Seminars and Colloquia by Series

Monday, November 5, 2018 - 14:00 , Location: Skiles 006 , Min Hoon Kim , Korea Institute for Advanced Study , Organizer: Jennifer Hom
Thursday, November 1, 2018 - 15:05 , Location: Skiles 006 , Christian Houdré , Georgia Institute of Technology , Organizer: Christian Houdre
Wednesday, October 31, 2018 - 13:55 , Location: Skiles 006 , Joe Fu , UGA , johogufu@gmail.com , Organizer: Galyna Livshyts
TBA
Wednesday, October 31, 2018 - 12:55 , Location: Skiles 006 , Joe Fu , UGA , johogufu@gmail.com , Organizer: Galyna Livshyts
TBA
Monday, October 29, 2018 - 14:30 , Location: Boyd , TBA , TBA , Organizer: Caitlin Leverson
Thursday, October 25, 2018 - 15:05 , Location: Skiles 006 , Eviatar Procaccia , Texas A&M , procaccia@math.tamu.edu , Organizer: Michael Damron
Wednesday, October 24, 2018 - 13:55 , Location: Skiles 006 , Dmirty Ryabogin , Kent State University , ryabogin@math.kent.edu , Organizer: Galyna Livshyts
TBA
Wednesday, October 24, 2018 - 12:55 , Location: Skiles 006 , Dmitry Ryabogin , Kent State University , ryabogin@math.kent.edu , Organizer: Galyna Livshyts
TBA
Friday, October 19, 2018 - 15:00 , Location: Skiles 005 , Boris Bukh , Carnegie Mellon University , Organizer: Lutz Warnke
Thursday, October 18, 2018 - 15:05 , Location: Skiles 006 , Rachel Kuske , School of Mathematics, Georgia Tech , Organizer: Christian Houdre
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).

Pages