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The first comprehensive graduate-level introduction to stochastic thermodynamics
Stochastic thermodynamics is a well-defined subfield of statistical physics that aims to interpret thermodynamic concepts for systems ranging in size from a few to hundreds of nanometers, the behavior of which is inherently random due to thermal fluctuations. This growing field therefore describes the nonequilibrium dynamics of small systems, such as artificial nanodevices and biological molecular machines, which are of increasing scientific and technological relevance. This textbook provides an up-to-date pedagogical introduction to stochastic thermodynamics, guiding readers from basic concepts in statistical physics, probability theory, and thermodynamics to the most recent developments in the field. Gradually building up to more advanced material, the authors consistentlyThe first comprehensive graduate-level introduction to stochastic thermodynamics Stochastic thermodynamics is a well-defined subfield of statistical physics that aims to interpret thermodynamic concepts for systems ranging in size from a few to hundreds of nanometers, the behavior of which is
An Introduction to Statistical Mechanics and Thermodynamics returns with a second edition which includes new chapters, further explorations, and updated information into the study of statistical mechanics and thermal dynamics. The first part of the book derives the entropy of the classical ideal
Provides a quick, but very readable introduction to stochastic differential equations-that is, to differential equations subject to additive 'white noise' and related random disturbances. The exposition is strongly focused upon the interplay between probabilistic intuition and mathematical
Provides a lively and accessible introduction to the numerical solution of stochastic differential equations with the aim of making this subject available to the widest possible readership. The book presents an outline of the underlying convergence and stability theory while avoiding technical
An introduction to the basic theory of stochastic calculus and its applications. Examples are given throughout the text, in order to motivate and illustrate the theory and show its importance for many applications in e.g. economics, biology and physics. The basic idea of the presentation is to
This book is an introduction to stochastic analysis and quantitative finance; Stochastic Analysis for Finance with Simulations is designed for readers who want to have a deeper understanding of the delicate theory of quantitative finance by doing computer simulations in addition to theoretical
An Introduction to Mathematical
Defines quadratic variation of a square integrable martingaleDemonstrates pathwise formulae for the stochastic integralUses the technique of random time change to study the solution of a stochastic differential equationStudies the predictable increasing process to introduce predictable stopping
This book presents basic stochastic processes, stochastic calculus including L vy processes on one hand, and Markov and Semi Markov models on the other. From the financial point of view, essential concepts such as the Black and Scholes model, VaR indicators, actuarial evaluation, market values,
Kaminski-Jensen is the first text to bring together thermodynamics, fluid mechanics, and heat transfer in an integrated manner, giving students the fullest possible understanding of their interconnectedness. The three topics are introduced early in the text, allowing for applications across these
Learn How to Program Stochastic ModelsHighly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce
This textbook presents a concise yet detailed introduction to quantum physics. Concise, because it condenses the essentials to a few principles. Detailed, because these few principles - necessarily rather abstract - are illustrated by several telling examples. A fairly complete overview of the
This textbook introduces thermodynamics with a modern approach, starting from four fundamental physical facts (the atomic nature of matter, the indistinguishability of atoms and molecules of the same species, the uncertainty principle, and the existence of equilibrium states) and analyzing the
This book differs from other thermodynamics texts in its objective which is to provide engineers with the concepts, tools, and experience needed to solve practical real-world energy problems. The presentation integrates computer tools (e.g., EES) with thermodynamic concepts to allow engineering
This second edition of Introduction to Cosmology is an exciting update of an award-winning textbook. It is aimed primarily at advanced undergraduate students in physics and astronomy, but is also useful as a supplementary text at higher levels. It explains modern cosmological concepts, such as dark
An Introduction to Modern Astrophysics is a comprehensive, well-organized and engaging text covering every major area of modern astrophysics, from the solar system and stellar astronomy to galactic and extragalactic astrophysics, and cosmology. Designed to provide students with a working knowledge
A self-contained introduction to abstract interpretation-based static analysis, an essential resource for students, developers, and users.Static program analysis, or static analysis, aims to discover semantic properties of programs without running them. It plays an important role in all phases of
An essential guide to creating
Modelling with the Itô integral or stochastic differential equations has become increasingly important in various applied fields, including physics, biology, chemistry and finance. However, stochastic calculus is based on a deep mathematical theory.This book is suitable for the reader without a
Markov processes.- Stochastic Differential Equations and Martingale Problems.- Stochastic Filtering.- Static Markov Bridges and Enlargement of Filtrations.- Dynamic Bridges.- Financial markets with informational asymmetries and equilibrium.- Kyle-Back model with dynamic information: no default