1.
Mathematics
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Mathematics is the study of topics such as quantity, structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope, Mathematicians seek out patterns and use them to formulate new conjectures. Mathematicians resolve the truth or falsity of conjectures by mathematical proof, when mathematical structures are good models of real phenomena, then mathematical reasoning can provide insight or predictions about nature. Through the use of abstraction and logic, mathematics developed from counting, calculation, measurement, practical mathematics has been a human activity from as far back as written records exist. The research required to solve mathematical problems can take years or even centuries of sustained inquiry, rigorous arguments first appeared in Greek mathematics, most notably in Euclids Elements. Galileo Galilei said, The universe cannot be read until we have learned the language and it is written in mathematical language, and the letters are triangles, circles and other geometrical figures, without which means it is humanly impossible to comprehend a single word. Without these, one is wandering about in a dark labyrinth, carl Friedrich Gauss referred to mathematics as the Queen of the Sciences. Benjamin Peirce called mathematics the science that draws necessary conclusions, David Hilbert said of mathematics, We are not speaking here of arbitrariness in any sense. Mathematics is not like a game whose tasks are determined by arbitrarily stipulated rules, rather, it is a conceptual system possessing internal necessity that can only be so and by no means otherwise. Albert Einstein stated that as far as the laws of mathematics refer to reality, they are not certain, Mathematics is essential in many fields, including natural science, engineering, medicine, finance and the social sciences. Applied mathematics has led to entirely new mathematical disciplines, such as statistics, Mathematicians also engage in pure mathematics, or mathematics for its own sake, without having any application in mind. There is no clear line separating pure and applied mathematics, the history of mathematics can be seen as an ever-increasing series of abstractions. The earliest uses of mathematics were in trading, land measurement, painting and weaving patterns, in Babylonian mathematics elementary arithmetic first appears in the archaeological record. Numeracy pre-dated writing and numeral systems have many and diverse. Between 600 and 300 BC the Ancient Greeks began a study of mathematics in its own right with Greek mathematics. Mathematics has since been extended, and there has been a fruitful interaction between mathematics and science, to the benefit of both. Mathematical discoveries continue to be made today, the overwhelming majority of works in this ocean contain new mathematical theorems and their proofs. The word máthēma is derived from μανθάνω, while the modern Greek equivalent is μαθαίνω, in Greece, the word for mathematics came to have the narrower and more technical meaning mathematical study even in Classical times

2.
Vector space
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A vector space is a collection of objects called vectors, which may be added together and multiplied by numbers, called scalars in this context. Scalars are often taken to be numbers, but there are also vector spaces with scalar multiplication by complex numbers, rational numbers. The operations of addition and scalar multiplication must satisfy certain requirements, called axioms. Euclidean vectors are an example of a vector space and they represent physical quantities such as forces, any two forces can be added to yield a third, and the multiplication of a force vector by a real multiplier is another force vector. In the same vein, but in a more geometric sense, Vector spaces are the subject of linear algebra and are well characterized by their dimension, which, roughly speaking, specifies the number of independent directions in the space. Infinite-dimensional vector spaces arise naturally in mathematical analysis, as function spaces and these vector spaces are generally endowed with additional structure, which may be a topology, allowing the consideration of issues of proximity and continuity. Among these topologies, those that are defined by a norm or inner product are commonly used. This is particularly the case of Banach spaces and Hilbert spaces, historically, the first ideas leading to vector spaces can be traced back as far as the 17th centurys analytic geometry, matrices, systems of linear equations, and Euclidean vectors. Today, vector spaces are applied throughout mathematics, science and engineering, furthermore, vector spaces furnish an abstract, coordinate-free way of dealing with geometrical and physical objects such as tensors. This in turn allows the examination of local properties of manifolds by linearization techniques, Vector spaces may be generalized in several ways, leading to more advanced notions in geometry and abstract algebra. The concept of space will first be explained by describing two particular examples, The first example of a vector space consists of arrows in a fixed plane. This is used in physics to describe forces or velocities, given any two such arrows, v and w, the parallelogram spanned by these two arrows contains one diagonal arrow that starts at the origin, too. This new arrow is called the sum of the two arrows and is denoted v + w, when a is negative, av is defined as the arrow pointing in the opposite direction, instead. Such a pair is written as, the sum of two such pairs and multiplication of a pair with a number is defined as follows, + = and a =. The first example above reduces to one if the arrows are represented by the pair of Cartesian coordinates of their end points. A vector space over a field F is a set V together with two operations that satisfy the eight axioms listed below, elements of V are commonly called vectors. Elements of F are commonly called scalars, the second operation, called scalar multiplication takes any scalar a and any vector v and gives another vector av. In this article, vectors are represented in boldface to distinguish them from scalars

3.
Dual space
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In mathematics, any vector space V has a corresponding dual vector space consisting of all linear functionals on V together with a naturally induced linear structure. The dual space as defined above is defined for all vector spaces, when defined for a topological vector space, there is a subspace of the dual space, corresponding to continuous linear functionals, called the continuous dual space. Dual vector spaces find application in many branches of mathematics that use vector spaces, when applied to vector spaces of functions, dual spaces are used to describe measures, distributions, and Hilbert spaces. Consequently, the space is an important concept in functional analysis. Given any vector space V over a field F, the dual space V∗ is defined as the set of all linear maps φ, V → F, since linear maps are vector space homomorphisms, the dual space is also sometimes denoted by Hom. The dual space V∗ itself becomes a space over F when equipped with an addition and scalar multiplication satisfying, = φ + ψ = a for all φ and ψ ∈ V∗, x ∈ V. Elements of the dual space V∗ are sometimes called covectors or one-forms. The pairing of a functional φ in the dual space V∗ and this pairing defines a nondegenerate bilinear mapping ⟨·, ·⟩, V∗ × V → F called the natural pairing. If V is finite-dimensional, then V∗ has the dimension as V. Given a basis in V, it is possible to construct a basis in V∗. This dual basis is a set of linear functionals on V, defined by the relation e i = c i, i =1, …, n for any choice of coefficients ci ∈ F. In particular, letting in turn one of those coefficients be equal to one. For example, if V is R2, and its basis chosen to be, then e1 and e2 are one-forms such that e1 =1, e1 =0, e2 =0, and e2 =1. In particular, if we interpret Rn as the space of columns of n real numbers, such a row acts on Rn as a linear functional by ordinary matrix multiplication. One way to see this is that a functional maps every n-vector x into a number y. So an element of V∗ can be thought of as a particular family of parallel lines covering the plane. To compute the value of a functional on a given vector, or, informally, one counts how many lines the vector crosses. The dimension of R∞ is countably infinite, whereas RN does not have a countable basis, again the sum is finite because fα is nonzero for only finitely many α

4.
Absolutely convex set
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A set C in a real or complex vector space is said to be absolutely convex or disked if it is convex and balanced, in which case it is called a disk. The absolutely convex hull of the set A is defined to be absconv A =, Vector, for vectors in physics Vector field Robertson, A. P. W. J. Robertson

5.
Absolutely convex envelope
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A set C in a real or complex vector space is said to be absolutely convex or disked if it is convex and balanced, in which case it is called a disk. The absolutely convex hull of the set A is defined to be absconv A =, Vector, for vectors in physics Vector field Robertson, A. P. W. J. Robertson

6.
Convex cone
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In linear algebra, a convex cone is a subset of a vector space over an ordered field that is closed under linear combinations with positive coefficients. A subset C of a vector space V is a if for each x in C and positive scalars α. A cone C is a cone if αx + βy belongs to C, for any positive scalars α, β. This concept is meaningful for any space that allows the concept of positive scalar, such as spaces over the rational, algebraic. Also note that the scalars in the definition are positive meaning that origin does not have to belong to C, some authors use a definition that ensures the origin belongs to C. Because of the scaling parameters α and β, cones are infinite in extent, if C is a convex cone, then for any positive scalar α and any x in C the vector αx = x + x is in C. It follows that a convex cone C is a case of a linear cone. It follows from the property that a convex cone can also be defined as a linear cone that is closed under convex combinations. More succinctly, a set C is a cone if and only if αC = C and C + C = C. The empty set, the space V, and any linear subspace of V are convex cones, the conical combination of a finite or infinite set of vectors in Rn is a convex cone. The tangent cones of a set are convex cones. The set ∪ is a cone but not a convex cone, the norm cone is a convex cone. The intersection of two cones in the same vector space is again a convex cone, but their union may fail to be one. The class of convex cones is also closed under arbitrary linear maps, in particular, if C is a convex cone, so is its opposite −C, and C ∩ −C is the largest linear subspace contained in C. The set of positive semidefinite matrices The set of continuous functions is a convex cone. An affine convex cone is the set resulting from applying a transformation to a convex cone. A common example is translating a convex cone by a point p, technically, such transformations can produce non-cones. For example, unless p=0, p+C is not a linear cone, however, it is still called an affine convex cone

7.
Dual cone and polar cone
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Dual cone and polar cone are closely related concepts in convex analysis, a branch of mathematics. C* is always a convex cone, even if C is neither convex nor a cone, alternatively, many authors define the dual cone in the context of a real Hilbert space, to be what is sometimes called the internal dual cone. Y and C lie on the side of that supporting hyperplane. C1 ⊆ C2 implies C2 ∗ ⊆ C1 ∗, if C has nonempty interior, then C* is pointed, i. e. C* contains no line in its entirety, if C is a cone and the closure of C is pointed, then C* has nonempty interior. Those authors who define the dual cone as the dual cone in a real Hilbert space usually say that a cone is self-dual if it is equal to its internal dual. This is slightly different than the definition, which permits a change of inner product. The nonnegative orthant of Rn and the space of all positive semidefinite matrices are self-dual, so are all cones in R3 whose base is the convex hull of a regular polygon with an odd number of vertices. A less regular example is the cone in R3 whose base is the house, the hull of a square. For a set C in X, the cone of C is the set C o =. It can be seen that the cone is equal to the negative of the dual cone. For a closed convex cone C in X, the cone is equivalent to the polar set for C. Bipolar theorem Polar set Goh, C. J. Yang, duality in optimization and variational inequalities. London, New York, Taylor & Francis, boltyanski, V. G. Martini, H. Soltan, P

8.
Pole and polar
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In geometry, the pole and polar are respectively a point and a line that have a unique reciprocal relationship with respect to a given conic section. If the point lies on the section, its polar is the tangent line to the conic section at that point. For a given circle, reciprocation in a means the transformation of each point in the plane into its polar line. Poles and polars have several properties, If a point P lies on a line l. If a point P moves along a line l, its polar p rotates about the pole L of the line l, If two tangent lines can be drawn from a pole to the conic section, then its polar passes through both tangent points. If a point lies on the section, its polar is the tangent through this point to the conic section. If a point P lies on its own line, then P is on the conic section. Each line has, with respect to a conic section. The pole of a line L in a circle C is a point P that is the inversion in C of the point Q on L that is closest to the center of the circle. Conversely, the line of a point P in a circle C is the line L such that its closest point Q to the center of the circle is the inversion of P in C. The relationship between poles and polars is reciprocal, thus, if a point Q is on the polar line A of a point P, then the point P must lie on the polar line B of the point Q. The two polar lines A and B need not be parallel, there is another description of the polar line of a point P in the case that it lies outside the circle C. In this case, there are two lines through P which are tangent to the circle, and the polar of P is the joining the two points of tangency. This shows that pole and polar line are concepts in the geometry of the plane. The concepts of a pole and its line were advanced in projective geometry. For instance, the line can be viewed as the set of projective harmonic conjugates of a given point. The operation of replacing every point by its polar and vice versa is known as a polarity, a polarity is a correlation that is also an involution. The concepts of pole, polar and reciprocation can be generalized from circles to other sections which are the ellipse

9.
Geometry
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Geometry is a branch of mathematics concerned with questions of shape, size, relative position of figures, and the properties of space. A mathematician who works in the field of geometry is called a geometer, Geometry arose independently in a number of early cultures as a practical way for dealing with lengths, areas, and volumes. Geometry began to see elements of mathematical science emerging in the West as early as the 6th century BC. By the 3rd century BC, geometry was put into a form by Euclid, whose treatment, Euclids Elements. Geometry arose independently in India, with texts providing rules for geometric constructions appearing as early as the 3rd century BC, islamic scientists preserved Greek ideas and expanded on them during the Middle Ages. By the early 17th century, geometry had been put on a solid footing by mathematicians such as René Descartes. Since then, and into modern times, geometry has expanded into non-Euclidean geometry and manifolds, while geometry has evolved significantly throughout the years, there are some general concepts that are more or less fundamental to geometry. These include the concepts of points, lines, planes, surfaces, angles, contemporary geometry has many subfields, Euclidean geometry is geometry in its classical sense. The mandatory educational curriculum of the majority of nations includes the study of points, lines, planes, angles, triangles, congruence, similarity, solid figures, circles, Euclidean geometry also has applications in computer science, crystallography, and various branches of modern mathematics. Differential geometry uses techniques of calculus and linear algebra to problems in geometry. It has applications in physics, including in general relativity, topology is the field concerned with the properties of geometric objects that are unchanged by continuous mappings. In practice, this often means dealing with large-scale properties of spaces, convex geometry investigates convex shapes in the Euclidean space and its more abstract analogues, often using techniques of real analysis. It has close connections to convex analysis, optimization and functional analysis, algebraic geometry studies geometry through the use of multivariate polynomials and other algebraic techniques. It has applications in areas, including cryptography and string theory. Discrete geometry is concerned mainly with questions of relative position of simple objects, such as points. It shares many methods and principles with combinatorics, Geometry has applications to many fields, including art, architecture, physics, as well as to other branches of mathematics. The earliest recorded beginnings of geometry can be traced to ancient Mesopotamia, the earliest known texts on geometry are the Egyptian Rhind Papyrus and Moscow Papyrus, the Babylonian clay tablets such as Plimpton 322. For example, the Moscow Papyrus gives a formula for calculating the volume of a truncated pyramid, later clay tablets demonstrate that Babylonian astronomers implemented trapezoid procedures for computing Jupiters position and motion within time-velocity space

10.
International Standard Book Number
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The International Standard Book Number is a unique numeric commercial book identifier. An ISBN is assigned to each edition and variation of a book, for example, an e-book, a paperback and a hardcover edition of the same book would each have a different ISBN. The ISBN is 13 digits long if assigned on or after 1 January 2007, the method of assigning an ISBN is nation-based and varies from country to country, often depending on how large the publishing industry is within a country. The initial ISBN configuration of recognition was generated in 1967 based upon the 9-digit Standard Book Numbering created in 1966, the 10-digit ISBN format was developed by the International Organization for Standardization and was published in 1970 as international standard ISO2108. Occasionally, a book may appear without a printed ISBN if it is printed privately or the author does not follow the usual ISBN procedure, however, this can be rectified later. Another identifier, the International Standard Serial Number, identifies periodical publications such as magazines, the ISBN configuration of recognition was generated in 1967 in the United Kingdom by David Whitaker and in 1968 in the US by Emery Koltay. The 10-digit ISBN format was developed by the International Organization for Standardization and was published in 1970 as international standard ISO2108, the United Kingdom continued to use the 9-digit SBN code until 1974. The ISO on-line facility only refers back to 1978, an SBN may be converted to an ISBN by prefixing the digit 0. For example, the edition of Mr. J. G. Reeder Returns, published by Hodder in 1965, has SBN340013818 -340 indicating the publisher,01381 their serial number. This can be converted to ISBN 0-340-01381-8, the check digit does not need to be re-calculated, since 1 January 2007, ISBNs have contained 13 digits, a format that is compatible with Bookland European Article Number EAN-13s. An ISBN is assigned to each edition and variation of a book, for example, an ebook, a paperback, and a hardcover edition of the same book would each have a different ISBN. The ISBN is 13 digits long if assigned on or after 1 January 2007, a 13-digit ISBN can be separated into its parts, and when this is done it is customary to separate the parts with hyphens or spaces. Separating the parts of a 10-digit ISBN is also done with either hyphens or spaces, figuring out how to correctly separate a given ISBN number is complicated, because most of the parts do not use a fixed number of digits. ISBN issuance is country-specific, in that ISBNs are issued by the ISBN registration agency that is responsible for country or territory regardless of the publication language. Some ISBN registration agencies are based in national libraries or within ministries of culture, in other cases, the ISBN registration service is provided by organisations such as bibliographic data providers that are not government funded. In Canada, ISBNs are issued at no cost with the purpose of encouraging Canadian culture. In the United Kingdom, United States, and some countries, where the service is provided by non-government-funded organisations. Australia, ISBNs are issued by the library services agency Thorpe-Bowker

11.
Mathematical analysis
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Mathematical analysis is the branch of mathematics dealing with limits and related theories, such as differentiation, integration, measure, infinite series, and analytic functions. These theories are studied in the context of real and complex numbers. Analysis evolved from calculus, which involves the elementary concepts and techniques of analysis, analysis may be distinguished from geometry, however, it can be applied to any space of mathematical objects that has a definition of nearness or specific distances between objects. Mathematical analysis formally developed in the 17th century during the Scientific Revolution, early results in analysis were implicitly present in the early days of ancient Greek mathematics. For instance, a geometric sum is implicit in Zenos paradox of the dichotomy. The explicit use of infinitesimals appears in Archimedes The Method of Mechanical Theorems, in Asia, the Chinese mathematician Liu Hui used the method of exhaustion in the 3rd century AD to find the area of a circle. Zu Chongzhi established a method that would later be called Cavalieris principle to find the volume of a sphere in the 5th century, the Indian mathematician Bhāskara II gave examples of the derivative and used what is now known as Rolles theorem in the 12th century. In the 14th century, Madhava of Sangamagrama developed infinite series expansions, like the power series and his followers at the Kerala school of astronomy and mathematics further expanded his works, up to the 16th century. The modern foundations of analysis were established in 17th century Europe. During this period, calculus techniques were applied to approximate discrete problems by continuous ones, in the 18th century, Euler introduced the notion of mathematical function. Real analysis began to emerge as an independent subject when Bernard Bolzano introduced the definition of continuity in 1816. In 1821, Cauchy began to put calculus on a firm logical foundation by rejecting the principle of the generality of algebra widely used in earlier work, instead, Cauchy formulated calculus in terms of geometric ideas and infinitesimals. Thus, his definition of continuity required a change in x to correspond to an infinitesimal change in y. He also introduced the concept of the Cauchy sequence, and started the theory of complex analysis. Poisson, Liouville, Fourier and others studied partial differential equations, the contributions of these mathematicians and others, such as Weierstrass, developed the -definition of limit approach, thus founding the modern field of mathematical analysis. In the middle of the 19th century Riemann introduced his theory of integration, the last third of the century saw the arithmetization of analysis by Weierstrass, who thought that geometric reasoning was inherently misleading, and introduced the epsilon-delta definition of limit. Then, mathematicians started worrying that they were assuming the existence of a continuum of numbers without proof. Around that time, the attempts to refine the theorems of Riemann integration led to the study of the size of the set of discontinuities of real functions, also, monsters began to be investigated