COURSE INFORMATION

550.695 ADVANCED PARAMETERIZATION IN SCIENCE AND ENGINEERING

SPRING 2009

Instructor: Gregory Eyink
Department: Applied Mathematics & Statistics
Office: Whitehead 202-D
Office hours: Mon-Wed-Fri, 10:00-10:50am
Email: eyink@ams.jhu.edu
Phone: (410) 516-7201


Classroom:    Computational Science and Engineering Building (CSEB), B17

Course Web Page:    http://www.ams.jhu.edu/~eyink/Advance-Param

Text:   The notes of the lecturer and cited journal articles will constitute the primary source for the course.

Overview:   This course is a continuation of 560.700, ``Applications of Science-Based Coupling of Models.''
See the link on the main page. Although not strictly a prerequisite, 560.700 shared the main subject and goals
of the present course. The basic topic is the coupling of multi-scale/multi-physics models in the context of
a broad range of science and engineering applications, emphasizing calculable approximation schemes.
The course is fundamentally interdisciplinary. Two of its key objectives are to help students to develop an
appreciation for the many disciplines in which science-based coupling of models is important and also to help
students communicate with researchers in other areas, in order to share and cross-fertilize ideas and methods.

The principal difference of this course from 560.700 is methodological. 560.700 was an introductory survey
that presented a series of sample applications, drawn from diverse fields, discussing the problems, methods,
and prospects in those several areass. The lectures of 560.700 will provide most of the concrete examples
considered in this course. In our discussions, however, the emphasis will be on unity as well as diversity.
An attempt will be made to identify common mathematical structures and methods that cut across the several
fields of research. A deeper understanding of the shared mathematics and tools should permit more effective
communication between researchers and better ability to adapt and exploit new approaches.

Topics Covered:

I.    Dynamics.

II.    Coarse-Grained Dynamics.

III.    Ensembles & Probability.

IV.    Moment Closure.

V.    Statistical Estimation & Uncertainty Quantification.

VI.    Hybrid/Multiscale Algorithms.

Grading:

Your final grade in this class will be determined from homework and from participation in scheduled
classroom conference sessions.

There will be periodic homework assignments, with written solutions due in class at the beginning of
conference sessions. Most of the homework problems will fill in details of lecture examples, with the
aim of deepening students' understanding. Students are encouraged to discuss homework, but all solutions
must be written up and submitted individually. The instructor's solutions to assigned exercises
will be presented in the conference sessions and on-line.

In addition to formal homework assignments, students in the course have an important additional on-going
assignment. As each topic is discussed in the course, students are asked to think about how the material
is relevant (or irrelevant!) to their own research interests. These thoughts should be recorded in writing
and presented together with solutions to homework exercises. Discussion of the lecture material in the
conference sessions will be an integral part of the course.