Wed, April 3, 2019
Public Access

Category: All

April 2019
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3:00pm [3:00pm] Harsha Hutridurga
Popular Talk. Speaker: Harsha Hutridurga. Date and Time: Wednesday 03 April, 3:00 pm - 3:50 pm. Venue: Ramanujan Hall, Department of Mathematics. Title: Intrigue of Invisibility cloaking. Abstract: Rendering objects or oneself invisible to others has fascinated us since the dawn of human civilization. Illustration of such vanishing acts are often made in sci-fi movies. Even though this idea of making oneself invisible to others sounds out of reach, lately it is gaining traction in the scientific community. This has led to the emergence of a fascinating field of meta-materials which deals with the design and study of assemblies of ordinary materials such that the assembly as a whole behaves in an exotic manner. This talk will try to present some elementary ideas involved in the theory of invisibility cloaking. The talk is intended for non-experts and will be accessible to people familiar with basic notions in multivariable calculus.

4:00pm [4:00pm] Rachel Kuske, Georgia Tech, Department Colloquium
Department Colloquium. Speaker: Rachel Kuske. Affiliation: Georgia Tech. Date and Time: Wednesday 03 April, 4:00 pm - 5:00 pm. Venue: Ramanujan Hall, Department of Mathematics. Title: Prevalence of heavy-tailed distributions in systems with multiple scales: insights through stochastic averaging. Abstract: Heavy tailed distributions have been shown to be consistent with data in a variety of systems with multiple time scales. Recently, increasing attention has appeared in different phenomena related to climate. For example, correlated additive and multiplicative (CAM) Gaussian noise, with infinite variance or heavy tails in certain parameter regimes, has received increased attention in the context of atmosphere and ocean dynamics. We discuss how CAM noise can appear generically in many reduced models. Then we show how reduced models for systems driven by fast linear CAM noise processes can be connected with the stochastic averaging for multiple scales systems driven by alpha-stable processes. We identify the conditions under which the approximation of a CAM noise process is valid in the averaged system, and illustrate methods using effectively equivalent fast, infinite-variance processes. These applications motivate new stochastic averaging results for systems with fast processes driven by heavy-tailed noise. We develop these results for the case of alpha-stable noise, and discuss open problems for identifying appropriate heavy tailed distributions for these multiple scale systems. This is joint work with Prof. Adam Monahan (U Victoria) and Dr. Will Thompson (UBC/NMi Metrology and Gaming).