续上......
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北京大学2007年多重网络自适应有限方法暑期课程
于六月二十五日至七月十三日举办
多重网格自适应有限方法暑期课程将于2007年6月25日至7月13日在北京大学举行。本课程是北京
国际数学研究中心、北京大学研究生院、北京大学科学与工程计算中心共同主办的多重网格自适
应有限方法暑期系列活动的一个部分。目的是为国内青年学者和研究生提供一个学习、交流与合
作的平台。我们已经邀请来自海内外的知名学者进行为期3周的授课，内容主要包括：多重网格方
法、各向同性自适应有限元方法、各向异性各向同性自适应有限元方法。
欢迎各大院校研究生、博士后、青年教师报名参加。
报名方式
通过网页下载报名表格，用email方式发至lianglan@pku.edu.cn
不收取注册费等费用，但食宿自理
截止日期
即日起至2007年5月20日。被录取的名单将于2007年5月31日前用email方式通知
联系方式
北京大学数学科学学院 梁岚
100871
Email:lianglan@pku.edu.cn
电话：010－62759090
传真：010－62767146
网页链接http://ccse.pku.edu.cn/2007summer/shortcourse.html
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会议信息: A two-month program on ``Bose-Einstein Condensation and Quantized Vortices in
Superfluidity and Superconductivity''
at Institute for Mathematical Sciences, National University of Singapore
(1 Nov - 31 Dec 2007)
Organizing Committee
Co-chairs
Weizhu Bao (National University of Singapore)
Fanghua Lin (Courant Institute, New York University)
Members
Jiangbin Gong (National University of Singapore)
Dieter Jaksch (University of Oxford)
Baowen Li (National University of Singapore)
Peter Markowich (University of Vienna)
Overview
Since its realization in dilute bosonic atomic gases in 1995,
Bose-Einstein condensation (BEC) of alkali atoms and hydrogen atoms
has been produced and studied extensively in the laboratory.
This has spurred great excitement in the atomic physics community
and renewed the interest in studying collective dynamics of
macroscopic ensembles of atoms occupying the same one-particle
quantum state and quantized vortex in superfluidity. Theoretical
predictions of the properties of BEC like the density profile,
collective excitations and the formation of quantized vortices
can now be compared with experimental data.
This dramatic progress on the experimental front has stimulated
a wave of activity on both the theoretical and the numerical fronts.
In fact, the study of BEC and quantized vortices in superfluidity
has been and will continue to be one of the hottest research areas
in quantum physics and applied and computational mathematics.
It involves field theory, kinetic theory, quantum mechanics,
molecular dynamics, quantum hydrodynamics, stochastic analysis
and scientific computing. Scientific modeling, mathematical
analysis and numerical simulation within these frameworks are
among the central themes of modern applied mathematics and sciences.
With advances in technology, BEC in solids and waveguides as well
as fermion condensation were realized in experiments recently.
However, the understanding of these complicated physical phenomena,
in particular, the scientific modeling for fermion condensation
and the application of BEC in quantum computing, provide formidable
challenges to researchers in these fields.
This two-month program will bring together leading international
applied and pure mathematicians, theoretical and experimental
physicists, and computational scientists, and researchers from
NUS Departments of Mathematics, Physics, Material Sciences and
Mechanical Engineering, and from A*STAR institutes IHPC and IMRE,
to review, develop and promote interdisciplinary research on
Bose-Einstein condensation and quantized vortex states and dynamics
in superfluidity and superconductivity.
Activities
The program activities will consist of two workshops, series
seminars and collaborative research.
1. Collaborative research: 1 November -- 31 December, 2007
2. Workshop 1: 12 -- 16 November, 2007
Title: Bose-Einstein condensation: modeling, analysis,
computation and applications
3. Workshop 2: 10 -- 14 December, 2007
Title: Quantized vortices in superfluidity and superconductivity
and kinetic theory
For more information about the program, please visit its webpage at:
http://www.ims.nus.edu.sg/Programs/bose07/index.htm
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会议信息:
Mathematical Issues in Stochastic Approaches for Multiscale Modeling
http://www.msri.org/calendar/wor ... o/398/show_workshop
May 21, 2007 to May 25, 2007
Organized By: Roberto Camassa (UNC - Chapel Hill), Jinqiao Duan
(Illinois Institute of Technology - Chicago), Peter E. Kloeden (U of
Frankfurt, Germany), Jonathan Mattingly
(Duke U), Richard McLaughlin (UNC - Chapel Hill)
Parent Programs:
Dynamical Systems
Participant List:
View a List of Registered Participants
Complex physical, biological, geophysical and environmental systems display
variability
over a broad range of spatial and
temporal scales. To make progress in understanding and modelling such systems, a
combination of computational, analytical, and experimental techniques is required.
There are issues that emerge prominently in each of these categories and in all
these stochastic methods are playing a fundamental role.
Firstly, at present and for the conceivable future, not all scales of variability
can be explicitly modeled: representations of the effects of the unresolved scales
of variability on the resolved scales are needed -- the so-called parameterization
problem. Recently, stochastic parameterization schemes have been proposed and used
in, for example,
geophysical and climate simulations. Some of these stochastic parameterization
methods may be verified under certain conditions.
Secondly, critical insight can be gained by deriving and studying models that
are simple enough to be amenable to analysis. Stochastic evolutionary equations are
used to build reduced models to improve our understanding of non-equilibrium
multiscale systems. Central topics for non-equilibrium systems investigations
are, for example, time evolution of the statistics of dependent variables,
such as passive tracers and their increments, slow-fast motion decomposition,
coarse-graining and model reduction. Fast motion or microscopic processes may
be represented by stochastic processes and this has brought in new insights for
model reduction (such as slow manifold reduction) of multiscale systems.
Thirdly, engineering and natural systems are often subject to uncertainty or
random influence, such as stochastic forcing, uncertain parameters, and random
boundary conditions. Taking stochastic effects into account is of central importance
for developing mathematical models capable of interpreting experimental data.
Stochastic partial or ordinary differential
equations are appropriate models for randomly influenced multiscale systems.
The last decade has seen important developments in both the areas of stochastic
analysis and of dynamical systems. Random dynamical systems (e.g., basic
background materials in Ludwig Arnold's 1998 book Random Dynamical Systems),
as the combination of these two seemly remote mathematical areas, have attracted
considerable attention in multiscale modeling community recently. Stochastic
dynamical systems provide a unified framework and useful techniques for
investigating multiscale systems under uncertainty.
The research in the above-mentioned areas has reached a point where it is
important and timely to summarize the past
achievements, to synthesize various ideas, methods, and paradigms, and use
these to stimulate new research by discussing directions and outlooks. Many
challenging problems
lie ahead, such as invariant manifold reduction under uncertainty,
predictability of dynamical behavior, and systematic coarse-graining and model
reduction, to name just a few. Solutions for these problems will greatly
enhance our ability in understanding, quantifying, and managing uncertainty
and predictability in engineering and science. Breakthroughs in solving these
challenging problems are stimulated when we take concentrated and focused actions.
With this in mind, we propose to organize a workshop at MSRI on mathematical
issues in stochastic approaches for multiscale modeling. The major difference
with other workshops
is that we focus on mathematical issues about stochastic methods for
multiscale non-equilibrium systems.
The planned workshop will survey past achievements in stochastic approaches for
multiscale modeling, and discuss future research directions. It is hoped that this
workshop will provide a unique opportunity for interaction of established
mathematicians
and newcomers (Ph.D. students, post-docs, and junior researchers).
Major goals of this workshop are: (i) to stimulate new research on stochastic
modeling of multiscale systems, and (ii) to
attract Ph.D. students, post-docs, and junior researchers into this exciting
field. The engagement of newcomers into the field is an important feature of
this workshop. Newcomers will have informal individual meetings with senior
participants, discussing possible research topics. Round table meetings will
be held, with senior participants outlining
what areas they deem important and what opportunities exist for junior people
to get involved in addressing open problems. This will offer newcomers a
comprehensive view of
the state of art of the field and pick up appropriate research projects.
To facilitate
the continued interaction among participants, informal electronic newsletters
(via an
E-mail list) will be edited by the organizers, discussing research and teaching
of stochastic modeling of multiscale systems. |
楼主
显身卡
发表于 2007-5-24 09:16
