7月4日 Rachel Kuske:Prevalence of heavy-tailed distributions in systems with multiple scales: insights through stochastic averaging

来源:中国足球竞彩比分 时间:2019-06-26浏览:61设置


讲座题目:Prevalence of heavy-tailed distributions in systems with multiple scales: insights   through stochastic averaging

主讲人:Rachel Kuske

主持人:谈胜利 教授

开始来源:中国足球竞彩比分 时间:2019-07-04 13:00:00  结束来源:中国足球竞彩比分 时间:2019-07-04 14:00:00

讲座地址:闵行数学楼401

主办单位:数学科学学院

  

报告人简介:

RACHEL ANN KUSKE, Professor and Chair School   of Mathematics Georgia Institute of Technology.

I. EARNED DEGREES

B.S. Mathematics 1987 University of Wisconsin,   Green Bay, WI

Ph.D. Applied Mathematics 1992 Northwestern   University, Evanston, IL

Ph.D. Thesis Advisor: Professor B.J. Mathowsky   

Ph.D. Thesis Title: Asymptotic Analysis of   Random Wave Equations

II. EMPLOYMENT HISTORY

2017-present Professor and Chair, School of   Mathematics, Georgia Institute of Technology

2006-2016 Professor, University of British   Columbia, Vancouver, BC

2011-2015 Senior Advisor to the Provost on   Women Faculty, University of British Columbia, Vancouver, BC

2007-2011 Department Head, University of British   Columbia, Vancouver, BC

2002-2006 Associate Professor, University of   British Columbia, Vancouver, BC

2000-2002 Associate Professor, University of   Minnesota, Minneapolis, Minnesota

2001-2002 Associate Director, Minnesota Center   for Industrial Math, University of Minnesota, Minneapolis, Minnesota

1997-2000 Assistant Professor, University of   Minnesota, Minneapolis, Minnesota

1996-1997 Assistant Professor, Tufts   University, Medford, Massachusetts

1994-1996 NSF Postdoc, Stanford University,   Stanford, California

1992-1993 NSF Postdoc, Stanford University,   Stanford, California

III. HONORS AND AWARDS

1. Harold M. Bacon Teaching Award, Stanford   University, 1995

2. Sloan Dissertation Fellowship, 1991

3. Tufts University Faculty Research Summer   Award, 1996

4. Tufts University Mellon Research Semester   Fellowship, 1997

5. McKnight Land Grant Professorship, 1998

6. Canadian Research Chair II, Applied Math,   UBC, 2002

7. Krieger-Nelson Prize, CMS, 2011

8. SIAM Fellow, 2015

9. Simons Fellowship, 2016

10. Association for Women in Mathematics   Service Award, 2013


报告内容:

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).

  


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