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In 1993, M. Kontsevich proposed a conceptual framework for explaining the phenomenon of mirror symmetry. Mirror symmetry had been discovered by physicists in string theory as a duality between families of three-dimensional Calabi–Yau manifolds. Kontsevich's proposal uses Fukaya's construction of the A∞-category of Lagrangian submanifolds on the symplectic side and the derived category of coherent sheaves on the complex side. The theory of mirror symmetry was further enhanced by physicists in the language of D-branes and also by Strominger–Yau–Zaslow in the geometric set-up of (special) Lagrangian torus fibrations. It rapidly expanded its scope across from geometry, topology, algebra to physics. In this volume, leading experts in the field explore recent developments in relation to homological mirror symmetry, Floer theory, D-branes and Gromov–Witten invariants. Kontsevich-Soibelman describe their solution to the mirror conjecture on the abelian variety based on the deformation theory of A∞-categories, and Ohta describes recent work on the Lagrangian intersection Floer theory by Fukaya–Oh–Ohta–Ono which takes an important step towards a rigorous construction of the A∞-category. There follow a number of contributions on the homological mirror symmetry, D-branes and the Gromov–Witten invariants, e.g. Getzler shows how the Toda conjecture follows from recent work of Givental, Okounkov and Pandharipande. This volume provides a timely presentation of the important developments of recent years in this rapidly growing field.

Mirror symmetry --- Symplectic groups --- Groups, Symplectic --- Linear algebraic groups --- Symmetry (Physics)

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This book provides an accessible overview concerning the stochastic numerical methods inheriting long-time dynamical behaviours of finite and infinite-dimensional stochastic Hamiltonian systems. The long-time dynamical behaviours under study involve symplectic structure, invariants, ergodicity and invariant measure. The emphasis is placed on the systematic construction and the probabilistic superiority of stochastic symplectic methods, which preserve the geometric structure of the stochastic flow of stochastic Hamiltonian systems. The problems considered in this book are related to several fascinating research hotspots: numerical analysis, stochastic analysis, ergodic theory, stochastic ordinary and partial differential equations, and rough path theory. This book will appeal to researchers who are interested in these topics.

Numerical analysis. --- Dynamical systems. --- Probabilities. --- Numerical Analysis. --- Dynamical Systems. --- Probability Theory. --- Sistemes hamiltonians --- Equacions diferencials estocàstiques --- Grups simplèctics --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Mathematical analysis --- Grups algebraics lineals --- Anàlisi numèrica --- Equació de Fokker-Planck --- Mecànica de Hamilton --- Mecànica hamiltoniana --- Sistemes de Hamilton --- Sistemes dinàmics de Hamilton --- Sistemes dinàmics diferenciables --- Equacions de Hamilton-Jacobi --- Hamiltonian systems. --- Stochastic differential equations. --- Symplectic groups. --- Groups, Symplectic --- Linear algebraic groups --- Differential equations --- Fokker-Planck equation --- Hamiltonian dynamical systems --- Systems, Hamiltonian --- Differentiable dynamical systems