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AN13 and CT13 Abstracts AN13 and CT13 Abstracts Abstracts are printed as submitted by the authors. Society for Industrial and Applied Mathematics 3600 Market Street, 6th Floor Philadelphia, PA 19104-2688 USA Telephone: +1-215-382-9800 Fax: +1-215-386-7999 Conference E-mail: [email protected] Conference web: www.siam.org/meetings/ Membership and Customer Service: 800-447-7426 (US & Canada) or +1-215-382-9800 (worldwide) 2 2013 SIAM Annual Meeting • SIAM Conference on Control & Its Applications Table of Contents Annual Meeting (AN13) Abstracts ...............................................3 Control & Its Applications (CT13) .............................................127 SIAM Presents Since 2008, SIAM has recorded many Invited Lectures, Prize Lectures, and selected Minisymposia from various conferences. These are available by visiting SIAM Presents (http://www.siam.org/meetings/presents.php). 2013 SIAM Annual Meeting • SIAM Conference on Control & Its Applications 3 AN13 Abstracts 4 AN13 Abstracts IC1 system including cars, buses, pedestrians, ants and molecu- Social Networks as Information Filters lar motors, which are considered as ”self-driven particles”. We recently call this interdisciplinary research on jamming Social networks, especially online social networks, are of self-driven particles as ”jamology”. This is based on driven by information sharing. But just how much informa- mathematical physics, and and includes engineering appli- tion sharing is influenced by social networks? A large-scale cations as well. In the talk, starting from the backgroud experiment measured the effect of the social network on the of this research, simple mathematical models, such as the quantity and diversity of information being shared within asymmetric simple exclusion process and the Burgers equa- Facebook. While strong ties were found to be individu- tion, are introduced as basis of all kinds of traffic flow. ally more influential, collectively it is the weak ties that Then it is extended in order to account various traffic phe- wield more influence and provide more diverse information nomena, and the comparison between theory and experi- exposure. This sharing behavior not only generates large ment is given to show that the models are able to capture cascades, but can also cause information to evolve. Joint fundamental features of observations. speaker with the SIAM Workshop on Network Science. Katsuhiro Nishinari Lada Adamic School of Engineering, The University of Tokyo University of Michigan, Ann Arbor PRESTO, Japan Science and Technology Corporation School of Information, Center for the Study of Complex [email protected] Syste [email protected] IC5 Stochastic Multiscale Modeling IC2 Cost-Minimizing Regulations for a Wholesale Elec- We consider systems that are governed by stochastic tricity Market ordinary and partial differential equations (SODEs and SPDEs), and we will present some effective methods for ob- We consider a wholesale electricity market model with gen- taining stochastic solutions. These can be coarse-grained erators interacting strategically and general networks in- molecular systems exhibiting multi-rate dynamics and gov- cluding externalities such as transmission losses. Previous erned by a very large number of SODEs or continuum mul- work shows how mechanisms such as the case when prices tiscale systems governed by SPDEs. We will present meth- correspond to the Lagrange multipliers of a centralized cost ods derived from the Mori-Zwanzig framework combined minimization program allow the producers to charge signif- with PDF evolution equations as well as recent extensions icantly more than marginal price. This situation originates of generalized polynomial chaos in high dimensions. We a important regulatory problem. In this presentation we will also discuss various applications in biophysics and in consider an incomplete information setting where the cost mesoscopic materials. structure of a producer is unknown to both its competitor and the regulator. We derive an optimal regulation mech- George E. Karniadakis anism and compare its performance to the ”price equal to Brown University Lagrange multiplier”. Division of Applied Mathematics george [email protected] Alejandro Jofr´e Universidad de Chile, Santiago, Chile [email protected] IC6 The Mathematics of Conservation Decision Making IC3 Species are currently becoming extinct at least 100 times Keeping Ford Green with Mathematics the background rate. The resources available to save biodi- versity are inadequate. Consequently we need to optimise Scientific societies, universities, research institutes, and the return on investment from conservation decisions. In foundations all over the world have banded together to ded- this talk I will show how we have been using optimisation icate 2013 as a special year for the Mathematics of Planet tools to solve conservation problems such as reserve system Earth. In line with this theme, I will describe how Ford’s design and allocating funds to threatened species manage- strategic sustainability efforts, as outlined in the Blueprint ment. for Sustainability, are supported by mathematical models. I will present examples of these modeling efforts, such as Hugh P. Possingham constructing global energy models, defining CO2 targets Department of Mathematics and School of Life Sciences over time, helping fleet customers reduce CO2 emissions, The University of Queensland and developing a future product and technology portfolio [email protected] that reduces emissions. Ford is committed to employing sustainable business processes and developing sustainable products: it’s not easy being green, but mathematics sure IC7 helps! Nonlinear Waves and Patterns: Two Examples Erica Klampfl Nonlinear waves and patterns are ubiquitous in nature. Ford Motor Company Surface waves on rivers, lakes and oceans, cloud patterns eklampfl@ford.com in the air, crystal structures in materials and animal skin patterns are just a few examples encountered in our ev- eryday lives. The underlying mathematical problems lead IC4 to nonlinear systems involving ordinary differential equa- Traffic Jams of Self-driven Particles tions or partial differential equations. This talk focuses on the analysis of two kinds of nonlinear waves and patterns. Jamming phenomena are seen in various transportation Relying upon techniques from the areas of dynamical sys- AN13 Abstracts 5 tems and bifurcation theory, we shall discuss, on the one physical significance. hand the dynamics of nonlinear water waves, and on the other hand, the existence of defects, such as dislocations Walter Craig and grain boundaries, in pattern forming systems. Department of Mathematics and Statistics McMaster University Mariana Haragus [email protected] Laboratoire de Mathematiques de Besancon Universite de Franche-Comte, France [email protected] IP1 Likelihood-based Climate Model Evaluation IC8 Climate models can be evaluated by comparing their out- Orthogonal Polynomials and Cubature Rules put to observations. Remote sensing data provide new possibilities for such comparisons because they are spa- Gaussian quadrature rules are important tools for numer- tially and temporally dense enough to go beyond simple ical integration. Their nodes are necessarily zeros of or- moments and estimate distributions. We evaluate climate thogonal polynomials. Does this relation extend to cuba- model fidelity to observations by the likelihood that a sum- ture (synonym for quadrature in higher dimension) rules mary statistic computed from an observational time series and orthogonal polynomials in several variables? The ex- arises from a sampling distribution of that same statistic tension works in some extend, but the relation becomes far calculated from a given climate model’s time series. We more complicated in higher dimension. For starter, it is demonstrate using models from the CMIP5 archive and necessary to consider common zeros of a family of poly- observations from NASA’s Atmospheric Infrared Sounder nomials, or, variety of a polynomial idea, in the language mission. of algebraic geometry. This talk explains what is known about zeros of orthogonal polynomials and cubature rules, Amy Braverman mostly restricted to two variables, and it includes several Jet Propulsion Laboratory recent examples that provide efficient numerical integration California Institute of Technology rules. [email protected] Yuan Xu University of Oregon IP2 [email protected] Correlation and Causality While everyone knows Berkeleys 1710 dictum correlation IC9 does not imply causation few realize that the converse cau- Photoacoustic Tomography: Ultrasonically Break- sation does not imply correlation is also true. This conun- ing through Optical Diffusion and Diffraction Lim- drum runs counter to deeply ingrained heuristic thinking its that is at the basis of modern science. Ecosystems are par- ticularly perverse on this issue by exhibiting mirage correla- Photoacoustic tomography (PAT), combining optical and tions that can continually cause us to rethink relationships ultrasonic waves via the photoacoustic effect, provides we thought we understood. Identifying causal networks is in vivo multiscale non-ionizing functional and molecular important for effective policy and management recommen- imaging. PAT is the only modality capable of imaging dations on climate, epidemiology, financial regulation, and across the length scales of organelles, cells, tissues, and or- much else. Here we introduce a method based on Takens gans with consistent contrast.
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