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For hundreds of years, the study of elliptic curves has played a central role in mathematics. The past century in particular has seen huge progress in this study, from Mordell's theorem in 1922 to the work of Wiles and Taylor-Wiles in 1994. Nonetheless, there remain many fundamental questions where we do not even know what sort of answers to expect. This book explores two of them: What is the average rank of elliptic curves, and how does the rank vary in various kinds of families of elliptic curves? Nicholas Katz answers these questions for families of ''big'' twists of elliptic curves in the function field case (with a growing constant field). The monodromy-theoretic methods he develops turn out to apply, still in the function field case, equally well to families of big twists of objects of all sorts, not just to elliptic curves. The leisurely, lucid introduction gives the reader a clear picture of what is known and what is unknown at present, and situates the problems solved in this book within the broader context of the overall study of elliptic curves. The book's technical core makes use of, and explains, various advanced topics ranging from recent results in finite group theory to the machinery of l-adic cohomology and monodromy. Twisted L-Functions and Monodromy is essential reading for anyone interested in number theory and algebraic geometry.

L-functions. --- Monodromy groups. --- Functions, L --- -L-functions. --- Group theory --- -Number theory --- L-functions --- Monodromy groups --- Abelian variety. --- Absolute continuity. --- Addition. --- Affine space. --- Algebraically closed field. --- Ambient space. --- Average. --- Betti number. --- Birch and Swinnerton-Dyer conjecture. --- Blowing up. --- Codimension. --- Coefficient. --- Computation. --- Conjecture. --- Conjugacy class. --- Convolution. --- Critical value. --- Differential geometry of surfaces. --- Dimension (vector space). --- Dimension. --- Direct sum. --- Divisor (algebraic geometry). --- Divisor. --- Eigenvalues and eigenvectors. --- Elliptic curve. --- Equation. --- Equidistribution theorem. --- Existential quantification. --- Factorization. --- Finite field. --- Finite group. --- Finite set. --- Flat map. --- Fourier transform. --- Function field. --- Functional equation. --- Goursat's lemma. --- Ground field. --- Group representation. --- Hyperplane. --- Hypersurface. --- Integer matrix. --- Integer. --- Irreducible component. --- Irreducible polynomial. --- Irreducible representation. --- J-invariant. --- K3 surface. --- L-function. --- Lebesgue measure. --- Lefschetz pencil. --- Level of measurement. --- Lie algebra. --- Limit superior and limit inferior. --- Minimal polynomial (field theory). --- Modular form. --- Monodromy. --- Morphism. --- Numerical analysis. --- Orthogonal group. --- Percentage. --- Polynomial. --- Prime number. --- Probability measure. --- Quadratic function. --- Quantity. --- Quotient space (topology). --- Representation theory. --- Residue field. --- Riemann hypothesis. --- Root of unity. --- Scalar (physics). --- Set (mathematics). --- Sheaf (mathematics). --- Subgroup. --- Summation. --- Symmetric group. --- System of imprimitivity. --- Theorem. --- Trivial representation. --- Zariski topology.

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This volume studies the dynamics of iterated holomorphic mappings from a Riemann surface to itself, concentrating on the classical case of rational maps of the Riemann sphere. This subject is large and rapidly growing. These lectures are intended to introduce some key ideas in the field, and to form a basis for further study. The reader is assumed to be familiar with the rudiments of complex variable theory and of two-dimensional differential geometry, as well as some basic topics from topology. This third edition contains a number of minor additions and improvements: A historical survey has been added, the definition of Lattés map has been made more inclusive, and the écalle-Voronin theory of parabolic points is described. The résidu itératif is studied, and the material on two complex variables has been expanded. Recent results on effective computability have been added, and the references have been expanded and updated. Written in his usual brilliant style, the author makes difficult mathematics look easy. This book is a very accessible source for much of what has been accomplished in the field.

Functions of complex variables --- Holomorphic mappings --- Riemann surfaces --- Fonctions d'une variable complexe --- Applications holomorphes --- Riemann, surfaces de --- Holomorphic mappings. --- Mappings, Holomorphic --- Functions of complex variables. --- Riemann surfaces. --- Surfaces, Riemann --- Functions --- Functions of several complex variables --- Mappings (Mathematics) --- Complex variables --- Elliptic functions --- Functions of real variables --- Absolute value. --- Addition. --- Algebraic equation. --- Attractor. --- Automorphism. --- Beltrami equation. --- Blaschke product. --- Boundary (topology). --- Branched covering. --- Coefficient. --- Compact Riemann surface. --- Compact space. --- Complex analysis. --- Complex number. --- Complex plane. --- Computation. --- Connected component (graph theory). --- Connected space. --- Constant function. --- Continued fraction. --- Continuous function. --- Coordinate system. --- Corollary. --- Covering space. --- Cross-ratio. --- Derivative. --- Diagram (category theory). --- Diameter. --- Diffeomorphism. --- Differentiable manifold. --- Disjoint sets. --- Disjoint union. --- Disk (mathematics). --- Division by zero. --- Equation. --- Euler characteristic. --- Existential quantification. --- Exponential map (Lie theory). --- Fundamental group. --- Harmonic function. --- Holomorphic function. --- Homeomorphism. --- Hyperbolic geometry. --- Inequality (mathematics). --- Integer. --- Inverse function. --- Irrational rotation. --- Iteration. --- Jordan curve theorem. --- Julia set. --- Lebesgue measure. --- Lecture. --- Limit point. --- Line segment. --- Linear map. --- Linearization. --- Mandelbrot set. --- Mathematical analysis. --- Maximum modulus principle. --- Metric space. --- Monotonic function. --- Montel's theorem. --- Normal family. --- Open set. --- Orbifold. --- Parameter space. --- Parameter. --- Periodic point. --- Point at infinity. --- Polynomial. --- Power series. --- Proper map. --- Quadratic function. --- Rational approximation. --- Rational function. --- Rational number. --- Real number. --- Riemann sphere. --- Riemann surface. --- Root of unity. --- Rotation number. --- Schwarz lemma. --- Scientific notation. --- Sequence. --- Simply connected space. --- Special case. --- Subgroup. --- Subsequence. --- Subset. --- Summation. --- Tangent space. --- Theorem. --- Topological space. --- Topology. --- Uniform convergence. --- Uniformization theorem. --- Unit circle. --- Unit disk. --- Upper half-plane. --- Winding number.

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In 1920, Pierre Fatou expressed the conjecture that--except for special cases--all critical points of a rational map of the Riemann sphere tend to periodic orbits under iteration. This conjecture remains the main open problem in the dynamics of iterated maps. For the logistic family x- ax(1-x), it can be interpreted to mean that for a dense set of parameters "a," an attracting periodic orbit exists. The same question appears naturally in science, where the logistic family is used to construct models in physics, ecology, and economics. In this book, Jacek Graczyk and Grzegorz Swiatek provide a rigorous proof of the Real Fatou Conjecture. In spite of the apparently elementary nature of the problem, its solution requires advanced tools of complex analysis. The authors have written a self-contained and complete version of the argument, accessible to someone with no knowledge of complex dynamics and only basic familiarity with interval maps. The book will thus be useful to specialists in real dynamics as well as to graduate students.

Geodesics (Mathematics) --- Polynomials. --- Mappings (Mathematics) --- Maps (Mathematics) --- Functions --- Functions, Continuous --- Topology --- Transformations (Mathematics) --- Algebra --- Geometry, Differential --- Global analysis (Mathematics) --- Mathematics --- Absolute value. --- Affine transformation. --- Algebraic function. --- Analytic continuation. --- Analytic function. --- Arithmetic. --- Automorphism. --- Big O notation. --- Bounded set (topological vector space). --- C0. --- Calculation. --- Canonical map. --- Change of variables. --- Chebyshev polynomials. --- Combinatorics. --- Commutative property. --- Complex number. --- Complex plane. --- Complex quadratic polynomial. --- Conformal map. --- Conjecture. --- Conjugacy class. --- Conjugate points. --- Connected component (graph theory). --- Connected space. --- Continuous function. --- Corollary. --- Covering space. --- Critical point (mathematics). --- Dense set. --- Derivative. --- Diffeomorphism. --- Dimension. --- Disjoint sets. --- Disjoint union. --- Disk (mathematics). --- Equicontinuity. --- Estimation. --- Existential quantification. --- Fibonacci. --- Functional equation. --- Fundamental domain. --- Generalization. --- Great-circle distance. --- Hausdorff distance. --- Holomorphic function. --- Homeomorphism. --- Homotopy. --- Hyperbolic function. --- Imaginary number. --- Implicit function theorem. --- Injective function. --- Integer. --- Intermediate value theorem. --- Interval (mathematics). --- Inverse function. --- Irreducible polynomial. --- Iteration. --- Jordan curve theorem. --- Julia set. --- Limit of a sequence. --- Linear map. --- Local diffeomorphism. --- Mathematical induction. --- Mathematical proof. --- Maxima and minima. --- Meromorphic function. --- Moduli (physics). --- Monomial. --- Monotonic function. --- Natural number. --- Neighbourhood (mathematics). --- Open set. --- Parameter. --- Periodic function. --- Periodic point. --- Phase space. --- Point at infinity. --- Polynomial. --- Projection (mathematics). --- Quadratic function. --- Quadratic. --- Quasiconformal mapping. --- Renormalization. --- Riemann sphere. --- Riemann surface. --- Schwarzian derivative. --- Scientific notation. --- Subsequence. --- Theorem. --- Theory. --- Topological conjugacy. --- Topological entropy. --- Topology. --- Union (set theory). --- Unit circle. --- Unit disk. --- Upper and lower bounds. --- Upper half-plane. --- Z0.

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Everybody knows that mathematics is indispensable to physics--imagine where we'd be today if Einstein and Newton didn't have the math to back up their ideas. But how many people realize that physics can be used to produce many astonishing and strikingly elegant solutions in mathematics? Mark Levi shows how in this delightful book, treating readers to a host of entertaining problems and mind-bending puzzlers that will amuse and inspire their inner physicist.Levi turns math and physics upside down, revealing how physics can simplify proofs and lead to quicker solutions and new theorems, and how physical solutions can illustrate why results are true in ways lengthy mathematical calculations never can. Did you know it's possible to derive the Pythagorean theorem by spinning a fish tank filled with water? Or that soap film holds the key to determining the cheapest container for a given volume? Or that the line of best fit for a data set can be found using a mechanical contraption made from a rod and springs? Levi demonstrates how to use physical intuition to solve these and other fascinating math problems. More than half the problems can be tackled by anyone with precalculus and basic geometry, while the more challenging problems require some calculus. This one-of-a-kind book explains physics and math concepts where needed, and includes an informative appendix of physical principles.The Mathematical Mechanic will appeal to anyone interested in the little-known connections between mathematics and physics and how both endeavors relate to the world around us.

Mathematical physics. --- Problem solving. --- MATHEMATICS / General. --- Methodology --- Psychology --- Decision making --- Executive functions (Neuropsychology) --- Physical mathematics --- Physics --- Mathematics --- Addition. --- Analytic function. --- Angular acceleration. --- Angular velocity. --- Axle. --- Calculation. --- Capacitor. --- Cartesian coordinate system. --- Cauchy's integral formula. --- Center of mass (relativistic). --- Center of mass. --- Centroid. --- Ceva's theorem. --- Clockwise. --- Complex analysis. --- Complex number. --- Conservation of energy. --- Convex curve. --- Curvature. --- Curve. --- Cylinder (geometry). --- Derivative. --- Diameter. --- Differential geometry. --- Dimension. --- Division by zero. --- Dot product. --- Eigenvalues and eigenvectors. --- Electric current. --- Equation. --- Euler's formula. --- Euler–Lagrange equation. --- Fermat's principle. --- Friction. --- Fundamental theorem of calculus. --- Gaussian curvature. --- Generating function. --- Geodesic curvature. --- Geometry. --- Gravity. --- Green's theorem. --- Heat flux. --- Hinge. --- Hooke's law. --- Horizontal plane. --- Hypotenuse. --- Inductance. --- Instant. --- Kinetic energy. --- Line integral. --- Linear map. --- Mathematics. --- Mechanics. --- Moment of inertia. --- Newton's laws of motion. --- Normal (geometry). --- Ohm's law. --- Optics. --- Partial derivative. --- Potential energy. --- Proportionality (mathematics). --- Pythagorean theorem. --- Quadratic function. --- Quantity. --- Rectangle. --- Resistor. --- Right angle. --- Right triangle. --- Second law of thermodynamics. --- Semicircle. --- Series and parallel circuits. --- Sign (mathematics). --- Slinky. --- Snell's law. --- Soap bubble. --- Soap film. --- Special case. --- Spring (device). --- Stiffness. --- Summation. --- Surface area. --- Surface tension. --- Tangent space. --- Tangent. --- Telescope. --- Theorem. --- Thought experiment. --- Tractrix. --- Trapezoid. --- Trigonometric functions. --- Two-dimensional gas. --- Uncertainty principle. --- Unit circle. --- Unit vector. --- Vacuum. --- Variable (mathematics). --- Vector field. --- Voltage drop. --- Voltage. --- Wavefront.

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Research on interior-point methods (IPMs) has dominated the field of mathematical programming for the last two decades. Two contrasting approaches in the analysis and implementation of IPMs are the so-called small-update and large-update methods, although, until now, there has been a notorious gap between the theory and practical performance of these two strategies. This book comes close to bridging that gap, presenting a new framework for the theory of primal-dual IPMs based on the notion of the self-regularity of a function.The authors deal with linear optimization, nonlinear complementarity problems, semidefinite optimization, and second-order conic optimization problems. The framework also covers large classes of linear complementarity problems and convex optimization. The algorithm considered can be interpreted as a path-following method or a potential reduction method. Starting from a primal-dual strictly feasible point, the algorithm chooses a search direction defined by some Newton-type system derived from the self-regular proximity. The iterate is then updated, with the iterates staying in a certain neighborhood of the central path until an approximate solution to the problem is found. By extensively exploring some intriguing properties of self-regular functions, the authors establish that the complexity of large-update IPMs can come arbitrarily close to the best known iteration bounds of IPMs.Researchers and postgraduate students in all areas of linear and nonlinear optimization will find this book an important and invaluable aid to their work.

Interior-point methods. --- Mathematical optimization. --- Programming (Mathematics). --- Mathematical optimization --- Interior-point methods --- Programming (Mathematics) --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Operations Research --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Operations research --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Simulation methods --- System analysis --- 519.85 --- 681.3*G16 --- 681.3*G16 Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- Optimization: constrained optimization; gradient methods; integer programming; least squares methods; linear programming; nonlinear programming (Numericalanalysis) --- 519.85 Mathematical programming --- Accuracy and precision. --- Algorithm. --- Analysis of algorithms. --- Analytic function. --- Associative property. --- Barrier function. --- Binary number. --- Block matrix. --- Combination. --- Combinatorial optimization. --- Combinatorics. --- Complexity. --- Conic optimization. --- Continuous optimization. --- Control theory. --- Convex optimization. --- Delft University of Technology. --- Derivative. --- Differentiable function. --- Directional derivative. --- Division by zero. --- Dual space. --- Duality (mathematics). --- Duality gap. --- Eigenvalues and eigenvectors. --- Embedding. --- Equation. --- Estimation. --- Existential quantification. --- Explanation. --- Feasible region. --- Filter design. --- Function (mathematics). --- Implementation. --- Instance (computer science). --- Invertible matrix. --- Iteration. --- Jacobian matrix and determinant. --- Jordan algebra. --- Karmarkar's algorithm. --- Karush–Kuhn–Tucker conditions. --- Line search. --- Linear complementarity problem. --- Linear function. --- Linear programming. --- Lipschitz continuity. --- Local convergence. --- Loss function. --- Mathematician. --- Mathematics. --- Matrix function. --- McMaster University. --- Monograph. --- Multiplication operator. --- Newton's method. --- Nonlinear programming. --- Nonlinear system. --- Notation. --- Operations research. --- Optimal control. --- Optimization problem. --- Parameter (computer programming). --- Parameter. --- Pattern recognition. --- Polyhedron. --- Polynomial. --- Positive semidefinite. --- Positive-definite matrix. --- Quadratic function. --- Requirement. --- Result. --- Scientific notation. --- Second derivative. --- Self-concordant function. --- Sensitivity analysis. --- Sign (mathematics). --- Signal processing. --- Simplex algorithm. --- Simultaneous equations. --- Singular value. --- Smoothness. --- Solution set. --- Solver. --- Special case. --- Subset. --- Suggestion. --- Technical report. --- Theorem. --- Theory. --- Time complexity. --- Two-dimensional space. --- Upper and lower bounds. --- Variable (computer science). --- Variable (mathematics). --- Variational inequality. --- Variational principle. --- Without loss of generality. --- Worst-case complexity. --- Yurii Nesterov. --- Mathematical Optimization --- Mathematics --- Programming (mathematics)