Multiscale Methods

Averaging and Homogenization

Author: G A Pavliotis,Andrew Stuart

Publisher: Springer Science & Business Media

ISBN: 0387738282

Category: Mathematics

Page: 310

View: 9140

This introduction to multiscale methods gives you a broad overview of the methods’ many uses and applications. The book begins by setting the theoretical foundations of the methods and then moves on to develop models and prove theorems. Extensive use of examples shows how to apply multiscale methods to solving a variety of problems. Exercises then enable you to build your own skills and put them into practice. Extensions and generalizations of the results presented in the book, as well as references to the literature, are provided in the Discussion and Bibliography section at the end of each chapter.With the exception of Chapter One, all chapters are supplemented with exercises.
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Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology

Author: David Holcman

Publisher: Springer

ISBN: 3319626272

Category: Mathematics

Page: 377

View: 436

This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of stochastic reaction-diffusion models, while in the latter, one can describe the processes by adopting the framework of Markov jump processes and stochastic differential equations. Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology will appeal to graduate students and researchers in the fields of applied mathematics, biophysics, and cellular biology.
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Effective Dynamics of Stochastic Partial Differential Equations

Author: Jinqiao Duan,Wei Wang

Publisher: Elsevier

ISBN: 0128012692

Category: Mathematics

Page: 282

View: 692

Effective Dynamics of Stochastic Partial Differential Equations focuses on stochastic partial differential equations with slow and fast time scales, or large and small spatial scales. The authors have developed basic techniques, such as averaging, slow manifolds, and homogenization, to extract effective dynamics from these stochastic partial differential equations. The authors’ experience both as researchers and teachers enable them to convert current research on extracting effective dynamics of stochastic partial differential equations into concise and comprehensive chapters. The book helps readers by providing an accessible introduction to probability tools in Hilbert space and basics of stochastic partial differential equations. Each chapter also includes exercises and problems to enhance comprehension. New techniques for extracting effective dynamics of infinite dimensional dynamical systems under uncertainty Accessible introduction to probability tools in Hilbert space and basics of stochastic partial differential equations Solutions or hints to all Exercises
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Nonlinear and Stochastic Climate Dynamics

Author: Christian L. E. Franzke,Terence J. O'Kane

Publisher: Cambridge University Press

ISBN: 1316883213

Category: Science

Page: N.A

View: 5640

It is now widely recognized that the climate system is governed by nonlinear, multi-scale processes, whereby memory effects and stochastic forcing by fast processes, such as weather and convective systems, can induce regime behavior. Motivated by present difficulties in understanding the climate system and to aid the improvement of numerical weather and climate models, this book gathers contributions from mathematics, physics and climate science to highlight the latest developments and current research questions in nonlinear and stochastic climate dynamics. Leading researchers discuss some of the most challenging and exciting areas of research in the mathematical geosciences, such as the theory of tipping points and of extreme events including spatial extremes, climate networks, data assimilation and dynamical systems. This book provides graduate students and researchers with a broad overview of the physical climate system and introduces powerful data analysis and modeling methods for climate scientists and applied mathematicians.
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Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations

Stochastic Manifolds for Nonlinear SPDEs II

Author: Mickaël D. Chekroun,Honghu Liu,Shouhong Wang

Publisher: Springer

ISBN: 3319125206

Category: Mathematics

Page: 129

View: 400

In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.
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Multiscale Modeling and Simulation in Science

Author: Björn Engquist,Per Lötstedt,Olof Runborg

Publisher: Springer Science & Business Media

ISBN: 3540888578

Category: Computers

Page: 320

View: 389

Most problems in science involve many scales in time and space. An example is turbulent ?ow where the important large scale quantities of lift and drag of a wing depend on the behavior of the small vortices in the boundarylayer. Another example is chemical reactions with concentrations of the species varying over seconds and hours while the time scale of the oscillations of the chemical bonds is of the order of femtoseconds. A third example from structural mechanics is the stress and strain in a solid beam which is well described by macroscopic equations but at the tip of a crack modeling details on a microscale are needed. A common dif?culty with the simulation of these problems and many others in physics, chemistry and biology is that an attempt to represent all scales will lead to an enormous computational problem with unacceptably long computation times and large memory requirements. On the other hand, if the discretization at a coarse level ignoresthe?nescale informationthenthesolutionwillnotbephysicallymeaningful. The in?uence of the ?ne scales must be incorporated into the model. This volume is the result of a Summer School on Multiscale Modeling and S- ulation in Science held at Boso ¤n, Lidingo ¤ outside Stockholm, Sweden, in June 2007. Sixty PhD students from applied mathematics, the sciences and engineering parti- pated in the summer school.
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A Course on Rough Paths

With an Introduction to Regularity Structures

Author: Peter K. Friz,Martin Hairer

Publisher: N.A

ISBN: 9783319083339

Category:

Page: 268

View: 8112

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Data Assimilation

A Mathematical Introduction

Author: Kody Law,Andrew Stuart,Konstantinos Zygalakis

Publisher: Springer

ISBN: 3319203258

Category: Mathematics

Page: 242

View: 4662

This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters. This book is aimed at mathematical researchers interested in a systematic development of this interdisciplinary field, and at researchers from the geosciences, and a variety of other scientific fields, who use tools from data assimilation to combine data with time-dependent models. The numerous examples and illustrations make understanding of the theoretical underpinnings of data assimilation accessible. Furthermore, the examples, exercises and MATLAB software, make the book suitable for students in applied mathematics, either through a lecture course, or through self-study.
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Numerische Behandlung partieller Differentialgleichungen

Author: Christian Großmann,Hans-Görg Roos

Publisher: Springer-Verlag

ISBN: 9783519220893

Category: Mathematics

Page: 572

View: 3623

Mathematiker, Naturwissenschaftler und Ingenieure erhalten mit diesem Lehrbuch eine Einführung in die numerische Behandlung partieller Differentialgleichungen. Diskutiert werden die grundlegenden Verfahren - Finite Differenzen, Finite Volumen und Finite Elemente - für die wesentlichen Typen partieller Differentialgleichungen: elliptische, parabolische und hyperbolische Gleichungen. Einbezogen werden auch moderne Methoden zur Lösung der diskreten Probleme. Hinweise auf aktuelle Software sowie zahlreiche Beispiele und Übungsaufgaben runden diese Einführung ab.
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Finite Elemente

Theorie, schnelle Löser und Anwendungen in der Elastizitätstheorie

Author: Dietrich Braess

Publisher: Springer-Verlag

ISBN: 3662072335

Category: Technology & Engineering

Page: 320

View: 7078

Diese völlig überarbeitete Neuauflage bietet dem Leser eine gründliche Einführung in die Methode der Finiten Elemente, welche heute verstärkt zur numerischen Lösung von partiellen Differentialgleichungen eingesetzt werden. Die Theorie wird so weit entwickelt, daß der Leser mit Kenntnissen aus den Grundvorlesungen des Mathematikstudiums auskommt. Dem für die Praxis relevanten Mehrgitterverfahren und der Methode der konjugierten Gradienten wird ein breiter Platz eingeräumt. Ausführlich wird die Strukturmechanik als ein wichtiger und typischer Anwendungsbereich für Finite Elemente behandelt. Da dieser Aspekt in anderen Lehrbüchern kaum Berücksichtigung findet, wurde er in der Neuauflage stark überarbeitet und abgerundet. Als weitere Ergänzung ist vor allem die Diskussion von a posteriori Schätzern zu nennen.
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Numerische Simulation in der Moleküldynamik

Numerik, Algorithmen, Parallelisierung, Anwendungen

Author: Michael Griebel,Stephan Knapek,Gerhard Zumbusch,Attila Caglar

Publisher: Springer-Verlag

ISBN: 364218779X

Category: Mathematics

Page: 480

View: 7137

Das Buch behandelt Methoden des wissenschaftlichen Rechnens in der Moleküldynamik, einem Bereich, der in vielen Anwendungen der Chemie, der Biowissenschaften, der Materialwissenschaften, insbesondere der Nanotechnologie, sowie der Astrophysik eine wichtige Rolle spielt. Es führt in die wichtigsten Simulationstechniken zur numerischen Behandlung der Newtonschen Bewegungsgleichungen ein. Der Schwerpunkt liegt hierbei auf der schnellen Auswertung kurz- und langreichweitiger Kräfte mittels Linked Cell-, P$/\3$M-, Baum- und Multipol-Verfahren, sowie deren paralleler Implementierung und Lastbalancierung auf Rechensystemen mit verteiltem Speicher. Die einzelnen Kapitel beinhalten darüberhinaus detailierte Hinweise, um die Verfahren Schritt für Schritt in ein Programmpaket umzusetzen. In zahlreichen farbigen Abbildungen werden Simulationsergebnisse für eine Reihe von Anwendungen präsentiert.
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Numerik partieller Differentialgleichungen

Author: Christian Großmann,Hans-Görg Roos

Publisher: Springer-Verlag

ISBN: 3322967522

Category: Mathematics

Page: 477

View: 2763

"Die Numerik partieller Differentialgleichungen wird hier in relativ weitem Umfang vorgeführt: es beginnt bei der Diskretisierung der ursprünglichen Gleichungen, es werden Fragen der Konsistenz und Stabilität behandelt, und auch Fragen der zweckmäßigen Lösung der entstehenden Gleichungen werden nicht wie sonst in vergleichbaren Büchern verschiedentlich, zur Seite geschoben." Monatshefte für Mathematik. H.Muthsam, Wien
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Numerische Methoden der Technischen Akustik

Author: Gerhard Müller,Michael Möser

Publisher: Springer-Verlag

ISBN: 3662554097

Category: Technology & Engineering

Page: 36

View: 7532

Dieser Band der Reihe Fachwissen Technische Akustik behandelt die am weitesten verbreiteten, wellentheoretischen Verfahren der numerischen Akustik. Die Randelementemethode, die Finite-Elemente-Methode und die Ersatzstrahlermethode werden in den Kapiteln ausführlich behandelt. Weitere Methoden wie z. B. Approximationen für hohe Frequenzen, Verfahren der geometrischen Akustik oder die statistische Energieanalyse werden ebenfalls kurz angesprochen.
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Stochastic Integrals

An Introduction

Author: Heinrich von Weizsäcker

Publisher: Springer-Verlag

ISBN: 3663139239

Category: Mathematics

Page: 332

View: 7301

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Handbuch der Physik

Author: Siegfried Flügge

Publisher: N.A

ISBN: N.A

Category: Physics

Page: N.A

View: 6750

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