Calculus On Euclidean Space
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Calculus On Euclidean Space
In mathematics, calculus on Euclidean space is a generalization of calculus of functions in one or several variables to calculus of functions on Euclidean space \mathbb^n as well as a finite-dimensional real vector space. This calculus is also known as advanced calculus, especially in the United States. It is similar to multivariable calculus but is somewhat more sophisticated in that it uses linear algebra (or some functional analysis) more extensively and covers some concepts from differential geometry such as differential forms and Stokes' formula in terms of differential forms. This extensive use of linear algebra also allows a natural generalization of multivariable calculus to calculus on Banach spaces or topological vector spaces. Calculus on Euclidean space is also a local model of calculus on manifolds, a theory of functions on manifolds. Basic notions Functions in one real variable This section is a brief review of function theory in one-variable calculus. A rea ...
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Calculus Of Functions
Calculus is the mathematical study of continuous change, in the same way that geometry is the study of shape, and algebra is the study of generalizations of arithmetic operations. Originally called infinitesimal calculus or "the calculus of infinitesimals", it has two major branches, differential calculus and integral calculus. The former concerns instantaneous rates of change, and the slopes of curves, while the latter concerns accumulation of quantities, and areas under or between curves. These two branches are related to each other by the fundamental theorem of calculus. They make use of the fundamental notions of convergence of infinite sequences and infinite series to a well-defined limit. It is the "mathematical backbone" for dealing with problems where variables change with time or another reference variable. Infinitesimal calculus was formulated separately in the late 17th century by Isaac Newton and Gottfried Wilhelm Leibniz. Later work, including codifying the ide ...
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Symmetry Of Second Derivatives
In mathematics, the symmetry of second derivatives (also called the equality of mixed partials) is the fact that exchanging the order of partial derivatives of a multivariate function :f\left(x_1,\, x_2,\, \ldots,\, x_n\right) does not change the result if some continuity conditions are satisfied (see below); that is, the second-order partial derivatives satisfy the identities :\frac \left( \frac \right) \ = \ \frac \left( \frac \right). In other words, the matrix of the second-order partial derivatives, known as the Hessian matrix, is a symmetric matrix. Sufficient conditions for the symmetry to hold are given by Schwarz's theorem, also called Clairaut's theorem or Young's theorem. In the context of partial differential equations, it is called the Schwarz integrability condition. Formal expressions of symmetry In symbols, the symmetry may be expressed as: :\frac \left( \frac \right) \ = \ \frac \left( \frac \right) \qquad\text\qquad \frac \ = ...
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Characteristic Function
In mathematics, the term "characteristic function" can refer to any of several distinct concepts: * The indicator function of a subset, that is the function \mathbf_A\colon X \to \, which for a given subset ''A'' of ''X'', has value 1 at points of ''A'' and 0 at points of ''X'' − ''A''. * The characteristic function in convex analysis, closely related to the indicator function of a set: \chi_A (x) := \begin 0, & x \in A; \\ + \infty, & x \not \in A. \end * In probability theory, the characteristic function of any probability distribution on the real line is given by the following formula, where ''X'' is any random variable with the distribution in question: \varphi_X(t) = \operatorname\left(e^\right), where \operatorname denotes expected value. For multivariate distributions, the product ''tX'' is replaced by a scalar product of vectors. * The characteristic function of a cooperative game in game theory. * The characteristic polynomial in linear algebra. * ...
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Fubini's Theorem
In mathematical analysis, Fubini's theorem characterizes the conditions under which it is possible to compute a double integral by using an iterated integral. It was introduced by Guido Fubini in 1907. The theorem states that if a function is Lebesgue integrable on a rectangle X\times Y, then one can evaluate the double integral as an iterated integral:\, \iint\limits_ f(x,y)\,\text(x,y) = \int_X\left(\int_Y f(x,y)\,\texty\right)\textx=\int_Y\left(\int_X f(x,y) \, \textx \right) \texty. This formula is generally not true for the Riemann integral, but it is true if the function is continuous on the rectangle. In multivariable calculus, this weaker result is sometimes also called Fubini's theorem, although it was already known by Leonhard Euler. Tonelli's theorem, introduced by Leonida Tonelli in 1909, is similar but is applied to a non-negative measurable function rather than to an integrable function over its domain. The Fubini and Tonelli theorems are usually combined and for ...
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Measure Zero
In mathematical analysis, a null set is a Lebesgue measurable set of real numbers that has Lebesgue measure, measure zero. This can be characterized as a set that can be Cover (topology), covered by a countable union of Interval (mathematics), intervals of arbitrarily small total length. The notion of null set should not be confused with the empty set as defined in set theory. Although the empty set has Lebesgue measure zero, there are also non-empty sets which are null. For example, any non-empty countable set of real numbers has Lebesgue measure zero and therefore is null. More generally, on a given measure space M = (X, \Sigma, \mu) a null set is a set S \in \Sigma such that \mu(S) = 0. Examples Every finite or countably infinite subset of the real numbers is a null set. For example, the set of natural numbers , the set of rational numbers and the set of algebraic numbers are all countably infinite and therefore are null sets when considered as subsets of the real nu ...
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Integrable Function
In mathematics, an integral is the continuous analog of a sum, which is used to calculate areas, volumes, and their generalizations. Integration, the process of computing an integral, is one of the two fundamental operations of calculus,Integral calculus is a very well established mathematical discipline for which there are many sources. See and , for example. the other being differentiation. Integration was initially used to solve problems in mathematics and physics, such as finding the area under a curve, or determining displacement from velocity. Usage of integration expanded to a wide variety of scientific fields thereafter. A definite integral computes the signed area of the region in the plane that is bounded by the graph of a given function between two points in the real line. Conventionally, areas above the horizontal axis of the plane are positive while areas below are negative. Integrals also refer to the concept of an ''antiderivative'', a function whose derivat ...
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Riemann Sum
In mathematics, a Riemann sum is a certain kind of approximation of an integral by a finite sum. It is named after nineteenth century German mathematician Bernhard Riemann. One very common application is in numerical integration, i.e., approximating the area of functions or lines on a graph, where it is also known as the rectangle rule. It can also be applied for approximating the length of curves and other approximations. The sum is calculated by partitioning the region into shapes (rectangles, trapezoids, parabolas, or cubics—sometimes infinitesimally small) that together form a region that is similar to the region being measured, then calculating the area for each of these shapes, and finally adding all of these small areas together. This approach can be used to find a numerical approximation for a definite integral even if the fundamental theorem of calculus does not make it easy to find a closed-form solution. Because the region by the small shapes is usually not ...
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Submersion Theorem
In mathematics, a submersion is a differentiable map between differentiable manifolds whose differential is everywhere surjective. It is a basic concept in differential topology, dual to that of an immersion. Definition Let ''M'' and ''N'' be differentiable manifolds, and let f\colon M\to N be a differentiable map between them. The map is a submersion at a point p \in M if its differential :Df_p \colon T_p M \to T_N is a surjective linear map. In this case, is called a regular point of the map ; otherwise, is a ''critical point''. A point q \in N is a regular value of if all points in the preimage f^(q) are regular points. A differentiable map that is a submersion at each point p \in M is called a submersion. Equivalently, is a submersion if its differential Df_p has constant rank equal to the dimension of . Some authors use the term ''critical point'' to describe a point where the rank of the Jacobian matrix of at is not maximal.: Indeed, this is the more useful ...
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Implicit Function Theorem
In multivariable calculus, the implicit function theorem is a tool that allows relations to be converted to functions of several real variables. It does so by representing the relation as the graph of a function. There may not be a single function whose graph can represent the entire relation, but there may be such a function on a restriction of the domain of the relation. The implicit function theorem gives a sufficient condition to ensure that there is such a function. More precisely, given a system of equations (often abbreviated into ), the theorem states that, under a mild condition on the partial derivatives (with respect to each ) at a point, the variables are differentiable functions of the in some neighborhood of the point. As these functions generally cannot be expressed in closed form, they are ''implicitly'' defined by the equations, and this motivated the name of the theorem. In other words, under a mild condition on the partial derivatives, the set of zero ...
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Whitney Extension Theorem
In mathematics, in particular in mathematical analysis, the Whitney extension theorem is a partial converse to Taylor's theorem. Roughly speaking, the theorem asserts that if ''A'' is a closed subset of a Euclidean space, then it is possible to extend a given function of ''A'' in such a way as to have prescribed derivatives at the points of ''A''. It is a result of Hassler Whitney. Statement A precise statement of the theorem requires careful consideration of what it means to prescribe the derivative of a function on a closed set. One difficulty, for instance, is that closed subsets of Euclidean space in general lack a differentiable structure. The starting point, then, is an examination of the statement of Taylor's theorem. Given a real-valued ''C''''m'' function ''f''(x) on R''n'', Taylor's theorem asserts that for each a, x, y ∈ R''n'', there is a function ''R''''α''(x,y) approaching 0 uniformly as x,y → a such that where the sum is over multi-indices ''α' ...
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Borel's Lemma
In mathematics, Borel's lemma, named after Émile Borel, is an important result used in the theory of asymptotic expansions and partial differential equations. Statement Suppose ''U'' is an open set in the Euclidean space R''n'', and suppose that ''f''0, ''f''1, ... is a sequence of smooth functions on ''U''. If ''I'' is any open interval in R containing 0 (possibly ''I'' = R), then there exists a smooth function ''F''(''t'', ''x'') defined on ''I''×''U'', such that :\left.\frac\_ = f_k(x), for ''k'' ≥ 0 and ''x'' in ''U''. Proof Proofs of Borel's lemma can be found in many text books on analysis, including and , from which the proof below is taken. Note that it suffices to prove the result for a small interval ''I'' = (−''ε'',''ε''), since if ''ψ''(''t'') is a smooth bump function with compact support in (−''ε'',''ε'') equal identically to 1 near 0, then ''ψ''(''t'') ⋅ ''F''(''t'', ''x'') gives a solution on R × ''U''. Similarly using a smooth partition of un ...
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Fourier Transform
In mathematics, the Fourier transform (FT) is an integral transform that takes a function as input then outputs another function that describes the extent to which various frequencies are present in the original function. The output of the transform is a complex-valued function of frequency. The term ''Fourier transform'' refers to both this complex-valued function and the mathematical operation. When a distinction needs to be made, the output of the operation is sometimes called the frequency domain representation of the original function. The Fourier transform is analogous to decomposing the sound of a musical chord into the intensities of its constituent pitches. Functions that are localized in the time domain have Fourier transforms that are spread out across the frequency domain and vice versa, a phenomenon known as the uncertainty principle. The critical case for this principle is the Gaussian function, of substantial importance in probability theory and statist ...
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