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The classic book that shares the enjoyment of mathematics with readers of all skill levelsWhat is so special about the number 30? Do the prime numbers go on forever? Are there more whole numbers than even numbers? The Enjoyment of Math explores these and other captivating problems and puzzles, introducing readers to some of the most fundamental ideas in mathematics. Written by two eminent mathematicians and requiring only a background in plane geometry and elementary algebra, this delightful book covers topics such as the theory of sets, the four-color problem, regular polyhedrons, Euler’s proof of the infinitude of prime numbers, and curves of constant breadth. Along the way, it discusses the history behind the problems, carefully explaining how each has arisen and, in some cases, how to resolve it. With an incisive foreword by Alex Kontorovich, this Princeton Science Library edition shares the enjoyment of math with a new generation of readers.

Mathematics --- Mathematical recreations. --- Mathematical puzzles --- Number games --- Recreational mathematics --- Recreations, Mathematical --- Puzzles --- Scientific recreations --- Games in mathematics education --- Magic squares --- Magic tricks in mathematics education --- Arbitrarily large. --- Arithmetic. --- Big O notation. --- Binomial theorem. --- Bonse's inequality. --- Circumference. --- Coefficient. --- Combination. --- Complete theory. --- Computation. --- Coprime integers. --- Diameter. --- Divisor. --- Equilateral triangle. --- Euler's formula. --- Euler's theorem. --- Exterior (topology). --- Factorial. --- Factorization. --- Fermat's Last Theorem. --- Fermat's theorem. --- Fourth power. --- Fractional part. --- Geometric mean. --- Geometric series. --- Geometry. --- Hypotenuse. --- Integer factorization. --- Intersection (set theory). --- Irrational number. --- Line segment. --- Logarithm. --- Long division. --- Mathematical induction. --- Mathematics. --- Metric space. --- Natural number. --- Non-Euclidean geometry. --- Number theory. --- Parallelogram. --- Parity (mathematics). --- Pedal triangle. --- Perfect number. --- Polyhedron. --- Power of 10. --- Prime factor. --- Prime number theorem. --- Prime number. --- Prime power. --- Pure mathematics. --- Pythagorean theorem. --- Rational number. --- Rectangle. --- Regular polygon. --- Regular polyhedron. --- Remainder. --- Reuleaux triangle. --- Rhomboid. --- Rhombus. --- Right angle. --- Right triangle. --- Scientific notation. --- Sign (mathematics). --- Special case. --- Straightedge. --- Summation. --- Theorem. --- Transfinite number. --- Variable (mathematics). --- Waring's problem.

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Splines, both interpolatory and smoothing, have a long and rich history that has largely been application driven. This book unifies these constructions in a comprehensive and accessible way, drawing from the latest methods and applications to show how they arise naturally in the theory of linear control systems. Magnus Egerstedt and Clyde Martin are leading innovators in the use of control theoretic splines to bring together many diverse applications within a common framework. In this book, they begin with a series of problems ranging from path planning to statistics to approximation. Using the tools of optimization over vector spaces, Egerstedt and Martin demonstrate how all of these problems are part of the same general mathematical framework, and how they are all, to a certain degree, a consequence of the optimization problem of finding the shortest distance from a point to an affine subspace in a Hilbert space. They cover periodic splines, monotone splines, and splines with inequality constraints, and explain how any finite number of linear constraints can be added. This book reveals how the many natural connections between control theory, numerical analysis, and statistics can be used to generate powerful mathematical and analytical tools. This book is an excellent resource for students and professionals in control theory, robotics, engineering, computer graphics, econometrics, and any area that requires the construction of curves based on sets of raw data.

Interpolation. --- Smoothing (Numerical analysis) --- Smoothing (Statistics) --- Curve fitting. --- Splines. --- Spline theory. --- Spline functions --- Approximation theory --- Interpolation --- Joints (Engineering) --- Mechanical movements --- Harmonic drives --- Fitting, Curve --- Numerical analysis --- Least squares --- Statistics --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Graphic methods --- Accuracy and precision. --- Affine space. --- Affine variety. --- Algorithm. --- Approximation. --- Arbitrarily large. --- B-spline. --- Banach space. --- Bernstein polynomial. --- Bifurcation theory. --- Big O notation. --- Birkhoff interpolation. --- Boundary value problem. --- Bézier curve. --- Chaos theory. --- Computation. --- Computational problem. --- Condition number. --- Constrained optimization. --- Continuous function (set theory). --- Continuous function. --- Control function (econometrics). --- Control theory. --- Controllability. --- Convex optimization. --- Convolution. --- Cubic Hermite spline. --- Data set. --- Derivative. --- Differentiable function. --- Differential equation. --- Dimension (vector space). --- Directional derivative. --- Discrete mathematics. --- Dynamic programming. --- Equation. --- Estimation. --- Filtering problem (stochastic processes). --- Gaussian quadrature. --- Gradient descent. --- Gramian matrix. --- Growth curve (statistics). --- Hermite interpolation. --- Hermite polynomials. --- Hilbert projection theorem. --- Hilbert space. --- Initial condition. --- Initial value problem. --- Integral equation. --- Iterative method. --- Karush–Kuhn–Tucker conditions. --- Kernel method. --- Lagrange polynomial. --- Law of large numbers. --- Least squares. --- Linear algebra. --- Linear combination. --- Linear filter. --- Linear map. --- Mathematical optimization. --- Mathematics. --- Maxima and minima. --- Monotonic function. --- Nonlinear programming. --- Nonlinear system. --- Normal distribution. --- Numerical analysis. --- Numerical stability. --- Optimal control. --- Optimization problem. --- Ordinary differential equation. --- Orthogonal polynomials. --- Parameter. --- Piecewise. --- Pointwise. --- Polynomial interpolation. --- Polynomial. --- Probability distribution. --- Quadratic programming. --- Random variable. --- Rate of convergence. --- Ratio test. --- Riccati equation. --- Simpson's rule. --- Simultaneous equations. --- Smoothing spline. --- Smoothing. --- Smoothness. --- Special case. --- Spline (mathematics). --- Spline interpolation. --- Statistic. --- Stochastic calculus. --- Stochastic. --- Telemetry. --- Theorem. --- Trapezoidal rule. --- Waypoint. --- Weight function. --- Without loss of generality.

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This book develops a general analysis and synthesis framework for impulsive and hybrid dynamical systems. Such a framework is imperative for modern complex engineering systems that involve interacting continuous-time and discrete-time dynamics with multiple modes of operation that place stringent demands on controller design and require implementation of increasing complexity--whether advanced high-performance tactical fighter aircraft and space vehicles, variable-cycle gas turbine engines, or air and ground transportation systems. Impulsive and Hybrid Dynamical Systems goes beyond similar treatments by developing invariant set stability theorems, partial stability, Lagrange stability, boundedness, ultimate boundedness, dissipativity theory, vector dissipativity theory, energy-based hybrid control, optimal control, disturbance rejection control, and robust control for nonlinear impulsive and hybrid dynamical systems. A major contribution to mathematical system theory and control system theory, this book is written from a system-theoretic point of view with the highest standards of exposition and rigor. It is intended for graduate students, researchers, and practitioners of engineering and applied mathematics as well as computer scientists, physicists, and other scientists who seek a fundamental understanding of the rich dynamical behavior of impulsive and hybrid dynamical systems.

Automatic control. --- Control theory. --- Dynamics. --- Discrete-time systems. --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Dynamics --- Machine theory --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- DES (System analysis) --- Discrete event systems --- Sampled-data systems --- Digital control systems --- Discrete mathematics --- System analysis --- Linear time invariant systems --- Actuator. --- Adaptive control. --- Algorithm. --- Amplitude. --- Analog computer. --- Arbitrarily large. --- Asymptote. --- Asymptotic analysis. --- Axiom. --- Balance equation. --- Bode plot. --- Boundedness. --- Calculation. --- Center of mass (relativistic). --- Coefficient of restitution. --- Continuous function. --- Convex set. --- Differentiable function. --- Differential equation. --- Dissipation. --- Dissipative system. --- Dynamical system. --- Dynamical systems theory. --- Energy. --- Equations of motion. --- Equilibrium point. --- Escapement. --- Euler–Lagrange equation. --- Exponential stability. --- Forms of energy. --- Hamiltonian mechanics. --- Hamiltonian system. --- Hermitian matrix. --- Hooke's law. --- Hybrid system. --- Identity matrix. --- Inequality (mathematics). --- Infimum and supremum. --- Initial condition. --- Instability. --- Interconnection. --- Invariance theorem. --- Isolated system. --- Iterative method. --- Jacobian matrix and determinant. --- Lagrangian (field theory). --- Lagrangian system. --- Lagrangian. --- Likelihood-ratio test. --- Limit cycle. --- Limit set. --- Linear function. --- Linearization. --- Lipschitz continuity. --- Lyapunov function. --- Lyapunov stability. --- Mass balance. --- Mathematical optimization. --- Melting. --- Mixture. --- Moment of inertia. --- Momentum. --- Monotonic function. --- Negative feedback. --- Nonlinear programming. --- Nonlinear system. --- Nonnegative matrix. --- Optimal control. --- Ordinary differential equation. --- Orthant. --- Parameter. --- Partial differential equation. --- Passive dynamics. --- Poincaré conjecture. --- Potential energy. --- Proof mass. --- Quantity. --- Rate function. --- Requirement. --- Robust control. --- Second law of thermodynamics. --- Semi-infinite. --- Small-gain theorem. --- Special case. --- Spectral radius. --- Stability theory. --- State space. --- Stiffness. --- Supply (economics). --- Telecommunication. --- Theorem. --- Transpose. --- Uncertainty. --- Uniform boundedness. --- Uniqueness. --- Vector field. --- Vibration. --- Zeroth (software). --- Zeroth law of thermodynamics.

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William Thurston (1946–2012) was one of the great mathematicians of the twentieth century. He was a visionary whose extraordinary ideas revolutionized a broad range of mathematical fields, from foliations, contact structures, and Teichmüller theory to automorphisms of surfaces, hyperbolic geometry, geometrization of 3-manifolds, geometric group theory, and rational maps. In addition, he discovered connections between disciplines that led to astonishing breakthroughs in mathematical understanding as well as the creation of entirely new fields. His far-reaching questions and conjectures led to enormous progress by other researchers. What's Next? brings together many of today's leading mathematicians to describe recent advances and future directions inspired by Thurston's transformative ideas.Including valuable insights from his colleagues and former students, What's Next? discusses Thurston's fundamental contributions to topology, geometry, and dynamical systems and includes many deep and original contributions to the field. This incisive and wide-ranging book also explores how he introduced new ways of thinking about and doing mathematics, innovations that have had a profound and lasting impact on the mathematical community as a whole.

Dynamics. --- Geometry. --- Topology. --- MATHEMATICS / General. --- Analysis situs --- Position analysis --- Rubber-sheet geometry --- Geometry --- Polyhedra --- Set theory --- Algebras, Linear --- Mathematics --- Euclid's Elements --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Thurston, William P., --- Thurston, W. P. --- Arbitrarily large. --- Asymptotic expansion. --- Automorphism. --- Big O notation. --- Braid group. --- Branch point. --- Central series. --- Character variety. --- Characterization (mathematics). --- Cohomology operation. --- Cohomology. --- Commutative property. --- Conjecture. --- Conjugacy class. --- Convex hull. --- Covering space. --- Coxeter group. --- Curvature. --- Dehn's lemma. --- Diagram (category theory). --- Disjoint union. --- Eigenfunction. --- Endomorphism. --- Epimorphism. --- Equivalence class. --- Equivalence relation. --- Euclidean space. --- Extreme point. --- Faithful representation. --- Fiber bundle. --- Free group. --- Free product. --- Fundamental group. --- Geometrization conjecture. --- HNN extension. --- Haar measure. --- Homeomorphism. --- Homotopy. --- Hyperbolic 3-manifold. --- Hyperbolic geometry. --- Hyperbolic manifold. --- Hyperbolic space. --- Hypercube. --- I0. --- Inclusion map. --- Incompressible surface. --- JSJ decomposition. --- Jordan curve theorem. --- Julia set. --- Klein bottle. --- Kleinian group. --- Lebesgue measure. --- Leech lattice. --- Limit point. --- Lyapunov exponent. --- Mahler measure. --- Manifold decomposition. --- Mapping cylinder. --- Marriage theorem. --- Maxima and minima. --- Moduli space. --- Möbius strip. --- Möbius transformation. --- Natural topology. --- Non-Euclidean geometry. --- Non-positive curvature. --- Normal subgroup. --- Open set. --- Orientability. --- Pair of pants (mathematics). --- Perfect group. --- Pleated surface. --- Polynomial. --- Preorder. --- Probability measure. --- Pullback (category theory). --- Pullback (differential geometry). --- Quadric. --- Quasi-isometry. --- Quasiconvex function. --- Rectangle. --- Riemann surface. --- Riemannian manifold. --- Saddle point. --- Sectional curvature. --- Sign (mathematics). --- Simple algebra. --- Simply connected space. --- Special case. --- Subgroup. --- Subset. --- Symplectic geometry. --- Theorem. --- Total order. --- Unit disk. --- Unit sphere. --- Upper and lower bounds. --- Vector bundle.

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High-energy astrophysics involves the study of exceedingly dynamic and energetic phenomena occurring near the most extreme celestial objects known to exist, such as black holes, neutron stars, white dwarfs, and supernova remnants. High-Energy Astrophysics provides graduate and advanced undergraduate students with the most complete, self-contained introduction to the subject available. This textbook covers all the essentials, weaving together the latest theory with the experimental techniques, instrumentation, and observational methods astronomers use to study high-energy radiation from space. Fulvio Melia introduces topics at the forefront of today's research, including relativistic particles, energetic radiation, and accretion disk theory. No other textbook offers such a thorough yet concise treatment of the key aspects of high-energy astrophysics--both theoretical and observational--or delves as deeply into modern detection techniques, satellite systems, and analytical and numerical modeling used by theoreticians. Amply illustrated, High-Energy Astrophysics is also ideal for researchers interested in the application of fundamental physical laws to understand how matter and radiation behave in regions of the universe where physical conditions are most extreme.Uniquely weaves together the theoretical and experimental aspects of this important branch of astronomy Features stunning images of the high-energy sky Fully describes the principal classes of high-energy sources, with an in-depth study of many archetypal objects within them Provides an excellent, self-contained resource for the classroom, written by a preeminent researcher and teacher in the field

Nuclear astrophysics. --- Astrophysics. --- Astrophysics --- Nuclear physics --- Astronomical physics --- Astronomy --- Cosmic physics --- Physics --- Acceleration. --- Accretion (astrophysics). --- Accretion disk. --- Active galactic nucleus. --- Amplitude. --- Angular momentum. --- Annihilation. --- Apsis. --- Arbitrarily large. --- BL Lac object. --- Bell's theorem. --- Binary star. --- Black hole. --- Boundary layer. --- Bremsstrahlung. --- Circular orbit. --- Classical mechanics. --- Classical physics. --- Compact star. --- Compton Gamma Ray Observatory. --- Compton scattering. --- Concept. --- Conceptual framework. --- Conjecture. --- Cosmic ray. --- Cygnus A. --- Cygnus X-1. --- Database. --- Dissipation. --- Doppler effect. --- Effective temperature. --- Emissivity. --- Event horizon. --- Four-dimensional space. --- Four-vector. --- Galactic Center. --- Galactic plane. --- Galaxy cluster. --- Gamma-ray burst. --- Gravitational energy. --- Initial condition. --- Instability. --- Interstellar medium. --- Intracluster medium. --- Luminosity function (astronomy). --- Magnetic field. --- Massive particle. --- Measurement. --- Milky Way. --- Minute and second of arc. --- Molecular cloud. --- Molecule. --- Neutron star. --- Nuclear reaction. --- Ontology. --- Optical depth. --- Orbital period. --- Particle physics. --- Phenomenon. --- Photon. --- Physical law. --- Physical quantity. --- Physicist. --- Pierre Auger Observatory. --- Pilot wave. --- Polytropic process. --- Positron. --- Power law. --- Prediction. --- Probability. --- Quantity. --- Quantum decoherence. --- Quantum mechanics. --- Quasar. --- ROSAT. --- Radiative cooling. --- Radiative flux. --- Roche lobe. --- Scattering. --- Spaceflight. --- Special relativity. --- Star. --- Supermassive black hole. --- Supernova. --- Synchrotron. --- Temperature. --- Theorem. --- Theory of relativity. --- Theory. --- Thin disk. --- Time dilation. --- Transonic. --- Virgo Cluster. --- Viscosity. --- Wave function. --- Wavelength. --- White dwarf. --- X-ray. --- XMM-Newton.