian Benes Tufts University 8/4/2005 - 8/6/2005
Nicholas Bennett Schlumberger-Doll Research 7/31/2005 - 8/10/2005
Noam Berger California Institute of Technology 8/4/2005 - 8/6/2005
Ian Besse University of Iowa 7/31/2005 - 8/10/2005
Sagar Bhatt Rice University 7/31/2005 - 8/10/2005
Debasis Bhattacharya Visva-Bharati University 8/4/2005 - 8/6/2005
Animikh Biswas University of North Carolina–Charlotte 8/14/2005 - 8/26/2005
Henry A. Boateng University of Michigan 7/31/2005 - 8/10/2005
Petra Bonfert-Taylor Wesleyan University 8/14/2005 - 8/26/2005
Maury Bramson University of Minnesota 8/5/2005 - 8/6/2005
Richard J. Braun University of Delaware 7/31/2005 - 8/10/2005
Wlodzimierz Bryc University of Cincinnati 8/4/2005 - 8/7/2005
Patrick R. Campbell Los Alamos National Laboratory 7/31/2005 - 8/11/2005
Suneal K. Chaudhary University of Utah 8/14/2005 - 8/25/2005
Pengwen Chen University of Florida 7/31/2005 - 8/11/2005
Qianyong Chen University of Minnesota 9/1/2004 - 8/31/2006
William W. Chen Internal Revenue Service 8/4/2005 - 8/6/2005
Tsung-Lin Cheng National Changhua University of Education 8/4/2005 - 8/6/2005
Zhiyi Chi University of Chicago 8/4/2005 - 8/6/2005
Julianne Chung Emory University 7/31/2005 - 8/10/2005
Keith Crank National Science Foundation 8/4/2005 - 8/6/2005
Michael Cranston University of California–Irvine 8/4/2005 - 8/6/2005
Shilpa Das Gupta Mississippi State University 7/31/2005 - 8/10/2005
Amir Dembo Stanford University 8/4/2005 - 8/6/2005
Lee Dicker University of Pennsylvania 8/4/2005 - 8/6/2005
Brian DiDonna University of Minnesota 9/1/2004 - 8/31/2006
Jintai Ding University of Cincinnati 8/14/2005 - 8/26/2005
John Rhodes Dixon Florida State University 8/14/2005 - 8/26/2005
John Dodson American Express Financial Advisors 8/4/2005 - 8/6/2005
Hongjie Dong University of Minnesota 8/4/2005 - 8/6/2005
Vanja Dukic University of Chicago 8/4/2005 - 8/6/2005
Valjean Elander University of Nevada–Las Vegas 7/31/2005 - 8/10/2005
Malena Espanol Tufts University 7/31/2005 - 8/10/2005
Qirong Fang Purdue University 7/31/2005 - 8/10/2005
Lara Faoro Rutgers University 8/14/2005 - 8/26/2005
Petri Fast Lawrence Livermore National Laboratories 7/31/2005 - 8/10/2005
Harshini Fernando Texas Tech University 7/31/2005 - 8/10/2005
Bert Fristedt University of Minnesota 8/4/2005 - 8/6/2005
Peter Friz Courant Institute 8/4/2005 - 8/6/2005
Nina Gantert Universitaet Karlsruhe 8/2/2005 - 8/8/2005
Ryan Gantner University of Minnesota 8/4/2005 - 8/6/2005
Tim Garoni University of Minnesota 8/25/2003 - 8/31/2005
Tim Garoni University of Minnesota 8/4/2005 - 8/6/2005
Paul Garrett University of Minnesota 8/14/2005 - 8/26/2005
Armenak Gasparyan Program Systems Institute of RAS 8/4/2005 - 8/6/2005
Jason Gower University of Cincinnati 8/14/2005 - 8/26/2005
Lawrence Gray University of Minnesota 8/4/2005 - 8/6/2005
Arindam Gupta University of Calcutta 8/4/2005 - 8/6/2005
Jooyoung Hahn KAIST 8/15/2005 - 7/31/2006
Martin Hairer University of Warwick 8/4/2005 - 8/6/2005
Sean Han University of Minnesota 8/4/2005 - 8/6/2005
Michael Hardy University of Minnesota 8/4/2005 - 8/6/2005
John Harlim University of Maryland 7/31/2005 - 8/10/2005
James Hegeman University of Wisconsin 8/2/2005 - 8/6/2005
Alfa Heryudono University of Delaware 7/31/2005 - 8/10/2005
Wenming Hong Beijing Normal University 8/4/2005 - 8/6/2005
Mark Huber Duke University 8/4/2005 - 8/6/2005
Lucky Igbinosun University of Benin 8/4/2005 - 8/6/2005
Mark Iwen University of Michigan 7/31/2005 - 8/10/2005
Naresh Jain University of Minnesota 8/4/2005 - 8/6/2005
Antal Jarai Carleton University 8/4/2005 - 8/6/2005
Jan Jelinek Honeywell 8/4/2005 - 8/6/2005
Lijian Jiang Texas A & M University 7/31/2005 - 8/11/2005
Chao Jin University of Colorado–Boulder 7/31/2005 - 8/11/2005
Yasong Jin University of Kansas 8/4/2005 - 8/6/2005
Sookyung Joo University of Minnesota 9/1/2004 - 8/31/2006
Palle E. T. Jorgensen University of Iowa 8/14/2005 - 8/26/2005
Hye Won Kang University of Wisconsin 8/4/2005 - 8/6/2005
Soyoung Kang Purdue University 8/4/2005 - 8/6/2005
Chiu Yen Kao University of Minnesota 9/1/2004 - 8/31/2006
Belaide Karima Abderahmane Mira University 8/4/2005 - 8/6/2005
Richard Kenyon University of British Columbia 8/4/2005 - 8/6/2005
Edward Keyes Semiconductor Insights 7/31/2005 - 8/10/2005
Mercedeh Khajavikhan University of Minnesota 8/4/2005 - 8/6/2005
Asha Khanna Indian Institute of Forest Management 8/4/2005 - 8/6/2005
Jong-Min Kim University of Minnesota–Morris 8/4/2005 - 8/6/2005
Kyeong-Hun Kim University of Utah 8/4/2005 - 8/6/2005
Alexei Kitaev California Institute of Technology 8/14/2005 - 8/26/2005
Richard Kollar University of Minnesota 9/1/2004 - 8/31/2005
George Kordzakhia University of California–Berkeley 8/4/2005 - 8/6/2005
Elena Kosygina Baruch College–The City University of New York 8/4/2005 - 8/6/2005
Nicolai Krylov University of Minnesota 8/4/2005 - 8/6/2005
Saji Kumar University of Kerala 8/4/2005 - 8/6/2005
Thomas G. Kurtz University of Wisconsin 8/4/2005 - 8/6/2005
Matthias Kurzke University of Minnesota 9/1/2004 - 8/31/2006
Song-Hwa Kwon University of Minnesota 8/30/2005 - 8/31/2007
Soumendra Nath Lahiri Iowa State University 8/14/2005 - 8/26/2005
Chang Hyeong Lee University of Minnesota 8/4/2005 - 8/6/2005
Chang-Ock Lee KAIST 8/1/2005 - 7/31/2006
Frederic Legoll University of Minnesota 9/3/2004 - 8/1/2005
Melvin Leok University of Michigan 8/14/2005 - 8/26/2005
Joel Lepak University of Michigan 7/31/2005 - 8/10/2005
Debra Lewis University of Minnesota 7/15/2004 - 8/31/2006
Xiantao Li University of Minnesota 8/3/2004 - 8/14/2005
Yan Li Texas A & M University 7/31/2005 - 8/11/2005
Hstau Liao University of Minnesota 8/30/2005 - 8/31/2007
Chjan Chin Lim Rensselaer Polytechnic Institute 8/14/2005 - 8/26/2005
Enbing Lin University of Toledo 8/14/2005 - 8/26/2005
Manuel Lladser University of Colorado 8/4/2005 - 8/6/2005
Russell Lyons Indiana University 8/4/2005 - 8/7/2005
Terence Lyons Oxford University 8/2/2005 - 8/7/2005
Jonathan C. Mattingly Duke University 8/4/2005 - 8/6/2005
Elebeoba E. May Sandia National Laboratories 8/14/2005 - 8/26/2005
David Meintrup University of the Federal Arms Munich 8/14/2005 - 8/27/2005
Michael J. Minardi Air Force Research Laboratory 7/31/2005 - 8/1/2005
Oana Mocioalca Kent State University 8/4/2005 - 8/7/2005
Adel Mohammadpour Universite Paris-Sud 8/3/2005 - 8/6/2005
Peter Mueller University of Goettingen 8/4/2005 - 8/6/2005
Abdallah Muwanga Swaziland Government 8/4/2005 - 8/6/2005
Kiran Naidu Air Force Research Laboratory 7/31/2005 - 8/2/2005
Jayoung Nam Indiana University 7/31/2005 - 8/10/2005
Subhrangshu Nandi University of Massachusetts–Amherst 8/4/2005 - 8/6/2005
Claudia Neuhauser University of Minnesota 8/4/2005 - 8/6/2005
Mahdi Nezafat University of Minnesota 8/4/2005 - 8/6/2005
Kwadwo Agyei Nyantakyi 8/4/2005 - 8/6/2005
Frank Oduro Graphic Communications Group Limited 8/4/2005 - 8/6/2005
Tamer Oraby University of Cincinnati 8/4/2005 - 8/7/2005
Anastasia Papavasiliou Princeton University 8/4/2005 - 8/6/2005
Jonathon Peterson University of Minnesota 8/4/2005 - 8/6/2005
Peter Philip University of Minnesota 8/22/2004 - 8/31/2006
Oleg Pikhurko Carnegie Mellon University 8/14/2005 - 8/25/2005
Lea Popovic University of Minnesota 9/2/2003 - 8/19/2005
Lea Popovic University of Minnesota 8/4/2005 - 8/6/2005
Karel L. Prikry University of Minnesota 8/14/2005 - 8/26/2005
Zhongmin Qian Oxford University 8/4/2005 - 8/6/2005
Maurice Rahe Texas A & M University 8/14/2005 - 8/26/2005
Jorge M. Ramirez Oregon State University 7/31/2005 - 8/11/2005
Gregory Jason Randall Universidad de la Republica 8/10/2005 - 7/31/2006
Arni SR Srinivasa Rao University of Guelph 8/4/2005 - 8/6/2005
Firas Rassoul-Agha Ohio State University 8/4/2005 - 8/6/2005
S. S. Ravindran University of Alabama–Huntsville 8/14/2005 - 8/26/2005
Fernando Reitich University of Minnesota 8/1/2005 - 8/10/2005
Alexander Roitershtein University of British Columbia 8/4/2005 - 8/6/2005
Robert Ronkese University of Delaware 7/31/2005 - 8/11/2005
David S. Ross Kaiser Permanente 7/31/2005 - 8/10/2005
John Sabino Rice University 7/31/2005 - 8/10/2005
Rina Santos University of Nevada–Las Vegas 7/31/2005 - 8/10/2005
Fadil Santosa University of Minnesota 8/1/2005 - 8/10/2005
Arnd Scheel University of Minnesota 7/15/2004 - 8/31/2006
Clyde Schoolfield University of Florida 8/4/2005 - 8/6/2005
Timo Seppalainen University of Wisconsin 8/2/2005 - 8/6/2005
Lee Seung Ohio State University 8/4/2005 - 8/6/2005
Qi-Man Shao Hong Kong University of Science and Technology 8/4/2005 - 8/6/2005
Tanush Shaska University of Idaho 8/14/2005 - 8/26/2005
Scott Sheffield New York University 8/4/2005 - 8/6/2005
Peter W. Shor Massachusetts Institute of Technology 8/14/2005 - 8/26/2005
Vladas Sidoravicius IMPA, Brazil 8/4/2005 - 8/6/2005
Warren Sinnott Ohio State University 8/14/2005 - 8/26/2005
Kai-Sheng Song Florida State University 8/14/2005 - 8/26/2005
Qingshuo Song Wayne State University 7/31/2005 - 8/10/2005
Skyler Speakman University of Kentucky 7/31/2005 - 8/11/2005
David Steinsaltz Queen's University 8/4/2005 - 8/6/2005
David St John University of Illinois–Chicago 7/31/2005 - 8/10/2005
Jason Swanson University of Wisconsin 8/4/2005 - 8/6/2005
Tzyh-Jong Tarn Washington University 8/14/2005 - 8/26/2005
David Tello Arizona State University 7/31/2005 - 8/10/2005
Pham Huu Tiep University of Florida 8/14/2005 - 8/26/2005
Igor Tsukerman University of Akron 8/15/2005 - 8/26/2005
Imre Tuba Virginia Tech 8/15/2005 - 8/26/2005
Abolfazl Vaghefi Iran University of Science & Technology 8/4/2005 - 8/6/2005
Paula Andrea Vasquez University of Delaware 7/31/2005 - 8/10/2005
John Verzani College of Staten Island–The City University of New York 8/4/2005 - 8/6/2005
Andrew Vizcarra Purdue University 8/4/2005 - 8/6/2005
Shuyan Wan Ohio State University 8/4/2005 - 8/6/2005
Lei Wang University of Michigan 7/31/2005 - 8/10/2005
Thomas Williams Mississippi State University 7/31/2005 - 8/11/2005
Doug Wright University of Minnesota 2/15/2005 - 8/31/2005
Chai Wah Wu IBM Corporation 7/31/2005 - 8/10/2005
Chuan Xue University of Minnesota 7/31/2005 - 8/10/2005
Emmanuel Yomba University of Ngaoundéré 10/6/2004 - 8/31/2005
Ofer Zeitouni University of Minnesota 8/4/2005 - 8/6/2005
Yong Zeng University of Missouri–Kansas City 8/4/2005 - 8/6/2005
Martin Zerner University of Tuebingen 8/4/2005 - 8/6/2005
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, Salo IT Solutions, Inc., 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, Medtronic, Inc., Motorola, Schlumberger-Doll Research, Siemens, Telcordia Technologies