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IMA Newsletter #370

August 2007

News and Notes

The University of Tennessee joins the IMA

The University of Tennessee has joined the IMA as a Participating Institution. The University of Tennessee's representative on the Participating Institutions Council is Michael Frazier, the head of the Department of Mathematics.

IMA Events

PI Summer Graduate Program

Applicable Algebraic Geometry

July 23 - August 10, 2007

Organizers: Laura Felicia Matusevich (Texas A & M University), Frank Sottile (Texas A & M University), Thorsten Theobald (Johann Wolfgang Goethe-Universität Frankfurt)

Classical and Quantum Approaches in Molecular Modeling

July 23 - August 3, 2007

Organizers: Eric Cances (CERMICS), Giovanni Ciccotti (Università di Roma "La Sapienza"), Benedict Leimkuhler (University of Edinburgh), Nicola Marzari (Massachusetts Institute of Technology), Yousef Saad (University of Minnesota Twin Cities), Gustavo E. Scuseria (Rice University), Robert D. Skeel (Purdue University), Mark E. Tuckerman (New York University)

Mathematical Modeling in Industry XI - A Workshop for Graduate Students

August 8-17, 2007

Organizers: Richard J. Braun (University of Delaware), Fernando Reitich (University of Minnesota Twin Cities), Arnd Scheel (University of Minnesota Twin Cities)
Schedule

Wednesday, August 1

8:30a-9:00aCoffeeEE/CS 3-176 SP7.23-8.3.07
9:00a-10:00aReal space pseudopotentials applied to nanoscale systemsJames R. Chelikowsky (University of Texas)EE/CS 3-180 SP7.23-8.3.07
10:00a-10:15aCoffeeEE/CS 3-176 SP7.23-8.3.07
10:15a-11:15aDensity-functional theory and its generalizations: legendre transform, constrained search, open problemsPaul W. Ayers (McMaster University)EE/CS 3-180 SP7.23-8.3.07
11:15a-11:30aCoffeeEE/CS 3-176 SP7.23-8.3.07
11:30a-12:00pTBAMatt Challacombe (Los Alamos National Laboratory)EE/CS 3-180 SP7.23-8.3.07
12:00p-12:30pNovel materials for quantum computingNicholas M. Harrison (Imperial College London)EE/CS 3-180 SP7.23-8.3.07
12:30p-2:30aLunch SP7.23-8.3.07
2:30p-3:00pTheoretical description of electrons in single molecule magnetsErnest R. Davidson (University of Washington)EE/CS 3-180 SP7.23-8.3.07
3:00p-4:00pA consistent, linear-response approach to LDA+U Matteo Cococcioni (University of Minnesota Twin Cities)EE/CS 3-180 SP7.23-8.3.07
4:00p-4:30pReal-space finite difference method for O(N) first-principles molecular dynamics with plane waves accuracyJean-Luc Fattebert (Lawrence Livermore National Laboratory)EE/CS 3-180 SP7.23-8.3.07
4:30p-4:45pGroup Photo SP7.23-8.3.07
4:45p-6:15pPoster SessionLind Hall 400 SP7.23-8.3.07
Molecular modelling the structure and dynamics of alginate oligosaccharidesHoda Abdel-Aal Bettley (University of Manchester)
Method for determination of Hubbard model phase diagram from optical lattice experiments by two parameter scalingVivaldo L. Campo (University of Minnesota Twin Cities)
Real-space corrections for electrostatic interactions in periodic boundary conditionsIsmaila Dabo (Massachusetts Institute of Technology)
Objective structures and their applicationsKaushik Dayal (University of Minnesota Twin Cities)
Modelling of local defects in crystalsAmélie Deleurence (École Nationale des Ponts-et-Chaussées (ENPC))
A systematic method to explore possible silicon tip structures used in AFMSeyed-Alireza Ghasemi (Universität Basel)
Conformational reinvestigation of two cyclic pentapeptides: to a generic approach in drug developmentPieter Hendrickx (University of Ghent (UG))
An ab initio molecular dynamics simulation of solid CL-20: mechanism and kinetics of thermal decompositionOlexandr Isayev (Jackson State University)
Numerical method for solving stochastic differential equations with non-Gaussian noiseChangho Kim (Korea Advanced Institute of Science and Technology (KAIST))
Particle-Scaling function (P3S) algorithm for electrostatic problems in free boundary conditionsAlexey Neelov (Universität Basel)
A Bell-Evans-Polanyi principle for molecular dynamics trajectories and its implications for global optimizationShantanu Roy (Universität Basel)
Uniqueness of the density-to-potential mapping in excited-state density-functional theoryPrasanjit Samal (University of Minnesota Twin Cities)
Local exchange potentials: A mathematical viewpointGabriel Stoltz (École Nationale des Ponts-et-Chaussées (ENPC))
Precision problems in density functional development for better molecular modelingMichael Teter (Cornell University)
Mesoscopic model for the fluctuating hydrodynamics of binary and ternary mixturesErkan Tüzel (North Dakota State University)
New numerical algorithms and software for minimizing biomolecular potential energy functionsDexuan Xie (University of Wisconsin)

Thursday, August 2

8:30a-9:00aCoffeeEE/CS 3-176 SP7.23-8.3.07
9:00a-10:00aWavelets for electronic structure calculations and electrostatic problemsStefan Goedecker (Universität Basel)EE/CS 3-180 SP7.23-8.3.07
10:00a-10:15aCoffeeEE/CS 3-176 SP7.23-8.3.07
10:15a-11:15aExchange and correlation in electronic systems: the hole story Axel D. Becke (Dalhousie University)EE/CS 3-180 SP7.23-8.3.07
11:15a-11:30aCoffeeEE/CS 3-176 SP7.23-8.3.07
11:30a-12:00pEfficient Kohn-Sham density functional calculations using the Gaussian and plane waves approachJürg Hutter (Universität Zürich)EE/CS 3-180 SP7.23-8.3.07
12:00p-12:30pVan der Waals interactions in density functional theoryDavid Langreth (Rutgers University)EE/CS 3-180 SP7.23-8.3.07
12:30p-2:30pLunch SP7.23-8.3.07
2:30p-3:00pLinear-scaling density-functional calculations with plane-wavesArash A. Mostofi (University of Cambridge)EE/CS 3-180 SP7.23-8.3.07
3:00p-3:30pA Linear-scaling AO-based MP2 method for large molecules by rigorous integral estimatesChristian Ochsenfeld (Eberhard-Karls-Universität Tübingen)EE/CS 3-180 SP7.23-8.3.07
3:30p-4:00pCoffeeEE/CS 3-176 SP7.23-8.3.07
4:00p-5:30pSecond Chances session on fast algorithms EE/CS 3-180 SP7.23-8.3.07
6:30p-8:30pGroup dinner at Caspian BistroCaspian Bistro 2418 University Ave SE Minneapolis, MN 55414
(612) 623-1113
SP7.23-8.3.07

Friday, August 3

8:30a-9:00aCoffeeEE/CS 3-176 SP7.23-8.3.07
9:00a-9:30aDealing with spatial regions Andreas Savin (Université de Paris VI (Pierre et Marie Curie))EE/CS 3-180 SP7.23-8.3.07
9:30a-10:00aKohn-Sham methods for implicit density functionalsViktor N. Staroverov (University of Western Ontario)EE/CS 3-180 SP7.23-8.3.07
10:00a-10:30aQM/MM studies on enzymesWalter Thiel ( Max-Planck-Institut für Kohlenforschung)EE/CS 3-180 SP7.23-8.3.07
10:30a-11:00aCoffeeEE/CS 3-176 SP7.23-8.3.07
11:00a-11:30aNew density functionals: a meta GGA and three hybrid meta GGAs with good performance for thermochemistry, thermochemical kinetics, noncovalent interactions, and spectroscopy Donald G. Truhlar (University of Minnesota Twin Cities)EE/CS 3-180 SP7.23-8.3.07
11:30a-12:00pOrbital-Corrected Orbital-Free density functional theoryYan Alexander Wang (University of British Columbia)EE/CS 3-180 SP7.23-8.3.07
12:00p-12:30pMaterials at ultra-high PTs: the coming of age of planetary materials theoryRenata Wentzcovitch (University of Minnesota Twin Cities)EE/CS 3-180 SP7.23-8.3.07
12:30p-2:30aLunch SP7.23-8.3.07
2:30p-3:00pOrbital-free embedding potential: properties, approximations, and the use in computer simulations to couple quantum chemical and classical levels of descriptionTomasz A. Wesolowski (Université de Genève)EE/CS 3-176 SP7.23-8.3.07
3:00p-4:30pSecond Chances session on DFT EE/CS 3-180 SP7.23-8.3.07

Wednesday, August 8

All DayWorkshop Outline: Posing of problems by the 6 industry mentors. Half-hour introductory talks in the morning followed by a welcoming lunch. In the afternoon, the teams work with the mentors. The goal at the end of the day is to get the students to start working on the projects.EE/CS 3-180 MM8.8-17.07
9:00a-9:30aCoffee and RegistrationEE/CS 3-176 MM8.8-17.07
9:30a-9:40aWelcome and IntroductionDouglas N. Arnold (University of Minnesota Twin Cities)
Richard J. Braun (University of Delaware)
Fernando Reitich (University of Minnesota Twin Cities)
Arnd Scheel (University of Minnesota Twin Cities)
EE/CS 3-180 MM8.8-17.07
9:40a-10:00aTeam 1: Supersonic designNatalia Alexandrov (NASA Langley Research Center)EE/CS 3-180 MM8.8-17.07
10:00a-10:20aTeam 2: 802.11 WLAN MAC layer modelingRadu V. Balan (Siemens Corporate Research, Inc.)EE/CS 3-180 MM8.8-17.07
10:20a-10:40aTeam 3: Associating earth-orbiting objects detected by astronomical telescopesGary B. Green (The Aerospace Corporation)EE/CS 3-180 MM8.8-17.07
10:40a-11:00aBreakEE/CS 3-176 MM8.8-17.07
11:00a-11:20aTeam 4: High dimensional, nonlinear, non-convex optimization problems in the area of aircraft and vehicle designJohn R. Hoffman (Lockheed Martin Missiles and Space Company, Inc.)EE/CS 3-180 MM8.8-17.07
11:20a-11:40aTeam 5: Size and shape comparisons from noisy, unlabeled, incomplete configurations of landmarks in three-dimensional spaceMark A. Stuff (General Dynamics Advanced Information Systems)EE/CS 3-180 MM8.8-17.07
11:40a-12:00pTeam 6: Wavelength assignment and conversion in optical networkingLisa Zhang (Lucent Technologies Bell Laboratories)EE/CS 3-180 MM8.8-17.07
12:00p-1:30pLunchLind Hall 400 MM8.8-17.07
1:30p-4:30pafternoon - start work on projectsBreak-out Rooms MM8.8-17.07

Thursday, August 9

All DayStudents work on the projects. Mentors guide their groups through the modeling process, leading discussion sessions, suggesting references, and assigning work.Break-out Rooms MM8.8-17.07

Friday, August 10

All DayStudents work on the projects. Mentors guide their groups through the modeling process, leading discussion sessions, suggesting references, and assigning work.Break-out Rooms MM8.8-17.07

Saturday, August 11

All DayStudents and mentors work on the projects.Break-out Rooms MM8.8-17.07

Sunday, August 12

All DayStudents and mentors work on the projects.Break-out Rooms MM8.8-17.07

Monday, August 13

9:30a-9:50aTeam 6 Progress ReportEE/CS 3-180 MM8.8-17.07
9:50a-10:00aTeam 3 Progress ReportEE/CS 3-180 MM8.8-17.07
10:10a-10:30aTeam 2 Progress ReportEE/CS 3-180 MM8.8-17.07
10:30a-11:00aBreakEE/CS 3-176 MM8.8-17.07
11:00a-11:20aTeam 4 Progress ReportEE/CS 3-180 MM8.8-17.07
11:20a-11:40aTeam 5 Progress ReportEE/CS 3-180 MM8.8-17.07
11:40a-12:00pTeam 1 Progress ReportEE/CS 3-180 MM8.8-17.07
12:00p-2:00pPicnicUofM East River Flats Park MM8.8-17.07

Tuesday, August 14

All DayStudents and mentors work on the projects.Breakout Rooms MM8.8-17.07

Wednesday, August 15

All DayStudents and mentors work on the projects.Breakout Rooms MM8.8-17.07

Thursday, August 16

All DayStudents and mentors work on the projects.Breakout Rooms MM8.8-17.07

Friday, August 17

9:00a-9:30aTeam 5 Final ReportEE/CS 3-180 MM8.8-17.07
9:30a-10:00aTeam 1 Final ReportEE/CS 3-180 MM8.8-17.07
10:00a-10:30aTeam 4 Final ReportEE/CS 3-180 MM8.8-17.07
10:30a-11:00aBreakEE/CS 3-176 MM8.8-17.07
11:00a-11:30aTeam 2 Final ReportEE/CS 3-180 MM8.8-17.07
11:30a-12:00pTeam 6 Final ReportEE/CS 3-180 MM8.8-17.07
12:00p-12:30pTeam 3 Final ReportEE/CS 3-180 MM8.8-17.07
12:30p-2:00pPizza partyLind Hall 400 MM8.8-17.07
Abstracts
Hoda Abdel-Aal Bettley (University of Manchester) Molecular modelling the structure and dynamics of alginate oligosaccharides
Abstract: Same abstract as the 7/24 poster session.
Natalia Alexandrov (NASA Langley Research Center) Team 1: Supersonic design
Abstract: Designing affordable, efficient, quiet supersonic passenger aircraft has been under investigation for many years. Obstacles to designing such aircraft are also many, both in fundamental physics and in computational science and engineering. The problem of design is multidisciplinary in its nature and the goals of the constituent disciplines that govern the behavior of an aircraft are often at odds. In particular, aircraft that yields low sonic boom may not be attractive aerodynamically, while aerodynamically optimized aircraft may produce unacceptable sonic boom. One of the essential difficulties in using direct optimization methods to design for low boom and low drag is in modeling the design problem. For instance, it is not clear what objective functions to use.

Some Early Boom Shaping Developments (Ferri, 1969)

This project will use simple aerodynamic and sonic boom models to examine modeling of the design problem itself. We will attempt to establish a meaningful direct functional dependence between the shape of the aircraft and aerodynamic and noise quantities of interest by studying the sensitivity of these quantities to changes in shape. We will experiment with several direct multiobjective optimization problem formulations. References:

  1. Seebass, R., Argrow, B.; "Sonic Boom Minimization Revisited", AIAA Paper 98-2956
  2. Shepherd, K.P., Sullivan, B.M.; "A Loudness Calculation Procedure Applied to Shaped Sonic Booms", NASA Technical Paper 3134, 1991
  3. Carlson, H.W., Maglieri, D.J.; "Review of Sonic Boom Generation Theory and Prediction Methods", J. Acoust. Soc. Amer., 51, pp. 675-685 (1972)
  4. Alonso, J.J., Kroo, I.M., Jameson, A. "Advanced Algorithms for Design and Optimization of Quiet Supersonic Platform", 40th AIAA Aerospace Sciences Meeting and Exhibit, AIAA Paper 2002-0144, Reno, NV, January 2002
  5. Raymer, D.P.; "Aircraft Design: a Conceptual Approach", Third Edition, AIAA, 1999

Prerequisites:

Required: Scientific computing skills (Matlab or Fortran 90/95 or C), 1 semester in nonlinear optimization

Desired: Some background in statistical modeling, numerical analysis, multiobjective optimization

Keywords: multidisciplinary optimization, supersonic design, low boom, aerodynamic optimization

Paul W. Ayers (McMaster University) Density-functional theory and its generalizations: legendre transform, constrained search, open problems
Abstract: The quantum many-electron problem is easy in principle (solve the N-electron Schrödinger equation) and hard in practice (because the cost of numerical methods typically grows exponentially with the number of variables). However, there are simplifying features. First, the dimensionality can be reduced because electronic Hamiltonians contain only 1-body and 2-body terms. (This leads to reduced density-matrix methods.) Second, the dimensionality can be reduced because electrons are identical particles: if you know everything about one electron, then you know everything about all of the electrons. (This leads to electron-propagator theory and density-functional theory.) There is a “catch.” Reducing the number of dimensions leads to other problems associated with approximating the energy functional and/or associated with restricting the domain of the variational procedure. Two powerful techniques for resolving these difficulties are the Legendre transform and constrained-search formulations of density functional theory. This talk will discuss these formulations, and show how they can be extended to define "generalized" density-functional theories. I'll conclude with some of my favorite open problems in density-functional theory.
Radu V. Balan (Siemens Corporate Research, Inc.) Team 2: 802.11 WLAN MAC layer modeling
Abstract: 802.11 Wireless Local Area Networks (WLANs) have become as ubiquitous as Internet access for personal computers. The basic unit of a WLAN is composed of one Access Point (AP), and several mobile stations (STAs), all forming a Basic Service Set (BSS). A typical WLAN setup is depicted in Figure 1.

Figure 1: A typical Basic Service Set (BSS), with one AP, and several mobile stations.

The IEEE Standard governing WLANs describes two modes of operation: Distributed Coordination Function (DCF), and Point Coordination Function (PCF). By and large, chipset manufacturers implement only the DCF mode, and compatibility testing is done for this mode exclusively. The DCF is a contention-based mechanism where each wireless device (AP, or STA) competes for air time. More specifically, the 802.11 standard is implemented as follows:

  1. At regular intervals (typically hundreds of ms) the AP broadcasts a beacon signal, which resets all devices internal clocks;
  2. Assume a transmission opportunity ended at time t0. Depending on the status of the internal Backoff counter (BCK) of the device, the following actions can take place:
    • If BCKr=0, and there is no activity on air for DIFS (Distributed Inter Frame Spacing = 50us in 802.11b) time, then station starts transmitting its data packet;
    • If BCK=0 and during the DIFS period there is activity on air then device generates a random BCK between 0 and CW-1 (initially CW=CWmin = 16, in 802.11b); Then the following rules apply:
      • For each slot time (Ts) of medium inactivity, the BCK decrements;
      • The countdown is stopped whenever medium is busy, and the the countdown is resumed only after a supplemental AIFS (Arbitration Inter Frame Spacing, =DIFS in 802.11b) wait;
      • When BCK reaches 0, the device transmits its packet data;
      • If receiver (AP, or STA) receives successfully the packet, then it sends back on the air an Acknowledgement (ACK) frame, after a SIFT (Short Inter Frame Spacing = 10us) period after transmitter finishes its transmission;
      • If transmitter receives the ACK correctly, then it assumes data was received correctly, and transmission ends; On the other hand, if ACK is not broadcast, or the transmitter does not receive correctly the ACK, then it assumes the transmission was not successful, and the following rules apply:
        1. If current number of retransmissions has not reached a max threshold, then increment the Number of Retransmissions counter
        2. If CW<= CWmax, then CW doubles;
        3. A new random BCK is generated between 0 and CW-1;
        4. Transmission process is restarted from step b. above
    • When transmission ends, a post-backoff mechanism is implemented, by which a random BCK between 0 and CWmin-1 is generated, and a virtual countdown process is started obeying b.i and b.ii above.
These (somewhat simplified) rules govern the behavior of 802.11 devices. A big challenge in WLAN research is in modeling such a system. The purpose of this research group is to advance the current state-of-the-art model to allow for effective network control algorithm design.

Description of the problem

Basically there are two distinct regimes, completely opposite from one another:

  1. Deterministic Regime: when no collision happen, and the initial MAC instance time are sufficiently far apart, then transmission happens in a deterministic mode. Such a case may happen when only voice data (such as VoIP stations are connected to the AP), or periodic transmitting stations are present. The deterministic regime analysis gives an upper bound on system performance;
  2. Stochastic Regime: once collisions happen, or medium is detected busy during a packet arrival, the random generation of a Backoff counter happens, and the contention-based mechanism kicks in.
The deterministic regime is used to compute maximal performance of a WLAN. In such a case, performance may be superior even to the PCF mode, where AP acts as a transmission controller. However, in highly loaded networks, collisions are quite frequent, and the stochastic regime is more likely. Several works proposed stochastic models for this regime. Each work concerned one feature or another of network behavior. Bianchi [1] was the first to propose the use of Markov Chain in modeling the saturation regime of a WLAN. Since his paper, several others considered saturation, and non-saturation modeling of WLANs, increasing the model complexity, and taking into account more phenomena observed in experimental setups. In particular [2] represents a relatively good stochastic model for several regimes of WLAN. A somewhat refined diagram is presented in Figure 2. However the current state-of-the-art model is not sufficient for several reasons:
  1. It does not take into account the deterministic regime, nor does the performance converge to that upper bound;
  2. The Markovianity assumption is not always justifiable; is it possible to introduce a deterministic-stochastic hybrid model?
  3. Subsequent improvements of the standard are not yet captured by the current model; in particular the 802.11n draft introduces new MAC mechanisms.

The goal of this research group is to address one or more of the issues above. Ideally, students should have:

- familiarity with basic stochastic modeling concepts (such as Markov chains)
- familiarity with use of network simulation software (such as ns2);
- familiarity with time-series data analysis software (such as perl, Matlab);

Figure 2: A Markov Chain Model for a WLAN device.

Bibliography

[1] G.Bianchi, Performance Analysis of the IEEE 802.11 Distributed Coordination Function, IEEE Journal on Selected Areas of Communications, 18 (3), 2000, 535-547.

[2] P.E.Engelstad and O.N.Osterbo, Non-Saturation and Saturation Analysis of IEEE 802.11e EDCA with Starvation Prediction, MSWiM.05: Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems, Montreal, Canada, 2005.

Axel D. Becke (Dalhousie University) Exchange and correlation in electronic systems: the hole story
Abstract: Exchange and correlation effects in electronic systems are rigorously related to a two-electron function called the exchange-correlation "hole". Modelling of the hole in real space is a powerful route to development and refinement of exchange and correlation functionals in DFT. We have developed real-space models of all correlation types of importance in chemical physics (dynamical, nondynamical, and dispersion) and these will be reviewed.
Vivaldo L. Campo (University of Minnesota Twin Cities) Method for determination of Hubbard model phase diagram from optical lattice experiments by two parameter scaling
Abstract: Same abstract as the 7/24 poster session.
James R. Chelikowsky (University of Texas) Real space pseudopotentials applied to nanoscale systems
Abstract: One of the most challenging issues in materials physics is to predict the properties of matter at the nanoscale. In this size regime, new structural and electronic properties exist that resemble neither the atomic, nor solid state. These altered properties can have profound technological implications. Theoretical methods to address such issues face formidable challenges. Nanoscale systems may contain thousands of electrons and atoms, and often possess little symmetry. I will illustrate some recent advances in this area based on new computational methods and apply these techniques to systems ranging from clusters of a few dozen atoms to quantum dots containing thousands of atoms. Recent publications: Y. Zhou, Y. Saad, M.L. Tiago, and J.R. Chelikowsky: "Parallel Self-Consistent-Field Calculations via Chebyshev-Filtered Subspace Acceleration,'' Phys. Rev. E 74, 066704 (2006). M.L. Tiago, Y. Zhou, M.M.G. Alemany, Y. Saad, J.R. Chelikowsky: "The Evolution of Magnetism in Iron from the Atom to the Bulk,'' Phys. Rev. Lett. 97, 147201 (2006). M. Lopez del Puerto, M.L. Tiago, and J.R. Chelikowsky: "Excitonic effects and optical properties of passivated CdSe clusters,'' Phys. Rev. Lett. 97, 096401 (2006).
Matteo Cococcioni (University of Minnesota Twin Cities) A consistent, linear-response approach to LDA+U
Abstract: Hubbard U-corrected DFT functionals have been very successful in describing several strongly-correlated systems for which "standard" approximations to DFT fail. Unfortunately no explicit expression exists for the effective electronic interaction parameter (the Hubbard U) contained in the corrective ("+U") functional and semiempirical estimates have been often used to determine its value. In this talk, after a general introduction to the LDA+U method, I will present our linear response approach to the evaluation of the Hubbard U [1]. Within this approach the on-site electronic coupling is computed from the response of the considered system to a shift in the potential acting on its correlated atomic states. Specifically, it is evaluated as the difference between the inverse of the bare and fully interacting response matrices. The U we obtain thus corresponds to the effective (atomically averaged) interaction between electrons that are located on the same site. In this way the strength of the "+U" correction is consistently evaluated from the same DFT scheme we aim to correct; the LDA+U is transformed in a completely ab-initio method with no need for any empirical evaluation of the effective coupling. The results are also largely independent on the choice of the localized orbitals: the same occupation matrix that enters the expression of the "+U" correction is consistently used to compute the effective interaction parameter. With this approach we successfully studied the structural, electronic, chemical and electrochemical properties of several transition metals compounds. Examples of applications will include minerals in the Earth's interior [1], cathode materials for next-generation lithium-ion batteries [2] and catalysis reactions on molecules [3]. [1] M. Cococcioni and S. de Gironcoli, PRB (2005). [2] F. Zhou, M. Cococcioni, A. C. Marianetti, D. Morgan and G. Ceder, PRB (2004). [3] H. J. Kulik, M. Cococcioni, D. Scherlis and N. Marzari, PRL (2007).
Ismaila Dabo (Massachusetts Institute of Technology) Real-space corrections for electrostatic interactions in periodic boundary conditions
Abstract: Joint work with Boris Kozinsky (Department of Physics, MIT), Nicholas E. Singh-Miller, and Nicola Marzari (Department of Materials Science and Engineering, MIT). We address periodic-image errors arising from the use of periodic boundary conditions to describe systems that do not exhibit full three- dimensional periodicity. We show that the difference between the periodic potential, straightforwardly obtained from a Fourier transform, and the exact potential can be characterized analytically. In light of this observation, we present an efficient real-space method to correct periodic-image errors, demonstrating that exponential convergence of the energy with respect to cell size can be achieved in practical periodic boundary-condition calculations. Comparing the method with existing schemes, we find that it is particularly advantageous for studying charged systems and systems exhibiting partial periodicity.
Ernest R. Davidson (University of Washington) Theoretical description of electrons in single molecule magnets
Abstract: Single molecule magnets are usually based on transition metals with partially filled d shells. When several metal centers are involved this leads to molecules with many single occupied orbitals coupled into an intermediate spin state. Conventional methods of quantum chemistry are not able to deal with this situation, so the Heisenberg model hamiltonian is often used with parameters estimated from DFT calculations. Practical as well as logical problems with this approach will be discussed. Some of the difficulties with treating exchange in DFT for open shell systems will be presented.
Kaushik Dayal (University of Minnesota Twin Cities) Objective structures and their applications
Abstract: Same abstract as the 7/24 poster session.
Amélie Deleurence (École Nationale des Ponts-et-Chaussées (ENPC)) Modelling of local defects in crystals
Abstract: Same abstract as the 7/24 poster session.
Jean-Luc Fattebert (Lawrence Livermore National Laboratory) Real-space finite difference method for O(N) first-principles molecular dynamics with plane waves accuracy
Abstract: Representing the electronic structure in Density Functional Theory (DFT) by a set of localized wave functions discretized on a real-space mesh essentially leads to a linear scaling of the computational cost with the size of the physical system. This can be achieved by formulating the DFT energy functional in terms of general non-orthogonal orbitals which are then optimized under localization constraints (spatial confinement). Multigrid preconditioning and a block version of Anderson's extrapolation scheme are used to accelerate convergence towards the ground state. For localization regions --- constraints --- large enough, one can reduce truncation error to a value smaller than discretization error and achieve the level of accuracy of a Plane Waves calculation. Accuracy is improved by allowing for flexible localization regions that can adapt to the system. This also reduces problems with local minima and enables energy conserving Born-Oppenheimer molecular dynamics simulations. Our implementation of this approach scales on hundreds of processors and becomes competitive with Plane Waves codes around 500 atoms. References:
[1] J.-L. Fattebert and F. Gygi, Phys. Rev. B 73, 115124 (2006)
[2] J.-L. Fattebert and F. Gygi, Comput. Phys. Comm. 162, 24 (2004) This work was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48.
Seyed-Alireza Ghasemi (Universität Basel) A systematic method to explore possible silicon tip structures used in AFM
Abstract: Same abstract as the 7/24 poster session.
Stefan Goedecker (Universität Basel) Wavelets for electronic structure calculations and electrostatic problems
Abstract: Wavelets are a systematic localized basis set that is well suited for representing Kohn-Sham orbitals. I will explain the algorithms that we are using in our new ABINIT wavelet program and show perfomance results. In the second part I will show how scaling functions can be used to solve electrostatic problems both for continuous and discrete charge distributions under various boundary conditions.
Gary B. Green (The Aerospace Corporation) Team 3: Associating earth-orbiting objects detected by astronomical telescopes
Abstract: Project description: Astronomical telescopes detect the passage of an earth-orbiting object as a streak in an image. Over a period of months, it is possible that many objects will pass through the field of view, some appearing more than once. There are estimates of 100,000 objects in orbit that might be detected by high resolution telescopes. A large field of view telescope may see 100 streaks a night. Most of these objects are space debris that pose a hazard to operational satellites. There is keen interest within the space community to discover and track all these objects.

If the telescope sensor is properly instrumented, it is possible to obtain time-tagged pairs of angles that relate the space object position to the sensor. With enough angle pairs, it is possible to estimate the position and velocity (the state) of the object, along with estimates of the uncertainties of these parameters. The workshop problem is to develop techniques to identify all the streaks made by each object. Streaks created by an object must somehow be associated with one another and disassociated from those made by other objects. One solution approach treats the state data as vectors in R6 and uses statistical clustering techniques for the association. A variation on this approach addresses physical properties of the orbits, sorting according to those least likely to change with small state variations.

Regardless of the approach, there are several interesting aspects to the problem. Automatic streak detection is required, with transform techniques of interest. Orbit mechanics are essential to effective state estimation as well as clustering techniques. In addition, traditional clustering techniques are computationally taxing. A related problem is identification of asteroids that might pose a hazard to planet earth. References:

Vallado, David A., Fundamentals of Astrodynamics and Applications, Edition 2, Microsoft Press, 2004; Milani, Andrea, "Three Short Lectures on Identifications and Orbit Determination," http://copernico.dm.unipi.it/~milani/preprints/preprint.html, 2006; Kaufman, L. and Rousseeuw, P., Finding Groups in Data - An Introduction to Cluster Analysis. Wiley Interscience 2005

Prerequisites:

Required: computing proficiency demonstrated by knowledge of at least one compiler, one semester differential equations, one semester statistics

Desired: one semester numerical analysis, familiarity with orbit mechanics and estimation theory.

Keywords: orbit mechanics, astronomical telescopes, statistical clustering

The Pan-starrs telescope on Mount Haleakela in Hawaii will be used, among other tasks, to search for asteroids. However, using its 1.4 billion pixel sensor, it will also detect earth-orbiting objects.

Nicholas M. Harrison (Imperial College London) Novel materials for quantum computing
Abstract: The controlled transport of spin polarised electrons on a 1 nanometre length scale is a realistic prospect and could be the basis for new multifunctional devices with a component density an order of magnitude higher than current VLSI technology. The fundamental materials chemistry challenge is to produce a nano-structured semiconductor that is ferromagnetic at room temperature. Ideally the electronic and magnetic properties need to be robust but tunable through control of composition and structure. The results of recent high quality theoretical calculations on a number of pure carbon materials will be presented. A novel mechanism for long range magnetic coupling in extended pi-bonded systems will be discussed and documented with explicit calculations on graphene ribbons and defective graphene sheets. A putative ordered defect phase which gives rise to a semiconducting ground state that is ferromagnetic at room temperature will be presented. It will also be shown that the band gap and magnetic coupling may be controlled by varying the defect density.
Pieter Hendrickx (University of Ghent (UG)) Conformational reinvestigation of two cyclic pentapeptides: to a generic approach in drug development
Abstract: Same abstract as the 7/24 poster session.
John R. Hoffman (Lockheed Martin Missiles and Space Company, Inc.) Team 4: High dimensional, nonlinear, non-convex optimization problems in the area of aircraft and vehicle design
Abstract: Presently, when a physics motivated vehicle designer explores vehicle designs for a new concept, he is often faced with an enormous range of choices and constraints. For an example, an aircraft designer has Aircraft shape, fuel type, and engine as his main free variables. While his main constraints are dictated by the laws of physics (weight, size, power, lift, and stall). Additionally, he has his objective which is typically some combination/subset of acceleration, maneuverability, range, endurance, payload capacity (size, weight and power), max and min speeds, manufacturing cost, maintainability, reliability, development cost, takeoff length, landing length, noise footprint and other items.

I am interested in examining the following problem: Given a set of performance objectives, how does one determine the space of designs available to the designer and find the optimal designs? How does the designer best visualize this space of options? Because he doesn't want just "the" answer, he wants to understand many aspects of the answer. While I'm interested in the general vehicle design problem, we will focus on aircraft design using a baseline tool that is to be determined as a concrete example with which we can test our ideas.

Jürg Hutter (Universität Zürich) Efficient Kohn-Sham density functional calculations using the Gaussian and plane waves approach
Abstract: The Gaussian and plane waves (GPW) approach combines the description of the Kohn-Sham orbitals as a linear combination of Gaussian functions with a representation of the electron density in plane waves. The unique properties of Gaussian functions allow for a fast and accurate calculation of the density in the plane wave basis. The plane wave representation of the density leads to an easy solution of Poisson's equation and thereby a representation of the electrostatic potential. Matrix elements of this potential can be calculated using the same methods. The auxiliary representation of the density is further used in the calculation of the exchange-correlation energy and potential. The resulting approach scales O(N log N) in the number of electrons and has many additional interesting features, namely, a small prefactor, early onset of linear scaling, and a nominal quadratic scaling in the basis set size for fixed system size. The GPW method is combined with a direct optimization of the subspace of occupied Kohn-Sham orbitals using an orbital transformation (OT) method. A variation of this method has recently been implemented that only requires matrix multiplications. The method combines a small prefactor with efficient implementation on parallel computers, thereby shifting the break even point with linear scaling algorithms to much larger systems. A strategy to combine the OT method with sparse linear algebra will be outlined.
Olexandr Isayev (Jackson State University) An ab initio molecular dynamics simulation of solid CL-20: mechanism and kinetics of thermal decomposition
Abstract: Same abstract as the 7/24 poster session.
Changho Kim (Korea Advanced Institute of Science and Technology (KAIST)) Numerical method for solving stochastic differential equations with non-Gaussian noise
Abstract: Same abstract as the 7/24 poster session.
David Langreth (Rutgers University) Van der Waals interactions in density functional theory
Abstract: To understand biostructures, soft matter, and other abundant sparse systems, one must account for both strong local atomic bonds and weak nonlocal van der Waals (vdW) forces between atoms which are sometimes separated by empty space. A fully nonlocal density functional, vdW-DF [1,3], now including a self-consistent potential [2,3], will be described. It has had a number of promising applications [3], some of which will be presented, including polymer crystals, metal-organic-framework structures, and nucleic acids. [1] Phys. Rev. Lett. 92, 246401 (2004); [2] cond-mat/0703442v1; [3] Much of the vdW-DF work has been a Chalmers-Rutgers collaboration.
Arash A. Mostofi (University of Cambridge) Linear-scaling density-functional calculations with plane-waves
Abstract: A number of reasons have resulted in plane-waves becoming one of the basis sets of choice for simulations based on density-functional theory, for example: the kinetic energy operator is diagonal in momentum space; quantities are switched efficiently between real space and momentum space using fast-Fourier transforms; the atomic forces are calculated by straightforward application of the Hellmann-Feynman theorem; the completeness of the basis is controlled systematically with a single parameter. The resulting simulations require a computational effort which scales as the cube of the system-size, which makes the cost of large-scale calculations prohibitive. For this reason there has been much interest in developing methods whose computational cost scales only linearly with system-size and hence bringing to bear the predictive power of density-functional calculations on nanoscale systems. At first sight the extended nature of plane-waves makes them unsuitable for representing the localised orbitals of linear scaling methods. In spite of this, we have developed ONETEP (Order-N Electronic Total Energy Package), a linear-scaling method based on plane-waves which overcomes the above difficulty and which is able to achieve the same accuracy and convergence rate as traditional cubic-scaling plane-wave calculations.
Alexey Neelov (Universität Basel) Particle-Scaling function (P3S) algorithm for electrostatic problems in free boundary conditions
Abstract: Same abstract as the 7/24 poster session.
Christian Ochsenfeld (Eberhard-Karls-Universität Tübingen) A Linear-scaling AO-based MP2 method for large molecules by rigorous integral estimates
Abstract: Describing electron correlation effects for large molecules is a major challenge for quantum chemistry due to the strong increase of the computational effort with molecular size. In order to overcome this limitation, we present a rigorous method based on an AO-formulation of MP2 theory, which allows to avoid the conventional fifth-power scaling of MO-MP2 theory and to reduce the scaling to linear without sacrificing accuracy. The key feature of our method are multipole-based integral estimates (MBIE), which account for the 1/R coupling in two-electron integrals and allow to rigorously preselect integral products in AO-MP2 theory. Here, the magnitude of products decays at least with 1/R**4, so that a linear-scaling behavior can be achieved by numerical thresholding without sacrificing any accuracy. The linear-scaling increase of the computational effort is reached much earlier than for HF or DFT approaches: e.g. the exact behavior of products indicates a scaling of N**1.0 from one to two DNA base-pairs for a 6-31G* basis. The number of significant elements in the pseudo-density matrices and of shell pairs hints to a very similar linear-scaling behavior for larger basis sets studied up to cc-pVQZ. First results of a preliminary implementation show that an early crossover to conventional MP2 schemes below two DNA base pairs is observed, while already for a system with four DNA base pairs wins are at least a factor of 16.
Shantanu Roy (Universität Basel) A Bell-Evans-Polanyi principle for molecular dynamics trajectories and its implications for global optimization
Abstract: Same abstract as the 7/24 poster session.
Prasanjit Samal (University of Minnesota Twin Cities) Uniqueness of the density-to-potential mapping in excited-state density-functional theory
Abstract: Same abstract as the 7/24 poster session.
Andreas Savin (Université de Paris VI (Pierre et Marie Curie)) Dealing with spatial regions
Abstract: Chemists are used to see molecules in three dimensions, and think of the molecular properties often related to specific regions of space. This is a good source of inspiration for theoretical methods, but efficient algorithms for a mathematical treatment of models needing, e.g., integration in arbitrary, flexible regions in 3D are still needed.
Viktor N. Staroverov (University of Western Ontario) Kohn-Sham methods for implicit density functionals
Abstract: Density functional theory calculations with a certain class of approximations to the Kohn-Sham exchange-correlation energy require an indirect evaluation of the functional derivative of an implicit functional. Although the formal prescription for obtaining this derivative is known, there are fundamental pitfalls in its practical implementation using discrete basis set representations of the operators. We discuss several pragmatic solutions to this problem and compare their advantages in various applications.
Gabriel Stoltz (École Nationale des Ponts-et-Chaussées (ENPC)) Local exchange potentials: A mathematical viewpoint
Abstract: Work in collaboration with Eric Cancès (CERMICS), Ernest R. Davidson (Department of Chemistry, University of Washington), Artur F. Izmaylov, Gustavo Scuseria and Viktor N. Staroverov (Department of Chemistry, Rice University). This work reviews and presents in a unified fashion several well-known local exchange potentials, such as the Slater potential, Optimized Effective Potentials and their approximations (KLI, CEDA local potentials) and the recently proposed Effective Local Potential. We provide alternative derivations of some of these well-known potentials, mainly based on variational arguments (the local exchange potential being defined as the best approximation of the nonlocal Hartree-Fock operator in some least square sense). The remaining potentials are approximate solutions of the so-called OEP integral equation, and can be recovered through convenient approximations of the resolvent of the Hamiltonian operator.
Mark A. Stuff (General Dynamics Advanced Information Systems) Team 5: Size and shape comparisons from noisy, unlabeled, incomplete configurations of landmarks in three-dimensional space
Abstract: Traditional non-invasive sensing technologies have generated information about only one or two dimensional projections of objects of interest. But the use of arrays of sensor components, and opportunities to rapidly move such arrays around objects of interest are enabling the practical generation of many forms of three-dimensional data. For example, in acoustics there has been steady progression from one-dimensional echo trains, to two-dimensional acoustic images, to modern three-dimensional reconstructions, on scales from ultrasound wavelengths to global seismic surveys. Similarly, three-dimensional tomographic reconstructions from x-rays are now commonly used to resolve ambiguities in traditional two-dimensional x-ray images.

As more three-dimensional data becomes available, the value of automatic tools for utilizing such data increases. Several desired applications need methods by which to automate the finding of correspondences between three-dimensional data sets. These three-dimensional data sets frequently share many geometric characteristics, but also have significant differences, due to differences in data collection geometries, changes in sensor capabilities, temporal changes in the object of interest, and noise in the data.

One approach to finding unknown coordinate transformations, which are needed to align multi-dimensional data sets, is to require an expert to examine each set and label certain common landmarks. If sufficient landmarks, having the same unique labels can be found in both sets, the three-dimensional coordinates of the landmarks enable the coordinate transformation to be estimated. This is like aligning images of faces, by first extracting the coordinates the tips of the noses, the left corners of the mouths, the bases of the right earlobes, etc.

But when no prior expertise is available, we need methods of estimating the transformation from set of automatically generated coordinates of 'interesting' locations (unlabeled landmarks). We expect that a significant subset of corresponding unlabeled landmarks may exist somewhere in the data set to which we need to compare. To solve our alignment problems, we need to devise automated methods to robustly find a pair of large subsets from a pair of sets of unlabeled landmarks, such that the subsets have similar geometric characteristics.

Does there exist a rigid motion mapping the configuration of red points onto a subset of the blue points? If so, what is the blue subset, and what is the rigid motion? If not, how much deformation of the red configuration is needed to make it so?

In principle, these problems can be solved by exhaustively comparing every possibility, but the level of effort grows exponentially fast with the number of landmarks. Our goal will be to find and test new approaches to this problem, seeking to devise algorithms which are robust and far more efficient.

References:

  1. Oliver Faugeraus, Three-Dimensional Computer Vision, MIT Press, 2001
  2. Ian L. Dyrden, Kanti V. Mardia, {Statistical Shape Analysis}, Wiley, 1998
  3. D. G. Kendall, D. Barden, T. K. Carne, H. Le, Shape and Shape Theory, Wiley Series in Probability and Statistics, 1999
  4. Gene H. Golub, Charles Van Loan, Matrix Computations, Johns Hopkins University Press, 1996

Prerequisites:

Basics of linear algebra and matrix theory, basic computer programming skills, elementary Euclidean geometry

Desired: Ability to bring relevant ideas from one or more of geometry, invariant theory, optimization theory, graph theory, combinatorics, or something else.

Michael Teter (Cornell University) Precision problems in density functional development for better molecular modeling
Abstract: Same abstract as the 7/24 poster session.
Walter Thiel ( Max-Planck-Institut für Kohlenforschung) QM/MM studies on enzymes
Abstract: The lecture will report on recent progress in combined quantum mechanical / molecular mechanical (QM/MM) approaches for modeling chemical reactions in large biomolecules. After a brief outline of the theoretical background and the chosen strategy [1], we address free-energy QM/MM calculations as well as the use of accurate correlated ab initio QM methods in QM/MM work. Case studies are presented for biocatalysis by p-hydroxybenzoate hydroxylase [2,3] and cytochrome P450cam [4,5]. [1] H. M. Senn, W. Thiel, Top. Curr. Chem. 2007, 268, 173-290.
[2] H. M. Senn, S. Thiel, W. Thiel, J. Chem. Theory Comput. 2005, 1, 494-505.
[3] F. Claeyssens, J. N. Harvey, F. R. Manby, R. Mata, A. J. Mulholland, K. E. Ranaghan, M. Schuetz, S. Thiel, W. Thiel, H.-J. Werner, Angew. Chem. Int. Ed. 2006, 45, 6856-6859.
[4] J. C. Schoeneboom, F. Neese, W. Thiel, J. Am. Chem. Soc. 2005, 127, 5840-5853.
[5] A. Altun, V. Guallar, R. A. Friesner, S. Shaik, W. Thiel, J. Am. Chem. Soc. 2006, 128, 3924-3925.
Donald G. Truhlar (University of Minnesota Twin Cities) New density functionals: a meta GGA and three hybrid meta GGAs with good performance for thermochemistry, thermochemical kinetics, noncovalent interactions, and spectroscopy
Abstract: In work carried out with Yan Zhao, we have developed a suite of hybrid meta exchange-correlation functionals, including three hybrid meta generalized gradient approximations (hybrid meta GGAs) called M06, M06-2X, and M06-HF and one local meta GGA, called M06-L. The M06 and M06-L functionals are parametrized including both transition metals and nonmetals, whereas the M06-2X and M06-HF functionals are high-nonlocality functionals with double the amount of nonlocal exchange (2X) as compared to M06 and 100% Hartree-Fock exchange, respectively, and they are parametrized only for nonmetals. We have assessed these four functionals by comparing their performance to that of other functionals and other theoretical results for 403 accurate energetic data in 29 diverse databases, including ten databases for thermochemistry, four databases for kinetics, eight databases for noncovalent interactions, three databases for transition metal bonding, one database for metal atom excitation energies, and three databases for molecular excitation energies. We have also tested the performance of these 17 methods for three databases containing 40 bond lengths and for databases containing 38 vibrational frequencies and 15 vibrational zero point energies. We recommend the M06-2X functional for applications involving main-group thermochemistry, kinetics, noncovalent interactions, and electronic excitation energies to valence and Rydberg states. We recommend the M06 functional for applications in organometallic and inorganometallic chemistry and for noncovalent interactions. We recommend the M06-HF functional for all main-group spectroscopy, and we recommend the local M06-L functional for calculations on large systems, where a local functional is very cost efficient. An overview of this work will be presented.
Erkan Tüzel (North Dakota State University) Mesoscopic model for the fluctuating hydrodynamics of binary and ternary mixtures
Abstract: Same abstract as the 7/24 poster session.
Yan Alexander Wang (University of British Columbia) Orbital-Corrected Orbital-Free density functional theory
Abstract: Density functional theory (DFT) has been firmly established as one of the most widely used first-principles quantum mechanical methods in many fields. Each of the two ways of solving the DFT problem, i.e., the traditional orbital-based Kohn-Sham (KS) and the orbital-free (OF) [1] schemes, has its own strengths and weaknesses. We have developed a new implementation of DFT, namely orbital-corrected OF-DFT (OO-DFT) [2], which coalesces the advantages and avoids the drawbacks of OF-DFT and KS-DFT and allows systems within different chemical bonding environment to be studied at a much lower cost than the traditional self-consistent KS-DFT method. For the cubic-diamond Si and the face-centered-cubic Ag systems, OO-DFT accomplishes the accuracy comparable to fully self-consistent KS-DFT with at most two non-self-consistent iterations [2] via accurately evaluating the total electronic energy before reaching the full self-consistency [2-5]. Furthermore, OO-DFT can achieve linear scaling by employing currently available linear-scaling KS-DFT algorithms and may provide a powerful tool to treat large systems of thousands of atoms within different chemical bonding environment much more efficiently than other currently available linear-scaling DFT methods. Our work also provides a new impetus to further improve OF-DFT method currently available in the literature. [1] Y. A. Wang and E. A. Carter, in Theoretical Methods in Condensed Phase Chemistry, edited by S. D. Schwartz (Kluwer, Dordrecht, 2000), p. 117. [2] B. Zhou and Y. A. Wang, J. Chem. Phys. 124, 081107 (2006). (Communication) [3] “An Accurate Total Energy Density Functional,” B. Zhou and Y. A. Wang, Int. J. Quantum Chem. (in press). [4] “The Total Energy Evaluation in the Strutinsky Shell Correction Method,” B. Zhou and Y. A. Wang, J. Chem. Phys. (in press). [5] “Accelerating the Convergence of the Total Energy Evaluation in Density Functional Theory Calculations,” B. Zhou and Y. A. Wang, J. Chem. Phys. (submitted).
Renata Wentzcovitch (University of Minnesota Twin Cities) Materials at ultra-high PTs: the coming of age of planetary materials theory
Abstract: DFT based approaches permit the determination of structural and thermodynamic properties of materials with sufficiently useful accuracy to allow one to address states and properties of planetary interiors. I will make a brief review of areas in mineral physics problems that have recently experienced much progress and are shedding light on fundamental problems in planetary sciences. Research supported by NSF/EAR and NSF/ITR programs.
Tomasz A. Wesolowski (Université de Genève) Orbital-free embedding potential: properties, approximations, and the use in computer simulations to couple quantum chemical and classical levels of description
Abstract: Practical applications of one-electron equations for embedded orbitals (Eqs. 20-21 in Ref. [1]) hinge on the availability of explicit density functionals to approximate adequately the exchange-correlation energy and the non-additive kinetic energy. The former quantity is defined as in the Kohn-Sham formulation of density functional theory, whereas the latter one arises from the use of orbitals (/embedded orbitals/) for only a selected component of the total electron density in the applied formal framework. The quality of the /shifts /of the electronic properties of a chemical species due to its condensed phase environment calculated by means of Eqs. 20-21 of Ref. [1] is determined by the kinetic-energy-functional dependent component of the total effective potential. In this work, our recent works concerning the development and testing of system-independent approximations this component of the embedding potential. and selected representative applications to study details of the electronic structure of embedded systems in condensed phase [2,3] are reviewed. [1] T.A. Wesolowski & A. Warshel, /J. Phys. Chem./ *97* (1993), 8050.
[2] M. Zbiri, C. Daul, and T.A. Wesolowski, /Journal of Chemical Theory and Computation / *2* (2006) 1106.
[3] J. Neugebauer, C.R. Jacob, T.A. Wesolowski, E.J. Baerends, /J. Phys. Chem. A./ *109* (2005) 7805.
Dexuan Xie (University of Wisconsin) New numerical algorithms and software for minimizing biomolecular potential energy functions
Abstract: Same abstract as the 7/24 poster session.
Lisa Zhang (Lucent Technologies Bell Laboratories) Team 6: Wavelength assignment and conversion in optical networking
Abstract: Today's optical telecommunication networks carry audio, video and data traffic over fiber optics at extremely high bit rates. The design of such networks encompasses a range of challenging combinatorial optimization problems. Typically, these problems are computationally hard even for restricted special cases. In this project we study how to assign wavelengths and place equipment so as to carry a set of traffic demands in large scale optical networks.

Our design problems are motivated by a popular optical technology called Wavelength Division Multiplexing (WDM). In this setting each fiber is partitioned into a fixed number of wavelengths and demands sharing a common fiber must be transported on distinct wavelengths. A demand stays on the same wavelength along its routing path as much as possible. When this is infeasible, we can either deploy an extra fiber for the demand to continue on the same wavelength; or place a wavelength converter for the demand to continue on a different wavelength. Both options incur cost. One objective is to assign wavelengths and place converters in an advantageous way so as to minimize the total cost.

In this project we explore algorithms and heuristics for assigning wavelengths and placing converters. The goals include studying the tradeoff between optimality and complexity and understanding the gap between theoretical bounds and practical performance.

References:

[1] Matthew Andrews and Lisa Zhang, Complexity of Wavelength Assignment in Optical Network Optimization. (Please see Section VI.) Proceedings of IEEE INFOCOM 2006. Barcelona, Spain, April 2006. http://cm.bell-labs.com/~ylz/2006.coloring4.pdf

[2] C. Chekuri, et al. Design Tools for Transparent Optical Networks. Bell Labs Technical Journal. Vol. 11, No. 2, pp. 129-143, 2006.

Prerequisite:

Required: One semester of algorithms; One semester of theory of computing; One semester of programming.

Desired: Knowledge of Python and CPLEX.

Keywords: Analysis of algorithms, combinatorial optimization, implementation of heuristics

Visitors in Residence
Hoda Abdel-Aal Bettley University of Manchester 7/22/2007 - 8/3/2007
Nikhil Chandra Admal University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Haseena Ahmed Iowa State University 8/7/2007 - 8/17/2007
Natalia Alexandrov NASA Langley Research Center 8/7/2007 - 8/18/2007
Jungha An University of Minnesota Twin Cities 9/1/2005 - 8/31/2007
Douglas N. Arnold University of Minnesota Twin Cities 7/15/2001 - 8/31/2008
Donald G. Aronson University of Minnesota Twin Cities 9/1/2002 - 8/31/2007
Nii Attoh-Okine University of Delaware 7/22/2007 - 8/3/2007
Paul W. Ayers McMaster University 7/29/2007 - 8/3/2007
Radu V. Balan Siemens Corporate Research, Inc. 8/7/2007 - 8/17/2007
Suman Balasubramanian Mississippi State University 8/7/2007 - 8/18/2007
Eric Barth Kalamazoo College 7/22/2007 - 8/3/2007
Daniel J. Bates University of Minnesota Twin Cities 9/1/2006 - 8/31/2008
Axel D. Becke Dalhousie University 7/31/2007 - 8/4/2007
Guy Bencteux Électricité de France 7/22/2007 - 8/3/2007
Yermal Sujeet Bhat University of Minnesota Twin Cities 9/1/2006 - 8/31/2008
Dan Bolintineanu University of Minnesota Twin Cities 7/24/2007 - 8/3/2007
Stephen Bond University of Illinois at Urbana-Champaign 7/22/2007 - 8/3/2007
Sara Bonella Scuola Normale Superiore 7/23/2007 - 8/3/2007
Sebastien Boyaval Ecole Nationale des Ponts et Chaussees 7/22/2007 - 8/4/2007
Richard J. Braun University of Delaware 8/7/2007 - 8/18/2007
Leslie Button Corning 7/22/2007 - 8/3/2007
Vivaldo L. Campo University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Eric Cances CERMICS 7/22/2007 - 8/4/2007
Michael Case Clemson University 8/7/2007 - 8/19/2007
Matt Challacombe Los Alamos National Laboratory 7/29/2007 - 8/3/2007
Adam Chamberlin University of Minnesota Twin Cities 7/24/2007 - 8/3/2007
James R. Chelikowsky University of Texas 7/31/2007 - 8/3/2007
Qiang Chen University of Delaware 8/7/2007 - 8/18/2007
Prince Chidyagwai University of Pittsburgh 8/7/2007 - 8/17/2007
Ting-Lan Chin University of Minnesota Twin Cities 7/25/2007 - 8/3/2007
Jun Kyung Chung University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Giovanni Ciccotti Università di Roma "La Sapienza" 7/22/2007 - 8/3/2007
Matteo Cococcioni University of Minnesota Twin Cities 7/31/2007 - 8/3/2007
Christopher J. Cramer University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Ismaila Dabo Massachusetts Institute of Technology 7/27/2007 - 8/3/2007
Derek Jordan Dalle University of Minnesota Twin Cities 8/7/2007 - 8/18/2007
Bonhommeau Andre David University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Ernest R. Davidson University of Washington 7/31/2007 - 8/4/2007
Kaushik Dayal University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Amélie Deleurence École Nationale des Ponts-et-Chaussées (ENPC) 7/22/2007 - 8/4/2007
Lisa Driskell Purdue University 8/7/2007 - 8/17/2007
Ying Wai Fan Emory University 8/7/2007 - 8/17/2007
Brendan Farrell University of California 8/7/2007 - 8/18/2007
Jean-Luc Fattebert Lawrence Livermore National Laboratory 7/31/2007 - 8/3/2007
Olalla Nieto Faza University of Minnesota Twin Cities 7/24/2007 - 8/3/2007
Laura Gagliardi Université de Genève 7/22/2007 - 8/3/2007
Timur Gatanov Harvard University 7/22/2007 - 8/3/2007
Seyed-Alireza Ghasemi Universität Basel 7/22/2007 - 8/4/2007
Manik Ghosh Kyungpook National University 7/22/2007 - 8/3/2007
Stefan Goedecker Universität Basel 7/31/2007 - 8/4/2007
Yejun Gong Michigan Technological University 8/7/2007 - 8/17/2007
Kun Gou Texas A & M University 8/7/2007 - 8/17/2007
Jason E. Gower University of Minnesota Twin Cities 9/1/2006 - 8/31/2008
Gary B. Green The Aerospace Corporation 8/7/2007 - 8/18/2007
Chad Michael Griep University of Rhode Island 8/7/2007 - 8/17/2007
Sergei Grudinin Forschungszentrum Jülich 7/22/2007 - 8/3/2007
Venkata Suresh Reddy Guthikonda University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Jeffrey Haack University of Wisconsin 8/7/2007 - 8/17/2007
Woods Halley University of Minnesota Twin Cities 7/24/2007 - 8/3/2007
Nicholas M. Harrison Imperial College London 7/29/2007 - 8/2/2007
Carsten Hartmann Free University of Berlin 7/25/2007 - 8/3/2007
Pieter Hendrickx University of Ghent (UG) 7/21/2007 - 8/5/2007
Milena Hering University of Minnesota Twin Cities 9/1/2006 - 8/31/2008
Andres Heyden University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Tony Hill University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
John R. Hoffman Lockheed Martin Missiles and Space Company, Inc. 8/8/2007 - 8/18/2007
Benjamin J. Howard University of Minnesota Twin Cities 9/1/2006 - 8/21/2007
Jingwei Hu University of Wisconsin 8/7/2007 - 8/17/2007
Xueying Hu University of Michigan 8/7/2007 - 8/17/2007
Yi Huang Kent State University 8/7/2007 - 8/17/2007
Jürg Hutter Universität Zürich 7/31/2007 - 8/4/2007
Olexandr Isayev Jackson State University 7/22/2007 - 8/4/2007
Mark Iwen University of Michigan 8/7/2007 - 8/17/2007
Alexander Izzo Bowling Green State University 7/22/2007 - 8/4/2007
Rashi Jain New Jersey Institute of Technology 8/7/2007 - 8/17/2007
Richard D. James University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Dan Karls University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Abdelouahab Kenoufi Universität Basel 7/28/2007 - 8/4/2007
Changho Kim Korea Advanced Institute of Science and Technology (KAIST) 7/22/2007 - 8/4/2007
Hyungjun Kim California Institute of Technology 7/22/2007 - 8/4/2007
MoonChang Kim Seoul National University 8/8/2007 - 8/18/2007
Si-Jo Kim Andong National University 7/23/2007 - 8/3/2007
Soojeong Kim University of Iowa 8/30/2007 - 1/20/2008
Debra Knisley East Tennessee State University 8/19/2007 - 6/1/2008
Leeor Kronik Weizmann Institute of Science 7/22/2007 - 8/3/2007
Mandar Kulkarni University of Alabama at Birmingham 8/7/2007 - 8/17/2007
Yuen Yick Kwan Purdue University 8/7/2007 - 8/17/2007
Song-Hwa Kwon University of Minnesota Twin Cities 8/30/2005 - 8/31/2007
David Langreth Rutgers University 7/31/2007 - 8/3/2007
Claude Le Bris École Nationale des Ponts-et-Chaussées (ENPC) 7/22/2007 - 8/4/2007
Frédéric Legoll École Nationale des Ponts-et-Chaussées 7/22/2007 - 8/4/2007
Anton Leykin University of Minnesota Twin Cities 8/16/2006 - 8/15/2008
Qizhen Li University of Nevada 7/22/2007 - 8/4/2007
Xiantao Li Pennsylvania State University 7/23/2007 - 8/3/2007
Hstau Y Liao University of Minnesota Twin Cities 9/2/2005 - 8/31/2007
Florence J. Lin University of Southern California 7/25/2007 - 8/3/2007
Liping Liu California Institute of Technology 7/22/2007 - 8/3/2007
Xinlian Liu Hood College 7/22/2007 - 8/3/2007
Yun Liu University of Minnesota Twin Cities 8/8/2007 - 8/17/2007
Marie Lopez del Puerto University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Jianfeng Lu Princeton University 7/21/2007 - 8/3/2007
Laura Lurati University of Minnesota Twin Cities 9/1/2006 - 8/31/2008
Hannah Markwig University of Minnesota Twin Cities 9/1/2006 - 8/31/2007
Glenn Martyna IBM Corporation 7/22/2007 - 8/3/2007
Nicola Marzari Massachusetts Institute of Technology 7/29/2007 - 8/1/2007
Timur Milgrom Clemson University 8/7/2007 - 8/18/2007
Julie C. Mitchell University of Wisconsin 7/22/2007 - 8/2/2007
Michal Mlejnek Corning 7/22/2007 - 8/3/2007
Darin Mohr University of Iowa 8/7/2007 - 8/18/2007
Robert Molt Jr University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Arash A. Mostofi University of Cambridge 7/30/2007 - 8/3/2007
Alexey Neelov Universität Basel 7/22/2007 - 8/4/2007
Jiawang Nie University of Minnesota Twin Cities 9/1/2006 - 8/31/2007
Mechie Nkengla University of Illinois 8/7/2007 - 8/17/2007
Christian Ochsenfeld Eberhard-Karls-Universität Tübingen 7/30/2007 - 8/3/2007
Vincent Quenneville-Belair McGill University 8/7/2007 - 8/18/2007
Aravind Rammohan Corning 7/22/2007 - 8/3/2007
Fernando Reitich University of Minnesota Twin Cities 8/8/2007 - 8/17/2007
Andres Reyes Universidad Nacional de Colombia 7/22/2007 - 8/4/2007
Shantanu Roy Universität Basel 7/22/2007 - 8/4/2007
Yousef Saad University of Minnesota Twin Cities 7/30/2007 - 8/3/2007
Prasanjit Samal University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Julien Saur École Nationale des Ponts-et-Chaussées (ENPC) 7/22/2007 - 8/4/2007
Andreas Savin Université de Paris VI (Pierre et Marie Curie) 7/31/2007 - 8/3/2007
Abdallah Sayyed-Ahmad University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Arnd Scheel University of Minnesota Twin Cities 7/15/2004 - 8/31/2007
Gustavo E. Scuseria Rice University 7/29/2007 - 8/3/2007
Chehrzad Shakiban University of Minnesota Twin Cities 9/1/2006 - 8/31/2008
Josef Aaron Sifuentes Rice University 8/7/2007 - 8/18/2007
Viktor N. Staroverov University of Western Ontario 7/31/2007 - 8/4/2007
Gabriel Stoltz École Nationale des Ponts-et-Chaussées (ENPC) 7/22/2007 - 8/4/2007
Mark A. Stuff General Dynamics Advanced Information Systems 8/7/2007 - 8/18/2007
Stephen Taylor University of Auckland 7/21/2007 - 8/6/2007
Helmi Temimi Virginia Polytechnic Institute and State University 8/7/2007 - 8/18/2007
Michael Teter Cornell University 7/22/2007 - 8/4/2007
Walter Thiel Max-Planck-Institut für Kohlenforschung 7/29/2007 - 8/3/2007
Carl Toews University of Minnesota Twin Cities 9/1/2005 - 8/31/2007
Donald G. Truhlar University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Igor Tsukerman University of Akron 7/22/2007 - 8/3/2007
Mark E. Tuckerman New York University 7/22/2007 - 8/3/2007
Erkan Tüzel North Dakota State University 7/22/2007 - 8/3/2007
Paolo Valentini University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Kochuparambil Deenamma Vargheese Corning 7/22/2007 - 8/3/2007
Sorkin Viacheslav University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
John Voight University of Minnesota Twin Cities 8/15/2006 - 8/31/2007
Roman Voskoboynikov University of Cambridge 7/22/2007 - 8/5/2007
Rodolphe Vuilleumier Université de Paris VI (Pierre et Marie Curie) 7/27/2007 - 8/2/2007
Sinisa Vukovic University of Toronto 7/22/2007 - 8/4/2007
Feng Wang Kent State University 7/22/2007 - 8/3/2007
Ting Wang University of Michigan 8/7/2007 - 8/17/2007
Yan Alexander Wang University of British Columbia 8/2/2007 - 8/3/2007
Yilun Wang Rice University 8/7/2007 - 8/17/2007
Renata Wentzcovitch University of Minnesota Twin Cities 7/31/2007 - 8/3/2007
Tomasz A. Wesolowski Université de Genève 7/29/2007 - 8/5/2007
Jahmario Lemonte Williams Mississippi State University 8/7/2007 - 8/18/2007
Seongho Wu University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Dexuan Xie University of Wisconsin 7/22/2007 - 8/4/2007
Zhenqiu Xie Purdue University 8/7/2007 - 8/17/2007
Xiangrong Xin University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Jinglong Ye Mississippi State University 8/7/2007 - 8/18/2007
Hongchao Zhang University of Minnesota Twin Cities 9/1/2006 - 8/31/2008
Lisa Zhang Lucent Technologies Bell Laboratories 8/7/2007 - 8/18/2007
Yan Zhaw University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Jingjing Zheng University of Minnesota Twin Cities 7/23/2007 - 8/3/2007
Jintong Zheng University of Delaware 8/7/2007 - 8/17/2007
Weifeng Zhi University of Kentucky 8/7/2007 - 8/18/2007
Yunkai Zhou Southern Methodist University 7/22/2007 - 8/4/2007
Johannes Zimmer University of Bath 7/22/2007 - 8/4/2007
Legend: Postdoc or Industrial Postdoc Long-term Visitor

IMA Affiliates:
3M, Boeing, Carnegie-Mellon University, Corning, ExxonMobil, Ford, General Electric, General Motors, Georgia Institute of Technology, Honeywell, IBM, Indiana University, Iowa State University, Johnson & Johnson, Kent State University, Lawrence Livermore National Laboratory, Lockheed Martin, Los Alamos National Laboratory, Medtronic, Michigan State University, Michigan Technological University, Microsoft Research, Mississippi State University, Motorola, Northern Illinois University, Ohio State University, Pennsylvania State University, Purdue University, Rice University, Rutgers University, Sandia National Laboratories, Schlumberger-Doll, Schlumberger-Doll Research, Seoul National University, Siemens, Telcordia, Texas A & M University, University of Chicago, University of Cincinnati, University of Delaware, University of Houston, University of Illinois at 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 Tennessee, University of Texas, University of Wisconsin, University of Wyoming, US Air Force Research Laboratory, Wayne State University, Worcester Polytechnic Institute