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Feynman integrals. --- Feynman, Intégrales de --- Feynman, Intégrales de
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Mathematical physics --- Measure theory. Mathematical integration --- Feynman integrals --- Function spaces --- Feynman, Intégrales de --- Espaces fonctionnels --- Feynman, Intégrales de --- Feynman integrals. --- Function spaces. --- Espaces fonctionnels. --- Feynman, Intégrales de.
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Functional analysis --- Feynman integrals. --- Calculus, Operational. --- Feynman, Intégrales de --- Calcul symbolique --- Feynman, Intégrales de
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Quantum mechanics. Quantumfield theory --- Discrete mathematics --- Graph theory --- Feynman integrals --- 519.1 --- Feynman diagrams --- Multiple integrals --- Graphs, Theory of --- Theory of graphs --- Combinatorial analysis --- Topology --- Combinatorics. Graph theory --- Extremal problems --- Feynman integrals. --- Graph theory. --- 519.1 Combinatorics. Graph theory --- Feynman, Intégrales de --- Feynman, Intégrales de --- Graphes, Théorie des --- Théorie quantique
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Statistical physics --- Quantum mechanics. Quantumfield theory --- Mathematical physics --- Measure theory. Mathematical integration --- 51-7 --- Mathematical studies and methods in other sciences. Scientific mathematics. Actuarial mathematics. Biometrics. Econometrics etc. --- Feynman integrals. --- 51-7 Mathematical studies and methods in other sciences. Scientific mathematics. Actuarial mathematics. Biometrics. Econometrics etc. --- Feynman, Intégrales de
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Scientists are increasingly finding themselves engaged in research problems that cross the traditional disciplinary lines of physics, chemistry, biology, materials science, and engineering. Because of its broad scope, statistical mechanics is an essential tool for students and more experienced researchers planning to become active in such an interdisciplinary research environment. Powerful computational methods that are based in statistical mechanics allow complex systems to be studied at an unprecedented level of detail. This book synthesizes the underlying theory of statistical mechanics with the computational techniques and algorithms used to solve real-world problems and provides readers with a solid foundation in topics that reflect the modern landscape of statistical mechanics. Topics covered include detailed reviews of classical and quantum mechanics, in-depth discussions of the equilibrium ensembles and the use of molecular dynamics and Monte Carlo to sample classical and quantum ensemble distributions, Feynman path integrals, classical and quantum linear-response theory, nonequilibrium molecular dynamics, the Langevin and generalized Langevin equations, critical phenomena, techniques for free energy calculations, machine learning models, and the use of these models in statistical mechanics applications. The book is structured such that the theoretical underpinnings of each topic are covered side by side with computational methods used for practical implementation of the theoretical concepts.
Statistical mechanics. --- Statistical physics. --- Quantum theory. --- Molecular dynamics --- Monte Carlo method. --- Langevin equations. --- Feynman integrals. --- Critical phenomena (Physics) --- Mécanique statistique. --- Physique statistique. --- Dynamique moléculaire. --- Bioinformatique. --- Thermodynamique. --- Théorie quantique. --- Monte-Carlo, Méthode de. --- Langevin, Équation de. --- Feynman, Intégrales de. --- Phénomènes critiques (physique) --- Manuels d'enseignement supérieur. --- Simulation methods --- Mécanique statistique. --- Dynamique moléculaire. --- Théorie quantique. --- Monte-Carlo, Méthode de. --- Langevin, Équation de. --- Feynman, Intégrales de. --- Phénomènes critiques (physique) --- Manuels d'enseignement supérieur.
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Algebraic topology --- Discrete mathematics --- Graph theory --- Electric networks --- 515.14 --- Feynman integrals --- Picard-Lefschetz theory --- Lefschetz theorem, Picard --- -Lefschetz theory, Picard --- -Picard-Lefschetz theorem --- Geometry, Algebraic --- Graphs, Theory of --- Theory of graphs --- Combinatorial analysis --- Topology --- Feynman diagrams --- Multiple integrals --- Network theory --- Networks, Electric --- Electric circuits --- Electric lines --- Electric power distribution --- System analysis --- Extremal problems --- Algebraic topology. --- Electric networks. --- Feynman integrals. --- Graph theory. --- Picard-Lefschetz theory. --- 515.14 Algebraic topology --- Feynman, Intégrales de --- Réseaux électriques (circuits) --- Graphes, Théorie des --- Topologie algébrique --- Feynman, Intégrales de --- Graphes, Théorie des --- Réseaux électriques (circuits) --- Topologie algébrique
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Mathematical optimization. --- Mathematical physics. --- Numerical methods of optimisation --- 51-7 --- 51-7 Mathematical studies and methods in other sciences. Scientific mathematics. Actuarial mathematics. Biometrics. Econometrics etc. --- Mathematical studies and methods in other sciences. Scientific mathematics. Actuarial mathematics. Biometrics. Econometrics etc. --- Calculus of variations --- Calcul des variations --- Numerical analysis --- Analyse numérique --- Feynman integrals. --- Feynman, Intégrales de --- Analyse numérique. --- Analyse mathématique --- Mathematical analysis --- Analyse fonctionnelle non linéaire --- Programmation (mathématiques) --- Feynman, Intégrales de --- Physique mathématique --- Théorie quantique des champs --- Fonctions generalisees --- Groupes topologiques --- Scattering --- Mecanique statistique --- Representation des groupes --- Representation --- Application a la physique --- Analyse fonctionnelle non linéaire --- Analyse mathématique --- Analyse numérique --- Programmation (mathématiques)
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Feynman path integrals, suggested heuristically by Feynman in the 40s, have become the basis of much of contemporary physics, from non-relativistic quantum mechanics to quantum fields, including gauge fields, gravitation, cosmology. Recently ideas based on Feynman path integrals have also played an important role in areas of mathematics like low-dimensional topology and differential geometry, algebraic geometry, infinite-dimensional analysis and geometry, and number theory. The 2nd edition of LNM 523 is based on the two first authors' mathematical approach of this theory presented in its 1st edition in 1976. To take care of the many developments since then, an entire new chapter on the current forefront of research has been added. Except for this new chapter and the correction of a few misprints, the basic material and presentation of the first edition has been maintained. At the end of each chapter the reader will also find notes with further bibliographical information.
Feynman integrals. --- Feynman, Intégrales de --- Feynman integrals --- Calculus --- Mathematical Theory --- Atomic Physics --- Physics --- Mathematics --- Physical Sciences & Mathematics --- Mathematics. --- Functional analysis. --- Global analysis (Mathematics). --- Manifolds (Mathematics). --- Integral equations. --- Measure theory. --- Operator theory. --- Probabilities. --- Integral Equations. --- Measure and Integration. --- Functional Analysis. --- Operator Theory. --- Probability Theory and Stochastic Processes. --- Global Analysis and Analysis on Manifolds. --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Functional analysis --- Lebesgue measure --- Measurable sets --- Measure of a set --- Algebraic topology --- Integrals, Generalized --- Measure algebras --- Rings (Algebra) --- Equations, Integral --- Functional equations --- Geometry, Differential --- Topology --- Analysis, Global (Mathematics) --- Differential topology --- Functions of complex variables --- Geometry, Algebraic --- Functional calculus --- Calculus of variations --- Integral equations --- Math --- Science --- Feynman diagrams --- Multiple integrals --- Distribution (Probability theory. --- Global analysis. --- Global analysis (Mathematics) --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities
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