| Hardcover ISBN: | 978-0-8218-3843-3 |
| Product Code: | CRMM/25 |
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| eBook ISBN: | 978-1-4704-3869-2 |
| Product Code: | CRMM/25.E |
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| MAA Member Price: | $99.00 |
| AMS Member Price: | $88.00 |
| Hardcover ISBN: | 978-0-8218-3843-3 |
| eBook: ISBN: | 978-1-4704-3869-2 |
| Product Code: | CRMM/25.B |
| List Price: | $225.00 $170.00 |
| MAA Member Price: | $202.50 $153.00 |
| AMS Member Price: | $180.00 $136.00 |
| Hardcover ISBN: | 978-0-8218-3843-3 |
| Product Code: | CRMM/25 |
| List Price: | $115.00 |
| MAA Member Price: | $103.50 |
| AMS Member Price: | $92.00 |
| eBook ISBN: | 978-1-4704-3869-2 |
| Product Code: | CRMM/25.E |
| List Price: | $110.00 |
| MAA Member Price: | $99.00 |
| AMS Member Price: | $88.00 |
| Hardcover ISBN: | 978-0-8218-3843-3 |
| eBook ISBN: | 978-1-4704-3869-2 |
| Product Code: | CRMM/25.B |
| List Price: | $225.00 $170.00 |
| MAA Member Price: | $202.50 $153.00 |
| AMS Member Price: | $180.00 $136.00 |
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Book DetailsCRM Monograph SeriesVolume: 25; 2005; 133 ppMSC: Primary 60; Secondary 62; 76; 82; 86; 94
This book introduces mathematicians to the fascinating mathematical interplay between ideas from stochastics and information theory and practical issues in studying complex multiscale nonlinear systems. It emphasizes the serendipity between modern applied mathematics and applications where rigorous analysis, the development of qualitative and/or asymptotic models, and numerical modeling all interact to explain complex phenomena.
After a brief introduction to the emerging issues in multiscale modeling, the book has three main chapters. The first chapter is an introduction to information theory with novel applications to statistical mechanics, predictability, and Jupiter's Red Spot for geophysical flows. The second chapter discusses new mathematical issues regarding fluctuation-dissipation theorems for complex nonlinear systems including information flow, various approximations, and illustrates applications to various mathematical models. The third chapter discusses stochastic modeling of complex nonlinear systems. After a general discussion, a new elementary model, motivated by issues in climate dynamics, is utilized to develop a self-contained example of stochastic mode reduction.
Based on A. Majda's Aisenstadt lectures at the University of Montreal, the book is appropriate for both pure and applied mathematics graduate students, postdocs and faculty, as well as interested researchers in other scientific disciplines. No background in geophysical flows is required.
About the authors: Andrew Majda is a member of the National Academy of Sciences and has received numerous honors and awards, including the National Academy of Science Prize in Applied Mathematics, the John von Neumann Prize of the Society of Industrial and Applied Mathematics, the Gibbs Prize of the American Mathematical Society, and the Medal of the College de France. In the past several years at the Courant Institute, Majda and a multi-disciplinary faculty have created the Center for Atmosphere Ocean Science to promote cross-disciplinary research with modern applied mathematics in climate modeling and prediction. R.V. Abramov is a young researcher; he received his PhD in 2002. M. J. Grote received his Ph.D. under Joseph B. Keller at Stanford University in 1995.
Titles in this series are co-published with the Centre de recherches mathématiques.
ReadershipGraduate students and research mathematicians interested in multiscale modeling, information theory, and geophysical flows.
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Table of Contents
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Chapters
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Information theory, predictability, Jupiter’s great red spot, and equilibrium statistical mechanics
-
The fluctuation-dissipation theorem for complex nonlinear systems
-
Mathematical strategies for stochastic mode reduction in climate
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Additional Material
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RequestsReview Copy – for publishers of book reviewsAccessibility – to request an alternate format of an AMS title
- Book Details
- Table of Contents
- Additional Material
- Requests
This book introduces mathematicians to the fascinating mathematical interplay between ideas from stochastics and information theory and practical issues in studying complex multiscale nonlinear systems. It emphasizes the serendipity between modern applied mathematics and applications where rigorous analysis, the development of qualitative and/or asymptotic models, and numerical modeling all interact to explain complex phenomena.
After a brief introduction to the emerging issues in multiscale modeling, the book has three main chapters. The first chapter is an introduction to information theory with novel applications to statistical mechanics, predictability, and Jupiter's Red Spot for geophysical flows. The second chapter discusses new mathematical issues regarding fluctuation-dissipation theorems for complex nonlinear systems including information flow, various approximations, and illustrates applications to various mathematical models. The third chapter discusses stochastic modeling of complex nonlinear systems. After a general discussion, a new elementary model, motivated by issues in climate dynamics, is utilized to develop a self-contained example of stochastic mode reduction.
Based on A. Majda's Aisenstadt lectures at the University of Montreal, the book is appropriate for both pure and applied mathematics graduate students, postdocs and faculty, as well as interested researchers in other scientific disciplines. No background in geophysical flows is required.
About the authors: Andrew Majda is a member of the National Academy of Sciences and has received numerous honors and awards, including the National Academy of Science Prize in Applied Mathematics, the John von Neumann Prize of the Society of Industrial and Applied Mathematics, the Gibbs Prize of the American Mathematical Society, and the Medal of the College de France. In the past several years at the Courant Institute, Majda and a multi-disciplinary faculty have created the Center for Atmosphere Ocean Science to promote cross-disciplinary research with modern applied mathematics in climate modeling and prediction. R.V. Abramov is a young researcher; he received his PhD in 2002. M. J. Grote received his Ph.D. under Joseph B. Keller at Stanford University in 1995.
Titles in this series are co-published with the Centre de recherches mathématiques.
Graduate students and research mathematicians interested in multiscale modeling, information theory, and geophysical flows.
-
Chapters
-
Information theory, predictability, Jupiter’s great red spot, and equilibrium statistical mechanics
-
The fluctuation-dissipation theorem for complex nonlinear systems
-
Mathematical strategies for stochastic mode reduction in climate
