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|[[Image:Integral example.png|thumb|A definite integral of a function can be represented as the signed area of the region bounded by its graph.]]
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'''Integration''' is an important concept in [[mathematics]], specifically in the field of [[calculus]] and, more broadly, [[mathematical analysis]]. Given a [[function (mathematics)|function]] ''&fnof;'' of a [[Real number|real]] [[variable]] ''x'' and an [[interval (mathematics)|interval]] <nowiki>[</nowiki>''a'',&nbsp;''b''<nowiki>]</nowiki> of the [[real line]], the '''integral'''
{{Calculus}}
 
In [[calculus]], the '''integral''' of a [[function (mathematics)|function]] is a generalization of [[area (geometry)|area]], [[mass]], [[volume]], [[sum]], and [[total]]. The process of finding integrals is '''integration''', in its mathematical meaning. Unlike the closely-related process of [[derivative|differentiation]], there are several possible definitions of integration, with different technical underpinnings. They are, however, compatible; any two different ways of integrating a function will give the same result when they are both defined.
 
   
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: <math>\int_a^b f(x)\,dx \, ,</math>
The word "integral" may also refer to [[antiderivative]]s in a mild abuse of language. Though they are closely related through the [[fundamental theorem of calculus]], the two notions are conceptually distinct. When one wants to clarify this distinction, an antiderivative integral is referred to as an indefinite integral (a function), while the integrals discussed in this article are termed '''definite integrals'''.
 
   
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is defined informally to be the net signed [[area (geometry)|area]] of the region in the ''xy''-plane bounded by the [[Graph of a function|graph]] of ''&fnof;'', the ''x''-axis, and the vertical lines ''x''&nbsp;= ''a'' and ''x''&nbsp;=&nbsp;''b''.
Intuitively, the integral of a [[continuous function|continuous]], [[negative and non-negative numbers|positive]] real-valued function ''f'' of one real variable ''x'' between a left endpoint ''a'' and a right endpoint ''b'' represents the area bounded by the lines ''x'' = ''a'', ''x'' = ''b'', the ''x''-axis, and the curve defined by the graph of ''f''. More formally, if we let
 
:<math> S= \{(x,y) \in \mathbb{R}^2:a \leq x \leq b ,0 \leq y \leq f(x)\}, </math>
 
   
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The term "integral" may also refer to the notion of [[antiderivative]], a function ''F'' whose [[derivative]] is the given function ''&fnof;''. In this case it is called an '''indefinite integral''', while the integrals discussed in this article are termed '''definite integrals'''. Some authors maintain a distinction between antiderivatives and indefinite integrals.
then the integral of ''f'' between ''a'' and ''b'' is the [[Measure (mathematics)|measure]] of ''S''.
 
   
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The principles of integration were formulated independently by [[Isaac Newton]] and [[Gottfried Leibniz]] in the late seventeenth century. Through the [[fundamental theorem of calculus]], which they independently developed, integration is connected with [[differential calculus|differentiation]]: if ''&fnof;'' is a continuous real-valued function defined on a [[closed interval]] [''a'',&nbsp;''b''], then, once an antiderivative ''F'' of ''&fnof;'' is known, the definite integral of ''&fnof;'' over that interval is given by
[[Leibniz]] introduced the standard [[long s]] notation for the integral. The integral of the previous paragraph would be written <math>\int_a^b f(x)\,dx</math>. The &int; sign represents integration, ''a'' and ''b'' are the endpoints of the [[interval]], ''f(x)'' is the function we are integrating, and ''dx'' is a notation for the variable of integration. Historically, ''dx'' represented an [[infinitesimal]] quantity, and the long s stood for "sum". However, modern theories of integration are built from different foundations, and the traditional symbols have become no more than [[Mathematical notation|notation]].
 
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:::<math>\int_a^b f(x)\,dx = F(b) - F(a)\, .</math>
   
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Integrals and derivatives became the basic tools of [[calculus]], with numerous applications in science and [[engineering]]. A rigorous mathematical definition of the integral was given by [[Bernhard Riemann]]. It is based on a [[limit (mathematics)|limiting]] procedure which approximates the area of a [[curvilinear]] region by breaking the region into thin vertical slabs. Beginning in the nineteenth century, more sophisticated notions of integral began to appear, where the type of the function as well as the domain over which the integration is performed has been generalised. A [[line integral]] is defined for functions of two or three variables, and the interval of integration <nowiki>[</nowiki>''a'',&nbsp;''b''<nowiki>]</nowiki> is replaced by a certain [[curve]] connecting two points on the plane or in the space. In a [[surface integral]], the curve is replaced by a piece of a [[surface]] in the three-dimensional space.
As an example, if ''f'' is the [[mathematical constant|constant]] function ''f''(''x'') = 3, then the integral of ''f'' between 0 and 10 is the area of the rectangle bounded by the lines ''x'' = 0, ''x'' = 10, ''y'' = 0, and ''y'' = 3. The area is the width of the rectangle times its height, so the value of the integral is 30.
 
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Integrals of [[differential form]]s play a fundamental role in modern [[differential geometry]]. These generalizations of integral first arose from the needs of [[physics]], and they play an important role in the formulation of many physical laws, notably those of [[Classical electromagnetism|electrodynamics]]. Modern concepts of integration are based on the abstract mathematical theory known as [[Lebesgue integration]], developed by [[Henri Lebesgue]].
   
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{{TOClimit|limit=2}}
Integrals can be taken over regions other than intervals. In general, the integral over a [[set]] ''E'' of a function ''f'' is written &int;<sub>''E''</sub>''f''(''x'')&nbsp;''dx''. Here ''x'' need not be a real number, but, for instance, a [[vector (spatial)|vector]] in '''R'''<sup>3</sup>. [[Fubini's theorem]] shows that such integrals can be rewritten as an iterated integral. In other words, the integral can be calculated by integrating one coordinate at a time.
 
   
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== History ==
[[Image:Integral as region under curve.png|thumb|250px|The integral of ''f''(''x'') is the area between the curve ''y'' = ''f''(''x'') and the ''x''-axis in the interval [''a'', ''b''].]]
 
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{{see also|History of calculus}}
If a function has an integral, it is said to be ''integrable''. The function for which the integral is calculated is called the '''integrand'''. Integrals result in a number, not another function. If the domain of the function to be integrated is the [[real number]]s, and if the region of integration is an [[interval (mathematics)|interval]], then the [[infimum|greatest lower bound]] of the interval is called the ''lower limit of integration'', and the [[supremum|least upper bound]] is called the ''upper limit of integration''.
 
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=== Pre-calculus integration ===
   
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Integration can be traced as far back as ancient Egypt, ''circa'' 1800 BC, with the [[Moscow Mathematical Papyrus]] demonstrating knowledge of a formula for the [[volume]] of a [[pyramid]]al [[frustum]]. The first documented systematic technique capable of determining integrals is the [[method of exhaustion]] of [[Eudoxus of Cnidus|Eudoxus]] (''circa'' 370 BC), which sought to find areas and volumes by breaking them up into an infinite number of shapes for which the area or volume was known. This method was further developed and employed by [[Archimedes]] and used to calculate areas for parabolas and an approximation to the area of a circle. Similar methods were independently developed in China around the 3rd Century AD by [[Liu Hui]], who used it to find the area of the circle. This method was later used in the 5th century by Chinese father and son mathematicians [[Zu Chongzhi]] and [[Zu Geng (mathematician)|Zu Geng]] to find the volume of a sphere.<ref>{{citation | last1=Shea | first1=Marilyn | title=Biography of Zu Chongzhi | date=May 2007 | url=http://hua.umf.maine.edu/China/astronomy/tianpage/0014ZuChongzhi9296bw.html | publisher=University of Maine | accessdate=9 January 2009}}<br>{{Citation | last1=Katz | first1=Victor J. | title=A History of Mathematics, Brief Version | publisher=[[Addison-Wesley]] | isbn=978-0-321-16193-2 | year=2004 | pages=125–126}}</ref> That same century, the [[Indian mathematics|Indian mathematician]] [[Aryabhata]] used a similar method in order to find the volume of a [[cube]].<ref>Victor J. Katz (1995), "Ideas of Calculus in Islam and India", ''Mathematics Magazine'' '''68''' (3): 163-174 [165]</ref>
[[Image:Areabetweentwographs.png|thumb|287px|Finding the area between two curves.]]
 
   
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The next major step in integral calculus came in the 11th century, when the [[Islamic mathematics|Iraqi mathematician]], [[Ibn al-Haytham]] (known as ''Alhazen'' in Europe), devised what is now known as "Alhazen's problem", which leads to an [[Quartic equation|equation of the fourth degree]], in his ''[[Book of Optics]]''. While solving this problem, he performed an integration in order to find the volume of a [[paraboloid]]. Using [[mathematical induction]], he was able to generalize his result for the integrals of [[polynomial]]s up to the [[Quartic polynomial|fourth degree]]. He thus came close to finding a general formula for the integrals of polynomials, but he was not concerned with any polynomials higher than the fourth degree.<ref name=Katz>Victor J. Katz (1995), "Ideas of Calculus in Islam and India", ''Mathematics Magazine'' '''68''' (3): 163–174 [165–9 & 173–4]</ref> Some ideas of integral calculus are also found in the ''Siddhanta Shiromani'', a 12th century [[Indian astronomy|astronomy]] text by Indian mathematician [[Bhāskara II]].
== Computing integrals ==
 
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The most basic technique for computing integrals of one real variable is based on the [[fundamental theorem of calculus]]. It proceeds like this:
 
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The next significant advances in integral calculus did not begin to appear until the 16th century. At this time the work of [[Bonaventura Cavalieri|Cavalieri]] with [[Cavalieri's principle|his ''method of indivisibles'']], and work by [[Pierre de Fermat|Fermat]], began to lay the foundations of modern calculus. Further steps were made in the early 17th century by [[Isaac Barrow|Barrow]] and [[Evangelista Torricelli|Torricelli]], who provided the first hints of a connection between integration and [[Differential calculus|differentiation]].
# Choose a function ''f(x)'' and an interval [''a'',''b''].
 
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# Find an [[antiderivative]] of ''f'', that is, a function ''F'' such that ''F' '' = ''f''.
 
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=== Newton and Leibniz ===
# By the fundamental theorem of calculus, provided the integrand and integral have no singularities on the path of integration, <math>\int_a^b f(x)\,dx = F(b)-F(a)</math>.
 
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The major advance in integration came in the 17th century with the independent discovery of the [[fundamental theorem of calculus]] by [[Isaac Newton|Newton]] and [[Gottfried Leibniz|Leibniz]]. The theorem demonstrates a connection between integration and differentiation. This connection, combined with the comparative ease of differentiation, can be exploited to calculate integrals. In particular, the fundamental theorem of calculus allows one to solve a much broader class of problems. Equal in importance is the comprehensive mathematical framework that both Newton and Leibniz developed. Given the name infinitesimal calculus, it allowed for precise analysis of functions within continuous domains. This framework eventually became modern [[calculus]], whose notation for integrals is drawn directly from the work of Leibniz.
# Therefore the value of the integral is ''F(b) − F(a)''.
 
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<!--- Please, do not remove: helpful for verification
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The last sentence originally said 'work of Newton and Leibniz', but for integrals, only Leibniz's notation is used. --->
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=== Formalizing integrals ===
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While Newton and Leibniz provided a systematic approach to integration, their work lacked a degree of rigor. [[George Berkeley|Bishop Berkeley]] memorably attacked [[infinitesimal]]s as "the [[ghosts of departed quantities]]". Calculus acquired a firmer footing with the development of [[Limit (mathematics)|limits]] and was given a suitable foundation by [[Augustin Louis Cauchy|Cauchy]] in the first half of the 19th century. Integration was first rigorously formalized, using limits, by [[Bernhard Riemann|Riemann]]. Although all bounded piecewise continuous functions are Riemann integrable on a bounded interval, subsequently more general functions were considered, to which Riemann's definition does not apply, and [[Henri Lebesgue|Lebesgue]] formulated a different definition of integral, founded in [[Measure (mathematics)|measure theory]] (a subfield of [[real analysis]]). Other definitions of integral, extending Riemann's and Lebesgue's approaches, were proposed.
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=== Notation ===
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[[Isaac Newton]] used a small vertical bar above a variable to indicate integration, or placed the variable inside a box. The vertical bar was easily confused with <math>\dot{x}</math> or <math>x'\,\!</math>, which Newton used to indicate differentiation, and the box notation was difficult for printers to reproduce, so these notations were not widely adopted.
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The modern notation for the indefinite integral was introduced by [[Gottfried Leibniz]] in 1675 ({{Harvnb|Burton|1988|loc=p.&nbsp;359}}; {{Harvnb|Leibniz|1899|loc=p.&nbsp;154}}). He adapted the [[integral symbol]], "'''∫'''", from an [[long s|elongated letter "s"]], standing for ''summa'' (Latin for "sum" or "total"). The modern notation for the definite integral, with limits above and below the integral sign, was first used by [[Joseph Fourier]] in ''Mémoires'' of the French Academy around 1819–20, reprinted in his book of 1822 ({{Harvnb|Cajori|1929|loc=pp.&nbsp;249–250}}; {{Harvnb|Fourier|1822|loc=&sect;231}}).
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In so-called [[modern Arabic mathematical notation]], which aims at pre-university levels of education in the Arab world and is written from right to left, an inverted integral symbol [[File:ArabicIntegralSign.svg|22px]] is used {{Harv|W3C|2006}}.
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== Terminology and notation ==
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If a function has an integral, it is said to be '''integrable'''. The function for which the integral is calculated is called the '''integrand'''. The region over which a function is being integrated is called the '''domain of integration'''. If the integral does not have a domain of integration, it is considered indefinite (one with a domain is considered definite). In general, the integrand may be a function of more than one variable, and the domain of integration may be an area, volume, a higher dimensional region, or even an abstract space that does not have a geometric structure in any usual sense.
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The simplest case, the integral of a real-valued function ''f'' of one real variable ''x'' on the interval [''a'', ''b''], is denoted by
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:<math>\int_a^b f(x)\,dx . </math>
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The ∫ sign, an elongated "s", represents integration; ''a'' and ''b'' are the '''lower limit''' and '''upper limit''' of integration, defining the domain of integration; ''f'' is the integrand, to be evaluated as ''x'' varies over the interval [''a'',''b'']; and ''dx'' is the variable of integration. In correct mathematical typography, the ''dx'' is separated from the integrand by a space (as shown). Some authors use an upright ''d'' (that is, <math>\mathrm{d}x</math> instead of ''dx'').
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The variable of integration ''dx'' has different interpretations depending on the theory being used. For example, it can be seen as strictly a notation indicating that ''x'' is a [[dummy variable]] of integration, as a reflection of the weights in the Riemann sum, a measure (in Lebesgue integration and its extensions), an infinitesimal (in non-standard analysis) or as an independent mathematical quantity: a [[differential form]]. More complicated cases may vary the notation slightly.
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== Introduction ==
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Integrals appear in many practical situations. Consider a swimming pool. If it is rectangular, then from its length, width, and depth we can easily determine the volume of water it can contain (to fill it), the area of its surface (to cover it), and the length of its edge (to rope it). But if it is oval with a rounded bottom, all of these quantities call for integrals. Practical approximations may suffice for such trivial examples, but precision engineering (of any discipline) requires exact and rigorous values for these elements.
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[[Image:Integral approximations.svg|thumb|right|Approximations to integral of &radic;''x'' from 0 to 1, with <span style="color:#fec200">■</span>&nbsp;5 right samples (above) and <span style="color:#009246">■</span>&nbsp;12 left samples (below)]]
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To start off, consider the curve ''y''&nbsp;=&nbsp;''f''(''x'') between ''x''&nbsp;=&nbsp;0 and ''x''&nbsp;=&nbsp;1, with ''f''(''x'')&nbsp;=&nbsp;√''x''. We ask:
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:What is the area under the function ''f'', in the interval from 0 to 1?
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and call this (yet unknown) area the '''integral''' of ''f''. The notation for this integral will be
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:<math> \int_0^1 \sqrt x \, dx \,\!.</math>
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As a first approximation, look at the unit square given by the sides ''x''&nbsp;=&nbsp;0 to ''x''&nbsp;=&nbsp;1 and ''y''&nbsp;=&nbsp;''f''(0)&nbsp;=&nbsp;0 and ''y''&nbsp;=&nbsp;''f''(1)&nbsp;=&nbsp;1. Its area is exactly 1. As it is, the true value of the integral must be somewhat less. Decreasing the width of the approximation rectangles shall give a better result; so cross the interval in five steps, using the approximation points 0, <sup>1</sup>⁄<sub>5</sub>, <sup>2</sup>⁄<sub>5</sub>, and so on to 1. Fit a box for each step using the right end height of each curve piece, thus √<sup>1</sup>⁄<sub>5</sub>, √<sup>2</sup>⁄<sub>5</sub>, and so on to √1&nbsp;=&nbsp;1. Summing the areas of these rectangles, we get a better approximation for the sought integral, namely
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<!--:&radic;<sup>1</sup>&frasl;<sub>5</sub>*( <sup>1</sup>&frasl;<sub>5</sub>-0)+&radic;<sup>2</sup>&frasl;<sub>5</sub>*( <sup>2</sup>&frasl;<sub>5</sub>-<sup>1</sup>&frasl;<sub>5</sub>)+...+&radic;<sup>5</sup>&frasl;<sub>5</sub>*( <sup>5</sup>&frasl;<sub>5</sub>-<sup>4</sup>&frasl;<sub>5</sub>) ≈ 0.7497.-->
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:<math>\textstyle \sqrt {\frac {1} {5}} \left ( \frac {1} {5} - 0 \right ) + \sqrt {\frac {2} {5}} \left ( \frac {2} {5} - \frac {1} {5} \right ) + \cdots + \sqrt {\frac {5} {5}} \left ( \frac {5} {5} - \frac {4} {5} \right ) \approx 0.7497.\,\!</math>
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Notice that we are taking a sum of finitely many function values of ''f'', multiplied with the differences of two subsequent approximation points. We can easily see that the approximation is still too large. Using more steps produces a closer approximation, but will never be exact: replacing the 5 subintervals by twelve as depicted, we will get an approximate value for the area of 0.6203, which is too small. The key idea is the transition from adding ''finitely many'' differences of approximation points multiplied by their respective function values to using infinitely fine, or ''[[infinitesimal]]'' steps.
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As for the '''actual calculation of integrals''', the [[fundamental theorem of calculus]], due to Newton and Leibniz, is the fundamental link between the operations of [[Derivative|differentiating]] and integrating. Applied to the square root curve, ''f''(''x'') = ''x''<sup>1/2</sup>, it says to look at the [[antiderivative]] ''F''(''x'')&nbsp;= <sup>2</sup>⁄<sub>3</sub>''x''<sup>3/2</sup>, and simply take ''F''(1) &minus; ''F''(0), where 0 and 1 are the boundaries of the [[interval (mathematics)|interval]] [0,1]. (This is a case of a general rule, that for ''f''(''x'')&nbsp;= ''x''<sup>''q''</sup>, with ''q''&nbsp;≠&nbsp;−1, the related function, the so-called [[antiderivative]] is ''F''(''x'')&nbsp;=&nbsp;(''x''<sup>''q''+1</sup>)/(''q'' + 1).) So the ''exact'' value of the area under the curve is computed formally as
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:<math> \int_0^1 \sqrt x \,dx = \int_0^1 x^{\frac{1}{2}} \,dx = \int_0^1 d \left({\textstyle \frac 2 3} x^{\frac{3}{2}}\right) = {\textstyle \frac 2 3}.</math>
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The notation
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:<math> \int f(x) \, dx \,\! </math>
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conceives the integral as a weighted sum, denoted by the elongated "s", of function values, ''f''(''x''), multiplied by infinitesimal step widths, the so-called ''differentials'', denoted by ''dx''. The multiplication sign is usually omitted.
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<!-- Note: Today's limits of integration were not part of the notation until much later, due to Fourier. -->Historically, after the failure of early efforts to rigorously interpret infinitesimals, Riemann formally defined integrals as a [[limit (mathematics)|limit]] of weighted sums, so that the ''dx'' suggested the limit of a difference (namely, the interval width). Shortcomings of Riemann's dependence on intervals and continuity motivated newer definitions, especially the [[Lebesgue integration|Lebesgue integral]], which is founded on an ability to extend the idea of "measure" in much more flexible ways. Thus the notation
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:<math> \int_A f(x) \, d\mu \,\!</math>
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refers to a weighted sum in which the function values are partitioned, with μ measuring the weight to be assigned to each value. Here ''A'' denotes the region of integration.
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[[Differential geometry]], with its "calculus on [[manifold]]s", gives the familiar notation yet another interpretation. Now ''f''(''x'') and ''dx'' become a [[differential form]], ω&nbsp;=&nbsp;''f''(''x'')&thinsp;''dx'', a new [[differential operator]] '''d''', known as the [[exterior derivative]] appears, and the fundamental theorem becomes the more general [[Stokes' theorem]],
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:<math> \int_{A} \bold{d} \omega = \int_{\part A} \omega , \,\!</math>
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from which [[Green's theorem]], the [[divergence theorem]], and the [[fundamental theorem of calculus]] follow.
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More recently, infinitesimals have reappeared with rigor, through modern innovations such as [[non-standard analysis]]. Not only do these methods vindicate the intuitions of the pioneers, they also lead to new mathematics.
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Although there are differences between these conceptions of integral, there is considerable overlap. Thus the area of the surface of the oval swimming pool can be handled as a geometric ellipse, as a sum of infinitesimals, as a Riemann integral, as a Lebesgue integral, or as a manifold with a differential form. The calculated result will be the same for all.
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== Formal definitions ==
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There are many ways of formally defining an integral, not all of which are equivalent. The differences exist mostly to deal with differing special cases which may not be integrable under other definitions, but also occasionally for pedagogical reasons. The most commonly used definitions of integral are Riemann integrals and Lebesgue integrals.
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=== Riemann integral ===
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{{main|Riemann integral}}
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[[Image:Integral Riemann sum.png|thumb|right|Integral approached as Riemann sum based on tagged partition, with irregular sampling positions and widths (max in red). True value is 3.76; estimate is 3.648.]]
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The Riemann integral is defined in terms of [[Riemann sum]]s of functions with respect to ''tagged partitions'' of an interval. Let [''a'',''b''] be a [[Interval (mathematics)|closed interval]] of the real line; then a ''tagged partition'' of [''a'',''b''] is a finite sequence
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:<math> a = x_0 \le t_1 \le x_1 \le t_2 \le x_2 \le \cdots \le x_{n-1} \le t_n \le x_n = b . \,\!</math>
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[[Image:Riemann sum convergence.png|thumb|250px|left|Riemann sums converging as intervals halve, whether sampled at <span style="color:#0081cd">■</span>&nbsp;right, <span style="color:#bc1e47">■</span>&nbsp;minimum, <span style="color:#009246">■</span>&nbsp;maximum, or <span style="color:#fec200">■</span>&nbsp;left.]]
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This partitions the interval [''a'',''b''] into ''i'' sub-intervals [''x''<sub>''i''−1</sub>, ''x''<sub>''i''</sub>], each of which is "tagged" with a distinguished point ''t''<sub>''i''</sub> ∈ [''x''<sub>''i''−1</sub>, ''x''<sub>''i''</sub>]. Let Δ<sub>''i''</sub>&nbsp;= ''x''<sub>''i''</sub>−''x''<sub>''i''−1</sub> be the width of sub-interval ''i''; then the ''mesh'' of such a tagged partition is the width of the largest sub-interval formed by the partition, max<sub>''i''=1…''n''</sub>&nbsp;Δ<sub>''i''</sub>. A ''Riemann sum'' of a function ''f'' with respect to such a tagged partition is defined as
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:<math>\sum_{i=1}^{n} f(t_i) \Delta_i ; </math>
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thus each term of the sum is the area of a rectangle with height equal to the function value at the distinguished point of the given sub-interval, and width the same as the sub-interval width. The ''Riemann integral'' of a function ''f'' over the interval [''a'',''b''] is equal to ''S'' if:
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:For all &epsilon;&nbsp;&gt;&nbsp;0 there exists &delta;&nbsp;&gt;&nbsp;0 such that, for any tagged partition [''a'',''b''] with mesh less than &delta;, we have
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::<math>\left| S - \sum_{i=1}^{n} f(t_i)\Delta_i \right| < \epsilon.</math>
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When the chosen tags give the maximum (respectively, minimum) value of each interval, the Riemann sum becomes an upper (respectively, lower) [[Darboux integral|Darboux sum]], suggesting the close connection between the Riemann integral and the [[Darboux integral]].
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=== Lebesgue integral ===
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{{main|Lebesgue integration}}
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The Riemann integral is not defined for a wide range of functions and situations of importance in applications (and of interest in theory). For example, the Riemann integral can easily integrate density to find the mass of a steel beam, but cannot accommodate a steel ball resting on it. This motivates other definitions, under which a broader assortment of functions is integrable {{Harv|Rudin|1987}}. The Lebesgue integral, in particular, achieves great flexibility by directing attention to the weights in the weighted sum.
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The definition of the Lebesgue integral thus begins with a [[measure (mathematics)|measure]], μ. In the simplest case, the [[Lebesgue measure]] μ(''A'') of an interval ''A''&nbsp;= [''a'',''b''] is its width, ''b'' &minus; ''a'', so that the Lebesgue integral agrees with the (proper) Riemann integral when both exist. In more complicated cases, the sets being measured can be highly fragmented, with no continuity and no resemblance to intervals.
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To exploit this flexibility, Lebesgue integrals reverse the approach to the weighted sum. As {{Harvtxt|Folland|1984|loc=p.&nbsp;56}} puts it, "To compute the Riemann integral of ''f'', one partitions the domain [''a'',''b''] into subintervals", while in the Lebesgue integral, "one is in effect partitioning the range of ''f''".
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One common approach first defines the integral of the [[indicator function]] of a [[Measure (mathematics)|measurable set]] ''A'' by:
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:<math>\int 1_A d\mu = \mu(A)</math>.
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This extends by linearity to a measurable [[simple function]] ''s'', which attains only a finite number, ''n'', of distinct non-negative values:
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:<math>\begin{align}
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\int s \, d\mu &{}= \int\left(\sum_{i=1}^{n} a_i 1_{A_i}\right) d\mu \\
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&{}= \sum_{i=1}^{n} a_i\int 1_{A_i} \, d\mu \\
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&{}= \sum_{i=1}^{n} a_i \, \mu(A_i)
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\end{align}</math>
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(where the image of ''A''<sub>''i''</sub> under the simple function ''s'' is the constant value ''a''<sub>''i''</sub>). Thus if ''E'' is a measurable set one defines
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:<math> \int_E s \, d\mu = \sum_{i=1}^{n} a_i \, \mu(A_i \cap E) . </math>
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Then for any non-negative [[measurable function]] ''f'' one defines
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:<math>\int_E f \, d\mu = \sup\left\{\int_E s \, d\mu\, \colon 0 \leq s\leq f\text{ and } s\text{ is a simple function}\right\};</math>
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that is, the integral of ''f'' is set to be the [[supremum]] of all the integrals of simple functions that are less than or equal to ''f''.
  +
A general measurable function ''f'', is split into its positive and negative values by defining
  +
:<math>\begin{align}
  +
f^+(x) &{}= \begin{cases}
  +
f(x), & \text{if } f(x) > 0 \\
  +
0, & \text{otherwise}
  +
\end{cases} \\
  +
f^-(x) &{}= \begin{cases}
  +
-f(x), & \text{if } f(x) < 0 \\
  +
0, & \text{otherwise}
  +
\end{cases}
  +
\end{align}</math>
  +
Finally, ''f'' is Lebesgue integrable if
  +
:<math>\int_E |f| \, d\mu < \infty , \,\!</math>
  +
and then the integral is defined by
  +
:<math>\int_E f \, d\mu = \int_E f^+ \, d\mu - \int_E f^- \, d\mu . \,\!</math>
  +
  +
When the measure space on which the functions are defined is also a [[Locally compact space|locally compact]] [[topological space]] (as is the case with the real numbers '''R'''), measures compatible with the topology in a suitable sense ([[Radon measure]]s, of which the Lebesgue measure is an example) and integral with respect to them can be defined differently, starting from the integrals of [[continuous function]]s with [[support (mathematics)#Compact support|compact support]]. More precisely, the compactly supported functions form a [[vector space]] that carries a natural [[topological space|topology]], and a (Radon) measure can be defined as ''any'' continuous [[linear map|linear]] functional on this space; the value of a measure at a compactly supported function is then also by definition the integral of the function. One then proceeds to expand the measure (the integral) to more general functions by continuity, and defines the measure of a set as the integral of its indicator function. This is the approach taken by {{Harvtxt|Bourbaki|2004}} and a certain number of other authors. For details see [[Radon measure#Radon measures on locally compact spaces|Radon measures]].
  +
  +
=== Other integrals ===
  +
Although the Riemann and Lebesgue integrals are the most important definitions of the integral, a number of others exist, including:
  +
* The [[Riemann-Stieltjes integral]], an extension of the Riemann integral.
  +
* The [[Lebesgue-Stieltjes integration|Lebesgue-Stieltjes integral]], further developed by [[Johann Radon]], which generalizes the [[Riemann-Stieltjes integral|Riemann-Stieltjes]] and [[Lebesgue integration|Lebesgue integrals]].
  +
* The [[Daniell integral]], which subsumes the [[Lebesgue integration|Lebesgue integral]] and [[Lebesgue-Stieltjes integration|Lebesgue-Stieltjes integral]] without the dependence on [[measure (mathematics)|measure]]s.
  +
* The [[Henstock-Kurzweil integral]], variously defined by [[Arnaud Denjoy]], [[Oskar Perron]], and (most elegantly, as the gauge integral) [[Jaroslav Kurzweil]], and developed by [[Ralph Henstock]]. Robert Bartle<ref>{{cite journal|first=Robert G.|last=Bartle|author-link=Robert G. Bartle|title=Return of the Riemann Integral|journal=The American Mathematical Monthly|volume=103|pages=625-632|date=1996}}</ref> gave perhaps the most compelling introduction to this integral in a paper for which he earned a writing award from the [[Mathematical Association of America]].
  +
* The [[Itō calculus|Itō integral]] and [[Stratonovich integral]], which define integration with respect to stochastic processes such as [[Wiener process|Brownian motion]].
  +
<!--* The [[Darboux integral]], equivalent to the Riemann integral.-->
  +
<!--* The [[Haar integral]], which is the Lebesgue integral with [[Haar measure]].-->
  +
  +
==Properties of integration==
  +
===Linearity===
  +
  +
*The collection of Riemann integrable functions on a closed interval [''a'', ''b''] forms a [[vector space]] under the operations of pointwise addition and multiplication by a scalar, and the operation of integration
  +
::<math> f \mapsto \int_a^b f \; dx</math>
  +
<!--- redundant
  +
for an integrable [[function (mathematics)|function]] ''f'' on [''a'', ''b'']
  +
--->
  +
:is a [[linear functional]] on this vector space. Thus, firstly, the collection of integrable functions is closed under taking [[linear combination]]s; and, secondly, the integral of a linear combination is the linear combination of the integrals,
  +
  +
<!--- leftover from the past text; redundant
  +
:For example, in Riemann integration, if ''f'' and ''g'' are [[real number|real-valued]] integrable functions on a [[closed set|closed]] and [[bounded set|bounded]] [[interval (mathematics)|interval]] [''a'', ''b''], and ''&alpha;'' and ''&beta;'' are real numbers, then the function ''&alpha;f'' + ''&beta;g'' defined by (''&alpha;f'' + ''&beta;g'')(''x'') = ''&alpha;f''(''x'') + ''&beta;g''(''x'') for all ''x'' in [''a'', ''b''] is integrable, with
  +
--->
  +
::<math> \int_a^b (\alpha f + \beta g)(x) \, dx = \alpha \int_a^b f(x) \,dx + \beta \int_a^b g(x) \, dx. \,</math>
  +
  +
*Similarly, the set of [[real number|real]]-valued Lebesgue integrable functions on a given [[Measure (mathematics)|measure space]] ''E'' with measure ''μ'' is closed under taking linear combinations and hence form a vector space, and the Lebesgue integral
  +
  +
:: <math> f\mapsto \int_E f d\mu </math>
  +
  +
:is a linear functional on this vector space, so that
  +
  +
::<math> \int_E (\alpha f + \beta g) \, d\mu = \alpha \int_E f \, d\mu + \beta \int_E g \, d\mu. </math>
  +
  +
*More generally, consider the vector space of all [[measurable function]]s on a measure space (''E'',''μ''), taking values in a [[Locally compact space|locally compact]] [[complete metric space|complete]] [[topological vector space]] ''V'' over a locally compact [[Topological ring|topological field]] ''K'', ''f'' : ''E'' → ''V''. Then one may define an abstract integration map assigning to each function ''f'' an element of ''V'' or the symbol ''∞'',
  +
::<math> f\mapsto\int_E f d\mu, \,</math>
  +
:that is compatible with linear combinations. In this situation the linearity holds for the subspace of functions whose integral is an element of ''V'' (i.e. "finite"). The most important special cases arise when ''K'' is '''R''', '''C''', or a finite extension of the field '''Q'''<sub>''p''</sub> of [[p-adic number]]s, and ''V'' is a finite-dimensional vector space over ''K'', and when ''K''='''C''' and ''V'' is a complex [[Hilbert space]].
  +
  +
Linearity, together with some natural continuity properties and normalisation for a certain class of "simple" functions, may be used to give an alternative definition of the integral. This is the approach of [[Daniell integral|Daniell]] for the case of real-valued functions on a set ''X'', generalized by [[Nicolas Bourbaki]] to functions with values in a locally compact topological vector space. See {{Harv|Hildebrandt|1953}} for an axiomatic characterisation of the integral.
  +
  +
=== Inequalities for integrals ===
  +
  +
A number of general inequalities hold for Riemann-integrable [[function (mathematics)|functions]] defined on a [[closed set|closed]] and [[bounded set|bounded]] [[interval (mathematics)|interval]] [''a'', ''b''] and can be generalized to other notions of integral (Lebesgue and Daniell).
  +
  +
* ''Upper and lower bounds.'' An integrable function ''f'' on [''a'', ''b''], is necessarily [[bounded function|bounded]] on that interval. Thus there are [[real number]]s ''m'' and ''M'' so that ''m'' ≤ ''f''&thinsp;(''x'') ≤ ''M'' for all ''x'' in [''a'', ''b'']. Since the lower and upper sums of ''f'' over [''a'', ''b''] are therefore bounded by, respectively, ''m''(''b'' &minus; ''a'') and ''M''(''b'' &minus; ''a''), it follows that
  +
:: <math> m(b - a) \leq \int_a^b f(x) \, dx \leq M(b - a). </math>
  +
  +
* ''Inequalities between functions.'' If ''f''(''x'') ≤ ''g''(''x'') for each ''x'' in [''a'', ''b''] then each of the upper and lower sums of ''f'' is bounded above by the upper and lower sums, respectively, of ''g''. Thus
  +
:: <math> \int_a^b f(x) \, dx \leq \int_a^b g(x) \, dx. </math>
  +
:This is a generalization of the above inequalities, as ''M''(''b'' &minus; ''a'') is the integral of the constant function with value ''M'' over [''a'', ''b''].
  +
  +
* ''Subintervals.'' If [''c'', ''d''] is a subinterval of [''a'', ''b''] and ''f''(''x'') is non-negative for all ''x'', then
  +
:: <math> \int_c^d f(x) \, dx \leq \int_a^b f(x) \, dx. </math>
  +
  +
* ''Products and absolute values of functions.'' If ''f'' and ''g'' are two functions then we may consider their [[pointwise product]]s and powers, and [[absolute value]]s:
  +
:: <math>
  +
(fg)(x)= f(x) g(x), \; f^2 (x) = (f(x))^2, \; |f| (x) = |f(x)|.\,</math>
  +
:If ''f'' is Riemann-integrable on [''a'', ''b''] then the same is true for |''f''|, and
  +
:: <math>\left| \int_a^b f(x) \, dx \right| \leq \int_a^b | f(x) | \, dx. </math>
  +
:Moreover, if ''f'' and ''g'' are both Riemann-integrable then ''f'' <sup>2</sup>, ''g'' <sup>2</sup>, and ''fg'' are also Riemann-integrable, and
  +
:: <math>\left( \int_a^b (fg)(x) \, dx \right)^2 \leq \left( \int_a^b f(x)^2 \, dx \right) \left( \int_a^b g(x)^2 \, dx \right). </math>
  +
:This inequality, known as the [[Cauchy–Schwarz inequality]], plays a prominent role in [[Hilbert space]] theory, where the left hand side is interpreted as the [[Inner product space|inner product]] of two square-integrable functions ''f'' and ''g'' on the interval [''a'', ''b''].
  +
  +
* ''Hölder's inequality.'' Suppose that ''p'' and ''q'' are two real numbers, 1 ≤ ''p'', ''q'' ≤ ∞ with 1/''p'' + 1/''q'' = 1, and ''f'' and ''g'' are two Riemann-integrable functions. Then the functions |''f''|<sup>''p''</sup> and |''g''|<sup>''q''</sup> are also integrable and the following [[Hölder's inequality]] holds:
  +
:<math>\left|\int f(x)g(x)\,dx\right| \leq
  +
\left(\int \left|f(x)\right|^p\,dx \right)^{1/p} \left(\int\left|g(x)\right|^q\,dx\right)^{1/q}.</math>
  +
:For ''p'' = ''q'' = 2, Hölder's inequality becomes the Cauchy–Schwarz inequality.
  +
  +
* ''Minkowski inequality''. Suppose that ''p'' ≥ 1 is a real number and ''f'' and ''g'' are Riemann-integrable functions. Then |''f''|<sup>''p''</sup>, |''g''|<sup>''p''</sup> and |''f'' + ''g''|<sup>''p''</sup> are also Riemann integrable and the following [[Minkowski inequality]] holds:
  +
:<math>\left(\int \left|f(x)+g(x)\right|^p\,dx \right)^{1/p} \leq
  +
\left(\int \left|f(x)\right|^p\,dx \right)^{1/p} +
  +
\left(\int \left|g(x)\right|^p\,dx \right)^{1/p}.</math>
  +
: An analogue of this inequality for Lebesgue integral is used in construction of [[Lp space|L<sup>p</sup> spaces]].
  +
  +
===Conventions===
  +
  +
In this section ''f'' is a [[real number|real-]]valued Riemann-integrable [[function (mathematics)|function]]. The integral
  +
:<math> \int_a^b f(x) \, dx </math>
  +
over an interval [''a'', ''b''] is defined if ''a'' &lt; ''b''. This means that the upper and lower sums of the function ''f'' are evaluated on a partition ''a'' = ''x''<sub>0</sub> ≤ ''x''<sub>1</sub> ≤ . . . ≤ ''x''<sub>''n''</sub> = ''b'' whose values ''x''<sub>''i''</sub> are increasing. Geometrically, this signifies that integration takes place "left to right", evaluating ''f'' within intervals [''x''<sub>&thinsp;''i''</sub>&thinsp;, ''x''<sub>&thinsp;''i''&thinsp;+1</sub>] where an interval with a higher index lies to the right of one with a lower index. The values ''a'' and ''b'', the end-points of the [[interval (mathematics)|interval]], are called the [[limits of integration]] of ''f''. Integrals can also be defined if ''a'' &gt; ''b'':
  +
  +
* ''Reversing limits of integration.'' If ''a'' &gt; ''b'' then define
  +
:: <math>\int_a^b f(x) \, dx = - \int_b^a f(x) \, dx. </math>
  +
This, with ''a'' = ''b'', implies:
  +
* ''Integrals over intervals of length zero.'' If ''a'' is a [[real number]] then
  +
:: <math>\int_a^a f(x) \, dx = 0. </math>
  +
  +
The first convention is necessary in consideration of taking integrals over subintervals of [''a'', ''b'']; the second says that an integral taken over a degenerate interval, or a [[Point (geometry)|point]], should be [[0 (number)|zero]]. One reason for the first convention is that the integrability of ''f'' on an interval [''a'', ''b''] implies that ''f'' is integrable on any subinterval [''c'', ''d''], but in particular integrals have the property that:
  +
  +
* ''Additivity of integration on intervals.'' If ''c'' is any [[element (mathematics)|element]] of [''a'', ''b''], then
  +
:: <math> \int_a^b f(x) \, dx = \int_a^c f(x) \, dx + \int_c^b f(x) \, dx.</math>
  +
With the first convention the resulting relation
  +
: <math>\begin{align}
  +
\int_a^c f(x) \, dx &{}= \int_a^b f(x) \, dx - \int_c^b f(x) \, dx \\
  +
&{} = \int_a^b f(x) \, dx + \int_b^c f(x) \, dx
  +
\end{align}</math>
  +
is then well-defined for any cyclic permutation of ''a'', ''b'', and ''c''.
  +
  +
Instead of viewing the above as conventions, one can also adopt the point of view that integration is performed on [[Orientability|''oriented'' manifolds]] only. If ''M'' is such an oriented ''m''-dimensional manifold, and ''M' '' is the same manifold with opposed orientation and ''ω'' is an ''m''-form, then one has (see below for integration of differential forms):
  +
: <math>\int_M \omega = - \int_{M'} \omega \,.</math>
  +
  +
==Fundamental theorem of calculus==
  +
{{main|Fundamental theorem of calculus}}
  +
  +
The ''fundamental theorem of calculus'' is the statement that [[derivative|differentiation]] and [[integral|integration]] are inverse operations: if a [[continuous function]] is first integrated and then differentiated, the original function is retrieved. An important consequence, sometimes called the ''second fundamental theorem of calculus'', allows one to compute integrals by using an [[antiderivative]] of the function to be integrated.
  +
  +
===Statements of theorems===
  +
* ''Fundamental theorem of calculus.'' Let ''f'' be a [[real number|real-valued]] integrable [[function (mathematics)|function]] defined on a [[Interval (mathematics)|closed interval]] [''a'', ''b'']. If ''F'' is defined for ''x'' in [''a'', ''b''] by
  +
::<math>F(x) = \int_a^x f(t)\, dt.</math>
  +
:then ''F'' is [[Continuous function|continuous]] on [''a'', ''b'']. If ''f'' is continuous at ''x'' in [''a'', ''b''], then ''F'' is [[differential calculus|differentiable]] at ''x'', and ''F''&thinsp;&prime;(''x'') = ''f''(''x'').
  +
  +
* ''Second fundamental theorem of calculus''. Let ''f'' be a real-valued integrable function defined on a closed interval [''a'', ''b'']. If ''F'' is a function such that ''F''&thinsp;&prime;(''x'') = ''f''(''x'') for all ''x'' in [''a'', ''b''] (that is, ''F'' is an [[antiderivative]] of ''f''), then
  +
::<math>\int_a^b f(t)\, dt = F(b) - F(a).</math>
  +
  +
* ''Corollary''. If ''f'' is a continuous function on [''a'', ''b''], then ''f'' is integrable on [''a'', ''b''], and ''F'', defined by
  +
::<math>F(x) = \int_a^x f(t) \, dt</math>
  +
:is an anti-derivative of ''f'' on [''a'', ''b'']. Moreover,
  +
::<math>\int_a^b f(t) \, dt = F(b) - F(a).</math>
  +
  +
== Extensions ==
  +
=== Improper integrals ===
  +
{{main|Improper integral}}
  +
[[Image:Improper integral.svg|right|thumb|The [[improper integral]]<br /><math>\int_{0}^{\infty} \frac{dx}{(x+1)\sqrt{x}} = \pi</math><br /> has unbounded intervals for both domain and range.]]
  +
A "proper" Riemann integral assumes the integrand is defined and finite on a closed and bounded interval, bracketed by the limits of integration. An improper integral occurs when one or more of these conditions is not satisfied. In some cases such integrals may be defined by considering the [[limit (mathematics)|limit]] of a [[sequence]] of proper [[Riemann integral]]s on progressively larger intervals.
  +
  +
If the interval is unbounded, for instance at its upper end, then the improper integral is the limit as that endpoint goes to infinity.
  +
:<math>\int_{a}^{\infty} f(x)dx = \lim_{b \to \infty} \int_{a}^{b} f(x)dx</math>
  +
If the integrand is only defined or finite on a half-open interval, for instance (''a'',''b''], then again a limit may provide a finite result.
  +
:<math>\int_{a}^{b} f(x)dx = \lim_{\epsilon \to 0} \int_{a+\epsilon}^{b} f(x)dx</math>
  +
  +
That is, the improper integral is the [[limit (mathematics)|limit]] of proper integrals as one endpoint of the interval of integration approaches either a specified [[real number]], or ∞, or &minus;∞. In more complicated cases, limits are required at both endpoints, or at interior points.
  +
  +
Consider, for example, the function <math>\tfrac{1}{(x+1)\sqrt{x}}</math> integrated from 0 to ∞ (shown right). At the lower bound, as ''x'' goes to 0 the function goes to ∞, and the upper bound is itself ∞, though the function goes to 0. Thus this is a doubly improper integral. Integrated, say, from 1 to 3, an ordinary Riemann sum suffices to produce a result of <math>\tfrac{\pi}{6}</math>. To integrate from 1 to ∞, a Riemann sum is not possible. However, any finite upper bound, say ''t'' (with ''t''&nbsp;&gt;&nbsp;1), gives a well-defined result, <math>\tfrac{\pi}{2} - 2\arctan \tfrac{1}{\sqrt{t}}</math>. This has a finite limit as ''t'' goes to infinity, namely <math>\tfrac{\pi}{2}</math>. Similarly, the integral from <sup>1</sup>⁄<sub>3</sub> to 1 allows a Riemann sum as well, coincidentally again producing <math>\tfrac{\pi}{6}</math>. Replacing <sup>1</sup>⁄<sub>3</sub> by an arbitrary positive value ''s'' (with ''s''&nbsp;&lt;&nbsp;1) is equally safe, giving <math>-\tfrac{\pi}{2} + 2\arctan\tfrac{1}{\sqrt{s}}</math>. This, too, has a finite limit as ''s'' goes to zero, namely <math>\tfrac{\pi}{2}</math>. Combining the limits of the two fragments, the result of this improper integral is
  +
:<math>\begin{align}
  +
\int_{0}^{\infty} \frac{dx}{(x+1)\sqrt{x}} &{} = \lim_{s \to 0} \int_{s}^{1} \frac{dx}{(x+1)\sqrt{x}}
  +
+ \lim_{t \to \infty} \int_{1}^{t} \frac{dx}{(x+1)\sqrt{x}} \\
  +
&{} = \lim_{s \to 0} \left( - \frac{\pi}{2} + 2 \arctan\frac{1}{\sqrt{s}} \right)
  +
+ \lim_{t \to \infty} \left( \frac{\pi}{2} - 2 \arctan\frac{1}{\sqrt{t}} \right) \\
  +
&{} = \frac{\pi}{2} + \frac{\pi}{2} \\
  +
&{} = \pi .
  +
\end{align}</math>
  +
This process is not guaranteed success; a limit may fail to exist, or may be unbounded. For example, over the bounded interval 0 to 1 the integral of <math>\tfrac{1}{x^2}</math> does not converge; and over the unbounded interval 1 to ∞ the integral of <math>\tfrac{1}{\sqrt{x}}</math> does not converge.
  +
  +
<!-- [[Image:Improper integral unbounded internally.svg|right|thumb|The [[improper integral]]<br /><math>\int_{-1}^{1} \frac{dx}{\sqrt[3]{x^2}} = 6</math><br /> is unbounded internally, but both left and right limits exist.]] -->
  +
It may also happen that an integrand is unbounded at an interior point, in which case the integral must be split at that point, and the limit integrals on both sides must exist and must be bounded. Thus
  +
:<math>\begin{align}
  +
\int_{-1}^{1} \frac{dx}{\sqrt[3]{x^2}} &{} = \lim_{s \to 0} \int_{-1}^{-s} \frac{dx}{\sqrt[3]{x^2}}
  +
+ \lim_{t \to 0} \int_{t}^{1} \frac{dx}{\sqrt[3]{x^2}} \\
  +
&{} = \lim_{s \to 0} 3(1-\sqrt[3]{s}) + \lim_{t \to 0} 3(1-\sqrt[3]{t}) \\
  +
&{} = 3 + 3 \\
  +
&{} = 6.
  +
\end{align}</math>
  +
But the similar integral
  +
:<math> \int_{-1}^{1} \frac{dx}{x} \,\!</math>
  +
cannot be assigned a value in this way, as the integrals above and below zero do not independently converge. (However, see [[Cauchy principal value]].)
  +
  +
=== Multiple integration ===
  +
{{main article|Multiple integral}}
  +
[[Image:Volume under surface.png|right|thumb|Double integral as volume under a surface.]]
  +
Integrals can be taken over regions other than intervals. In general, an integral over a [[Set (mathematics)|set]] ''E'' of a function ''f'' is written:
  +
  +
:<math>\int_E f(x) \, dx.</math>
  +
  +
Here ''x'' need not be a real number, but can be another suitable quantity, for instance, a [[Vector (geometric)|vector]] in '''R'''<sup>3</sup>. [[Fubini's theorem]] shows that such integrals can be rewritten as an '''[[Multiple integral|iterated integral]]'''. In other words, the integral can be calculated by integrating one coordinate at a time.
  +
  +
Just as the definite integral of a positive function of one variable represents the [[area]] of the region between the graph of the function and the ''x''-axis, the '''double integral''' of a positive function of two variables represents the [[volume]] of the region between the surface defined by the function and the plane which contains its [[domain (mathematics)|domain]]. (The same volume can be obtained via the '''triple integral''' &mdash; the integral of a function in three variables &mdash; of the constant function ''f''(''x'', ''y'', ''z'') = 1 over the above-mentioned region between the surface and the plane.) If the number of variables is higher, then the integral represents a [[Fourth dimension|hypervolume]], a volume of a solid of more than three dimensions that cannot be graphed.
  +
  +
For example, the volume of the [[cuboid]] of sides 4 &times; 6 &times; 5 may be obtained in two ways:
  +
* By the double integral
  +
:: <math>\iint_D 5 \ dx\, dy</math>
  +
: of the function ''f''(''x'', ''y'') = 5 calculated in the region ''D'' in the ''xy''-plane which is the base of the cuboid. For example, if a rectangular base of such a cuboid is given via the ''xy'' inequalities 2 ≤ ''x'' ≤ 7, 4 ≤ ''y'' ≤ 9, our above double integral now reads
  +
  +
::<math>\int_2^7 \int_4^9 \ 5 \ dx\, dy</math>
  +
  +
:From here, integration is conducted with respect to either ''x'' or ''y'' first; in this example, integration is first done with respect to ''x'' as the interval corresponding to ''x'' is the inner integral. Once the first integration is completed via the <math>F(b) - F(a)</math> method or otherwise, the result is again integrated with respect to the other variable. The result will equate to the volume under the surface.
  +
  +
* By the triple integral
  +
::<math>\iiint_\mathrm{cuboid} 1 \, dx\, dy\, dz</math>
  +
:of the constant function 1 calculated on the cuboid itself.
  +
  +
=== Line integrals ===
  +
{{main|Line integral}}
  +
[[Image:Line-Integral.gif|right|thumb|A line integral sums together elements along a curve.]]
  +
The concept of an integral can be extended to more general domains of integration, such as curved lines and surfaces. Such integrals are known as line integrals and surface integrals respectively. These have important applications in physics, as when dealing with [[vector field]]s.
  +
  +
A '''line integral''' (sometimes called a '''path integral''') is an integral where the [[function (mathematics)|function]] to be integrated is evaluated along a [[curve]]. Various different line integrals are in use. In the case of a closed curve it is also called a '''contour integral'''.
  +
  +
The function to be integrated may be a [[scalar field]] or a [[vector field]]. The value of the line integral is the sum of values of the field at all points on the curve, weighted by some scalar function on the curve (commonly [[arc length]] or, for a vector field, the [[Inner product space|scalar product]] of the vector field with a [[Differential (infinitesimal)|differential]] vector in the curve). This weighting distinguishes the line integral from simpler integrals defined on [[interval (mathematics)|interval]]s. Many simple formulas in physics have natural continuous analogs in terms of line integrals; for example, the fact that [[Mechanical work|work]] is equal to [[force]] multiplied by distance may be expressed (in terms of vector quantities) as:
  +
:<math>W=\vec F\cdot\vec d</math>;
  +
which is paralleled by the line integral:
  +
:<math>W=\int_C \vec F\cdot d\vec s</math>;
  +
which sums up vector components along a continuous path, and thus finds the work done on an object moving through a field, such as an electric or gravitational field
  +
  +
=== Surface integrals ===
  +
{{main|Surface integral}}
  +
[[Image:Surface integral illustration.png|right|thumb|The definition of surface integral relies on splitting the surface into small surface elements.]]
  +
A '''surface integral''' is a definite integral taken over a [[surface]] (which may be a curved set in [[space]]); it can be thought of as the [[Multiple integral|double integral]] analog of the [[line integral]]. The function to be integrated may be a [[scalar field]] or a [[vector field]]. The value of the surface integral is the sum of the field at all points on the surface. This can be achieved by splitting the surface into surface elements, which provide the partitioning for Riemann sums.
  +
  +
For an example of applications of surface integrals, consider a vector field '''v''' on a surface ''S''; that is, for each point '''x''' in ''S'', '''v'''('''x''') is a vector. Imagine that we have a fluid flowing through ''S'', such that '''v'''('''x''') determines the velocity of the fluid at '''x'''. The [[flux]] is defined as the quantity of fluid flowing through ''S'' in unit amount of time. To find the flux, we need to take the [[dot product]] of '''v''' with the unit [[surface normal]] to ''S'' at each point, which will give us a scalar field, which we integrate over the surface:
  +
:<math>\int_S {\mathbf v}\cdot \,d{\mathbf {S}}.</math>
  +
The fluid flux in this example may be from a physical fluid such as water or air, or from electrical or magnetic flux. Thus surface integrals have applications in [[physics]], particularly with the [[classical theory]] of [[electromagnetism]].
  +
  +
=== Integrals of differential forms ===
  +
{{main|differential form}}
  +
  +
A [[differential form]] is a mathematical concept in the fields of [[multivariable calculus]], [[differential topology]] and [[tensor]]s. The modern notation for the differential form, as well as the idea of the differential forms as being the [[Exterior algebra|wedge products]] of [[exterior derivative]]s forming an [[exterior algebra]], was introduced by [[Élie Cartan]].
  +
  +
We initially work in an [[open set]] in '''R'''<sup>''n''</sup>.
  +
A 0-form is defined to be a [[smooth function]] ''f''.
  +
When we integrate a [[function (mathematics)|function]] ''f'' over an ''m''-[[dimension]]al subspace ''S'' of '''R'''<sup>''n''</sup>, we write it as
  +
:<math>\int_S f\,dx^1 \cdots dx^m.</math>
  +
  +
(The superscripts are indices, not exponents.) We can consider ''dx''<sup>1</sup> through ''dx''<sup>''n''</sup> to be formal objects themselves, rather than tags appended to make integrals look like [[Riemann sum]]s. Alternatively, we can view them as [[One-form|covectors]], and thus a [[measure (mathematics)|measure]] of "density" (hence integrable in a general sense). We call the ''dx''<sup>1</sup>, …,''dx<sup>n</sup>'' ''basic'' [[one-form|1-''forms'']].
  +
  +
We define the [[Exterior algebra|wedge product]], "∧", a bilinear "multiplication" operator on these elements, with the ''alternating'' property that
  +
  +
:<math> dx^a \wedge dx^a = 0 \,\!</math>
  +
  +
for all indices ''a''. Note that alternation along with linearity implies ''dx''<sup>''b''</sup>∧''dx''<sup>''a''</sup>&nbsp;= −''dx''<sup>''a''</sup>∧''dx''<sup>''b''</sup>. This also ensures that the result of the wedge product has an [[Orientation (mathematics)|orientation]].
  +
  +
We define the set of all these products to be ''basic'' 2-''forms'', and similarly we define the set of products of the form ''dx''<sup>''a''</sup>∧''dx''<sup>''b''</sup>∧''dx''<sup>''c''</sup> to be ''basic'' 3-''forms''. A general ''k''-form is then a weighted sum of basic ''k-''forms, where the weights are the smooth functions ''f''. Together these form a [[vector space]] with basic ''k''-forms as the basis vectors, and 0-forms (smooth functions) as the field of scalars. The wedge product then extends to ''k''-forms in the natural way. Over '''R'''<sup>''n''</sup> at most ''n'' covectors can be linearly independent, thus a ''k-''form with ''k''&nbsp;&gt;&nbsp;''n'' will always be zero, by the alternating property.
  +
  +
In addition to the wedge product, there is also the [[exterior derivative]] operator '''d'''. This operator maps ''k''-forms to (''k''+1)-forms. For a ''k''-form ω = ''f'' ''dx<sup>a</sup>'' over '''R'''<sup>''n''</sup>, we define the action of '''d''' by:
  +
  +
:<math>{\bold d}{\omega} = \sum_{i=1}^n \frac{\partial f}{\partial x_i} dx^i \wedge dx^a.</math>
  +
  +
with extension to general ''k''-forms occurring linearly.
  +
  +
This more general approach allows for a more natural coordinate-free approach to integration on [[manifold]]s. It also allows for a natural generalisation of the [[fundamental theorem of calculus]], called [[Stokes' theorem]], which we may state as
  +
  +
:<math>\int_{\Omega} {\bold d}\omega = \int_{\partial\Omega} \omega \,\!</math>
  +
  +
where ω is a general ''k''-form, and ∂Ω denotes the [[boundary (topology)|boundary]] of the region Ω. Thus in the case that ω is a 0-form and Ω is a closed interval of the real line, this reduces to the [[fundamental theorem of calculus]]. In the case that ω is a 1-form and Ω is a 2-dimensional region in the plane, the theorem reduces to [[Green's theorem]]. Similarly, using 2-forms, and 3-forms and [[Hodge dual]]ity, we can arrive at [[Stokes' theorem]] and the [[divergence theorem]]. In this way we can see that differential forms provide a powerful unifying view of integration.
  +
  +
== Methods ==
  +
=== Computing integrals ===
  +
The most basic technique for computing definite integrals of one real variable is based on the [[fundamental theorem of calculus]]. It proceeds like this:
  +
# Let ''f''(''x'') be the function of ''x'' to be integrated over a given interval [''a'', ''b''].
  +
# Find an antiderivative of ''f'', that is, a function ''F'' such that ''F' '' = ''f'' on the interval.
  +
# Then, by the fundamental theorem of calculus, provided the integrand and integral have no [[Mathematical singularity|singularities]] on the path of integration,
  +
#:<math>\int_a^b f(x)\,dx = F(b)-F(a).</math>
   
 
Note that the integral is not actually the antiderivative, but the fundamental theorem allows us to use antiderivatives to evaluate definite integrals.
 
Note that the integral is not actually the antiderivative, but the fundamental theorem allows us to use antiderivatives to evaluate definite integrals.
   
The difficult step is finding an antiderivative of ''f''. It is rarely possible to glance at a function and write down its antiderivative. More often, it is necessary to use one of the many techniques that have been developed to evaluate integrals. Most of these techniques rewrite one integral as a different one which is hopefully more tractable. Techniques include:
+
The difficult step is often finding an antiderivative of ''f''. It is rarely possible to glance at a function and write down its antiderivative. More often, it is necessary to use one of the many techniques that have been developed to evaluate integrals. Most of these techniques rewrite one integral as a different one which is hopefully more tractable. Techniques include:
* [[Integration by substitution|Integration by substitution]]
+
* [[Integration by substitution]]
 
* [[Integration by parts]]
 
* [[Integration by parts]]
  +
* [[Order of integration (calculus)|Changing the order of integration]]
 
* [[trigonometric substitution|Integration by trigonometric substitution]]
 
* [[trigonometric substitution|Integration by trigonometric substitution]]
 
* [[Partial fractions in integration|Integration by partial fractions]]
 
* [[Partial fractions in integration|Integration by partial fractions]]
  +
* [[Integration by reduction formulae]]
  +
* [[Integration using parametric derivatives]]
  +
* [[Integrating trigonometric products as complex exponentials]]
  +
* [[Differentiation under the integral sign]]
  +
* [[Methods of contour integration| Contour Integration]]
   
Even if these techniques fail, it may still be possible to evaluate a given integral. The next most common technique is [[Residue (complex analysis)|residue calculus]]. There are also many less common ways of calculating definite integrals; for instance, [[Parseval's identity]] can be used to transform an integral over a rectangular region into an infinite sum. Occasionally, an integral can be evaluated by a trick; for an example of this, see [[Gaussian integral]].
+
Even if these techniques fail, it may still be possible to evaluate a given integral. Many [[nonelementary integral]]s can be expanded in a [[Taylor series]] and integrated term by term. Occasionally, the resulting infinite series can be summed analytically. The method of convolution using [[Meijer G-function]]s can also be used, assuming that the integrand can be written as a product of Meijer G-functions. There are also many less common ways of calculating definite integrals; for instance, [[Parseval's identity]] can be used to transform an integral over a rectangular region into an infinite sum. Occasionally, an integral can be evaluated by a trick; for an example of this, see [[Gaussian integral]].
   
 
Computations of volumes of [[solid of revolution|solids of revolution]] can usually be done with [[disk integration]] or [[shell integration]].
 
Computations of volumes of [[solid of revolution|solids of revolution]] can usually be done with [[disk integration]] or [[shell integration]].
   
Specific results which have been worked out by various techniques are collected in the [[list of integrals]].
+
Specific results which have been worked out by various techniques are collected in the [[Lists of integrals|list of integrals]].
   
=== Approximation of definite integrals ===
+
=== Symbolic algorithms ===
  +
{{main|Symbolic integration}}
Definite integrals may be approximated using several methods of [[numerical integration]]. One popular method, called the [[rectangle method]], relies on dividing the region under the function into a series of rectangles and finding the sum. Other well-known methods are the [[trapezoidal rule]] and [[Simpson's rule]].
 
   
  +
Many problems in mathematics, physics, and engineering involve integration where an explicit formula for the integral is desired. Extensive [[Lists of integrals|tables of integrals]] have been compiled and published over the years for this purpose. With the spread of [[computer]]s, many professionals, educators, and students have turned to [[computer algebra system]]s that are specifically designed to perform difficult or tedious tasks, including integration. Symbolic integration presents a special challenge in the development of such systems.
Some integrals cannot be found exactly, and others are so complex that finding the exact answer would be extremely time-consuming or computationally-intensive. Approximation, however, is a process which relies only on variable substitution, multiplication, addition, and [[division (mathematics)|division]]. It can be done easily and quickly by modern graphing calculators and computers. Many real-world applications of calculus rely on calculating integrals approximately because of the complexity of formulas and since an exact answer is unnecessary.
 
   
  +
A major mathematical difficulty in symbolic integration is that in many cases, a closed formula for the antiderivative of a rather simple-looking function does not exist. For instance, it is known that the antiderivatives of the functions ''exp'' ( ''x''<sup>2</sup>), ''x''<sup>''x''</sup> and sin&nbsp;''x''&nbsp;/''x'' cannot be expressed in the closed form involving only [[rational function|rational]] and [[exponential function|exponential]] functions, [[logarithm]], [[trigonometric function|trigonometric]] and [[inverse trigonometric function]]s, and the operations of multiplication and composition; in other words, none of the three given functions is integrable in [[elementary function]]s. [[Differential Galois theory]] provides general criteria that allow one to determine whether the antiderivative of an elementary function is elementary. Unfortunately, it turns out that functions with closed expressions of antiderivatives are the exception rather than the rule. Consequently, computerized algebra systems have no hope of being able to find an antiderivative for a randomly constructed elementary function. On the positive side, if the 'building blocks' for antiderivatives are fixed in advance, it may be still be possible to decide whether the antiderivative of a given function can be expressed using these blocks and operations of multiplication and composition, and to find the symbolic answer whenever it exists. The [[Risch algorithm]], implemented in [[Mathematica]] and other [[computer algebra system]]s, does just that for functions and antiderivatives built from rational functions, [[Nth root|radicals]], logarithm, and exponential functions.
=== Integrals and computerized algebra systems ===
 
Many professionals, educators, and students now use [[computerized algebra systems]] to make difficult (or simply tedious) algebra and calculus problems easier. The design of such a computer algebra system is nontrivial as systematic methods of antidifferentiation are difficult to formulate, although in many cases a definite integral can be computed without finding an antiderivative.
 
   
  +
Some special integrands occur often enough to warrant special study. In particular, it may be useful to have, in the set of antiderivatives, the [[special functions]] of [[physics]] (like the [[Associated Legendre function|Legendre functions]], the [[hypergeometric function]], the [[Gamma function]] and so on). Extending the Risch-Norman algorithm so that it includes these functions is possible but challenging.
One difficulty in computing definite integrals is that it is not always possible to find "[[closed-form expression|explicit formulae]]" for antiderivatives. For instance, there is a (nontrivial) proof that there is no nice function (e.g., involving sin, cos, exp, [[polynomial]]s, roots and so on) whose derivative is ''x''<sup>''x''</sup>. As such, computerized algebra systems have no hope of being able to find an antiderivative for this particular function. Unfortunately, functions that have nice antiderivatives are the exception. If one writes a large random expression involving [[exponential]]s and polynomials, the odds are almost nil that it will have an antiderivative. (This statement can be made formal, but it is difficult to do so.)
 
   
  +
Most humans are not able to integrate such general formulae, so in a sense computers are more skilled at integrating highly complicated formulae. Very complex formulae are unlikely to have closed-form antiderivatives, so how much of an advantage this presents is a philosophical question that is open for debate.
One of the difficulties is to decide what set of functions to use as building blocks for antiderivatives. Usually, we need a set of antiderivatives closed under, say, multiplication and composition. This set of antiderivatives should also include polynomials, perhaps quotients, exponentials, [[logarithm]]s, sines and [[cosine]]s. The [[Risch-Norman algorithm]] is able to compute any integral of such a shape; that is, if the antiderivative involves polynomials, sines, cosines, etc..., the Risch-Norman algorithm will be able to compute it. Extended versions of this algorithm are implemented in [[Mathematica]] and the [[Maple computer algebra system]].
 
   
  +
=== Numerical quadrature ===
Some special integrands occur often enough to warrant special study. In particular, it may be useful to have, in the set of antiderivatives, the [[special functions]] of [[physics]] (like the [[Legendre function]]s, the [[hypergeometric function]], the [[Gamma function]] and so on). Extending the Risch-Norman algorithm so that it includes these functions is possible but challenging.
 
  +
{{main|numerical integration}}
   
  +
The integrals encountered in a basic calculus course are deliberately chosen for simplicity; those found in real applications are not always so accommodating. Some integrals cannot be found exactly, some require special functions which themselves are a challenge to compute, and others are so complex that finding the exact answer is too slow. This motivates the study and application of numerical methods for approximating integrals, which today use [[Floating point|floating point arithmetic]] on digital electronic [[computer]]s. Many of the ideas arose much earlier, for hand calculations; but the speed of general-purpose computers like the [[ENIAC]] created a need for improvements.
Most humans are not able to integrate such general formulae, so in a sense computers are more skilled at integrating highly complicated formulae. On the other hand, very complex formulae are unlikely to have closed-form antiderivatives, so this advantage is dubious.
 
   
  +
The goals of numerical integration are accuracy, reliability, efficiency, and generality. Sophisticated methods can vastly outperform a naive method by all four measures ({{Harvnb|Dahlquist|Björck|2008}}; {{Harvnb|Kahaner|Moler|Nash|1989}}; {{Harvnb|Stoer|Bulirsch|2002}}). Consider, for example, the integral
== Improper integrals ==
 
  +
:<math> \int_{-2}^{2} \tfrac15 \left( \tfrac{1}{100}(322 + 3 x (98 + x (37 + x))) - 24 \frac{x}{1+x^2} \right) dx , </math>
Not all integrals can be evaluated using a single limit process. An integral which can only be evaluated by considering it as the limit of integrals on successively larger and larger intervals is called an '''[[improper integral]]'''. Improper integrals usually turn up when the [[range of a function|range]] of the function to be integrated is infinite or, in the case of the [[Riemann integral]], when the [[domain of a function|domain]] of the function is infinite. One common example of an improper integral is the [[Cauchy principal value]].
 
  +
which has the exact answer <sup>94</sup>⁄<sub>25</sub>&nbsp;= 3.76. (In ordinary practice the answer is not known in advance, so an important task — not explored here — is to decide when an approximation is good enough.) A “calculus book” approach divides the integration range into, say, 16 equal pieces, and computes function values.
  +
:{| cellpadding="0" cellspacing="0" class="wikitable" style="text-align:center;background-color:white"
  +
|+ Spaced function values
  +
|-
  +
! ''x''
  +
| colspan="2" | −2.00 || colspan="2" | −1.50 || colspan="2" | −1.00 || colspan="2" | −0.50 || colspan="2" | &nbsp;0.00 || colspan="2" | &nbsp;0.50 || colspan="2" | &nbsp;1.00 || colspan="2" | &nbsp;1.50 || colspan="2" | &nbsp;2.00
  +
|- style="font-size:80%"
  +
! style="font-size:125%" | ''f''(''x'')
  +
| colspan="2" | &nbsp;2.22800 || colspan="2" | &nbsp;2.45663 || colspan="2" | &nbsp;2.67200 || colspan="2" | &nbsp;2.32475 || colspan="2" | &nbsp;0.64400 || colspan="2" | −0.92575 || colspan="2" | −0.94000 || colspan="2" | −0.16963 || colspan="2" | &nbsp;0.83600
  +
|-
  +
! ''x''
  +
| &nbsp;
  +
| colspan="2" | −1.75 || colspan="2" | −1.25 || colspan="2" | −0.75 || colspan="2" | −0.25 || colspan="2" | &nbsp;0.25 || colspan="2" | &nbsp;0.75 || colspan="2" | &nbsp;1.25 || colspan="2" | &nbsp;1.75 ||
  +
|- style="font-size:80%"
  +
! style="font-size:125%" | ''f''(''x'')
  +
|
  +
| colspan="2" | &nbsp;2.33041 || colspan="2" | &nbsp;2.58562 || colspan="2" | &nbsp;2.62934 || colspan="2" | &nbsp;1.64019 || colspan="2" | −0.32444 || colspan="2" | −1.09159 || colspan="2" | −0.60387 || colspan="2" | &nbsp;0.31734 ||
  +
|- style="background-color:#aaa"
  +
| || || || || || || || || || || || || || || || || || || <!-- extra row improves column spacing -->
  +
|}
  +
[[Image:Numerical quadrature 4up.png|thumb|right|Numerical quadrature methods: <span style="color:#bc1e47">■</span>&nbsp;Rectangle, <span style="color:#fec200">■</span>&nbsp;Trapezoid, <span style="color:#0081cd">■</span>&nbsp;Romberg, <span style="color:#009246">■</span>&nbsp;Gauss]]
  +
Using the left end of each piece, the [[rectangle method]] sums 16 function values and multiplies by the step width, ''h'', here 0.25, to get an approximate value of 3.94325 for the integral. The accuracy is not impressive, but calculus formally uses pieces of infinitesimal width, so initially this may seem little cause for concern. Indeed, repeatedly doubling the number of steps eventually produces an approximation of 3.76001. However 2<sup>18</sup> pieces are required, a great computational expense for so little accuracy; and a reach for greater accuracy can force steps so small that arithmetic precision becomes an obstacle.
   
  +
A better approach replaces the horizontal tops of the rectangles with slanted tops touching the function at the ends of each piece. This [[trapezium rule]] is almost as easy to calculate; it sums all 17 function values, but weights the first and last by one half, and again multiplies by the step width. This immediately improves the approximation to 3.76925, which is noticeably more accurate. Furthermore, only 2<sup>10</sup> pieces are needed to achieve 3.76000, substantially less computation than the rectangle method for comparable accuracy.
== Definitions of the integral ==
 
The most important integrals are the [[Riemann integral]] and the [[Lebesgue integral]]. The Riemann integral was created by [[Bernhard Riemann]] in [[1854]] and was the first [[rigor]]ous definition of the integral. The Lebesgue integral was created by [[Henri Lebesgue]] to integrate a wider class of functions and to prove very strong [[theorem]]s about interchanging [[limit]]s and integrals (see Lebesgue's [[dominated convergence theorem]]).
 
   
  +
[[Romberg's method]] builds on the trapezoid method to great effect. First, the step lengths are halved incrementally, giving trapezoid approximations denoted by ''T''(''h''<sub>0</sub>), ''T''(''h''<sub>1</sub>), and so on, where ''h''<sub>''k''+1</sub> is half of ''h''<sub>''k''</sub>. For each new step size, only half the new function values need to be computed; the others carry over from the previous size (as shown in the table above). But the really powerful idea is to [[Interpolation|interpolate]] a polynomial through the approximations, and extrapolate to ''T''(0). With this method a numerically ''exact'' answer here requires only four pieces (five function values)! The [[Lagrange polynomial]] interpolating {''h''<sub>''k''</sub>,''T''(''h''<sub>''k''</sub>)}<sub>''k''=0…2</sub>&nbsp;= {(4.00,6.128), (2.00,4.352), (1.00,3.908)} is 3.76+0.148''h''<sup>2</sup>, producing the extrapolated value 3.76 at ''h''&nbsp;= 0.
Although the Riemann and Lebesgue integrals are the most important ones, a number of others exist, including but not limited to:
 
* The [[Daniell integral]].
 
* The [[Darboux integral]], a variation of the Riemann integral.
 
* The [[Denjoy integral]] (also known as the [[Henstock-Kurzweil integral]]), an extension of both the Riemann and Lebesgue integrals.
 
* The [[Haar integral]].
 
* The [[Henstock-Kurzweil integral]], an extension of both the Riemann and Lebesgue integrals (also called HK-integral).
 
* The [[Henstock-Kurzweil-Stieltjes integral]] (also called HK-Stieltjes integral).
 
* The [[Lebesgue-Stieltjes integral]] (also called Lebesgue-Radon integral).
 
* The [[Perron integral]], which is equivalent to the restricted [[Denjoy integral]].
 
* The [[Riemann-Stieltjes integral]], an extension of the Riemann integral.
 
   
  +
[[Gaussian quadrature]] often requires noticeably less work for superior accuracy. In this example, it can compute the function values at just two ''x'' positions, ±<sup>2</sup>⁄<sub>√3</sub>, then double each value and sum to get the numerically exact answer. The explanation for this dramatic success lies in error analysis, and a little luck. An ''n-''point Gaussian method is exact for polynomials of degree up to 2''n''−1. The function in this example is a degree 3 polynomial, plus a term that cancels because the chosen endpoints are symmetric around zero. (Cancellation also benefits the Romberg method.)
== Definitions by means of an integral ==
 
Several mathematical functions and constants can be defined by using an integral. The [[natural logarithm]] is usually defined as
 
:<math>\ln x = \int_1^x \! {dt\over t}.</math>
 
The mathematical constant ''e'' may then be defined as the number such that
 
:<math>\ln e =\int_1^e \! {dt\over t} = 1.</math>
 
   
  +
Shifting the range left a little, so the integral is from −2.25 to 1.75, removes the symmetry. Nevertheless, the trapezoid method is rather slow, the polynomial interpolation method of Romberg is acceptable, and the Gaussian method requires the least work — if the number of points is known in advance. As well, rational interpolation can use the same trapezoid evaluations as the Romberg method to greater effect.
== See also ==
 
  +
* [[Lists of integrals]]
 
  +
:{| class="wikitable" style="background-color:white;text-align:center"
* [[Multiple integral]] (integrals for functions of more than one variable)
 
  +
|+ Quadrature method cost comparison
* [[Integral (examples)]]
 
  +
|-
  +
! style="text-align:right" | Method
  +
| '''Trapezoid''' || '''Romberg''' || '''Rational''' || '''Gauss'''
  +
|-
  +
! style="text-align:right" | Points
  +
| 1048577 || 257 || 129 || 36
  +
|-
  +
! style="text-align:right" | Rel. Err.
  +
| −5.3×10<sup>−13</sup> || −6.3×10<sup>−15</sup> || 8.8×10<sup>−15</sup> || 3.1×10<sup>−15</sup>
  +
|-
  +
! style="text-align:right" | Value
  +
| colspan="4" | <math>\textstyle \int_{-2.25}^{1.75} f(x)\,dx = 4.1639019006585897075\ldots</math>
  +
|}
  +
  +
In practice, each method must use extra evaluations to ensure an error bound on an unknown function; this tends to offset some of the advantage of the pure Gaussian method, and motivates the popular [[Gauss–Kronrod quadrature formula]]s. Symmetry can still be exploited by splitting this integral into two ranges, from −2.25 to −1.75 (no symmetry), and from −1.75 to 1.75 (symmetry). More broadly, [[adaptive quadrature]] partitions a range into pieces based on function properties, so that data points are concentrated where they are needed most.
  +
  +
This brief introduction omits higher-dimensional integrals (for example, area and volume calculations), where alternatives such as [[Monte Carlo integration]] have great importance.
  +
  +
A calculus text is no substitute for numerical analysis, but the reverse is also true. Even the best adaptive numerical code sometimes requires a user to help with the more demanding integrals. For example, improper integrals may require a change of variable or methods that can avoid infinite function values; and known properties like symmetry and periodicity may provide critical leverage.
  +
  +
== See also ==
  +
* [[Lists of integrals]] - integrals of the most common functions.
  +
* [[Multiple integral]]
 
* [[Antiderivative]]
 
* [[Antiderivative]]
  +
* [[Numerical integration]]
  +
* [[Integral equation]]
  +
* [[Riemann integral]]
  +
* [[Riemann-Stieltjes integral]]
  +
* [[Henstock–Kurzweil integral]]
  +
* [[Lebesgue integration]]
  +
* [[Darboux integral]]
  +
* [[Riemann sum]]
  +
* [[Product integral]]
  +
  +
  +
==References==
  +
* {{citation | last=Apostol | first=Tom M. | author-link=Tom M. Apostol | title=Calculus, Vol.&nbsp;1: One-Variable Calculus with an Introduction to Linear Algebra | year=1967 | edition=2nd | publisher=[[John Wiley & Sons|Wiley]] | isbn=978-0-471-00005-1}}
  +
* {{citation | last=Bourbaki| first=Nicolas | author-link=Nicolas Bourbaki | title=Integration I | year=2004 | publisher=[[Springer Science+Business Media|Springer Verlag]] | isbn=3-540-41129-1}}. In particular chapters III and IV.
  +
* {{citation | last=Burton | first=David M. | title=The History of Mathematics: An Introduction | edition=6<sup>th</sup> | year=2005<!--November 8--> | publisher=[[McGraw-Hill]] | isbn=978-0-07-305189-5 | page=p.&nbsp;359}}
  +
* {{citation | last=Cajori | first=Florian | author-link=Florian Cajori | title=A History Of Mathematical Notations Volume II | year=1929 | publisher=[[Open Court Publishing Company|Open Court Publishing]] | url=http://www.archive.org/details/historyofmathema027671mbp | isbn=978-0-486-67766-8 | pages=247–252}}
  +
* {{citation | last1=Dahlquist | first1=Germund | author1-link=Germund Dahlquist | last2=Björck | first2=Åke | title=Numerical Methods in Scientific Computing, Volume I | publisher=[[SIAM]] | location=Philadelphia | year=2008 | url=http://www.mai.liu.se/~akbjo/NMbook.html | chapter=Chapter&nbsp;5: Numerical Integration}}
  +
* {{citation | last = Folland | first = Gerald B.| title=Real Analysis: Modern Techniques and Their Applications | edition=1st | publisher=[[John Wiley & Sons]] | year = 1984 | isbn=978-0-471-80958-6 }}
  +
* {{citation | last=Fourier | first=Jean Baptiste Joseph | author-link=Joseph Fourier | title=Théorie analytique de la chaleur | year=1822 | publisher=Chez Firmin Didot, père et fils | url=http://books.google.com/books?id=TDQJAAAAIAAJ | page=&sect;231}}<br /
  +
>Available in translation as {{citation | last=Fourier | first=Joseph | title=The analytical theory of heat | year=1878<!--original 1822--> | publisher=[[Cambridge University Press]] | url=http://www.archive.org/details/analyticaltheory00fourrich | others=Freeman, Alexander (trans.) | pages=pp.&nbsp;200–201}}
  +
* {{citation | editor-last=Heath | editor-first=T. L. | editor-link=T. L. Heath | title = The Works of Archimedes | year = 2002 | publisher = [[Dover Publications|Dover]] | ISBN = 978-0-486-42084-4 | url = http://www.archive.org/details/worksofarchimede029517mbp }}<br />(Originally published by [[Cambridge University Press]], 1897, based on J. L. Heiberg's Greek version.)
  +
* {{citation | last=Hildebrandt | first=T. H. | author-link= | title=Integration in abstract spaces | journal=[[Bulletin of the American Mathematical Society]] | volume=59 | number=2 | year=1953 | pages=111–139 | url=http://projecteuclid.org/euclid.bams/1183517761 | issn=0273-0979}}
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* {{citation | last1=Kahaner | first1=David | last2=Moler | first2=Cleve | author2-link=Cleve Moler | last3=Nash | first3=Stephen | title=Numerical Methods and Software | year=1989 | publisher=[[Prentice Hall]] | chapter=Chapter&nbsp;5: Numerical Quadrature | isbn=978-0-13-627258-8 }}
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* {{citation | last=Leibniz | first=Gottfried Wilhelm | author-link=Gottfried Wilhelm Leibniz | title=Der Briefwechsel von Gottfried Wilhelm Leibniz mit Mathematikern. Erster Band | editor-last=Gerhardt | editor-first=Karl Immanuel | place=Berlin | publisher=Mayer &amp; Müller | year=1899 | url=http://name.umdl.umich.edu/AAX2762.0001.001}}
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<!--
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* ''Der Briefwechsel von Gottfried Wilhelm Leibniz mit Mathematikern. Erster Band. Hrsg. von C. I. Gerhardt. Mit Unterstützung der Königl. Preussischen Akademie der Wissenschaften.''<br /
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>Leibniz, Gottfried Wilhelm, Freiherr von, 1646–1716., Gerhardt, Karl Immanuel, ed. 1816–1899, Berlin: Mayer & Müller, 1899. [http://name.umdl.umich.edu/AAX2762.0001.001]
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-->
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* {{citation | last=Miller | first=Jeff | title=Earliest Uses of Symbols of Calculus | url=http://members.aol.com/jeff570/calculus.html | access-date=2007-06-02}}
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* {{citation | last1=O’Connor | first1=J. J. | last2=Robertson | first2=E. F. | title=A history of the calculus | year=1996 | url=http://www-history.mcs.st-andrews.ac.uk/HistTopics/The_rise_of_calculus.html | access-date=2007-07-09 }}
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* {{citation | last=Rudin | first=Walter | author-link=Walter Rudin | title=Real and Complex Analysis | year=1987 | edition=International | publisher=[[McGraw-Hill]] | chapter=Chapter&nbsp;1: Abstract Integration | isbn=978-0-07-100276-9}}
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* {{citation | last=Saks | first=Stanisław | author-link=Stanisław Saks | title=Theory of the integral | url=http://matwbn.icm.edu.pl/kstresc.php?tom=7&wyd=10&jez= | edition= English translation by L. C. Young. With two additional notes by Stefan Banach. Second revised | publisher= Dover | place=New York | year=1964 }}
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* {{citation | last1=Stoer | first1=Josef | last2=Bulirsch | first2=Roland | year=2002 | title=Introduction to Numerical Analysis | edition=3rd | publisher=[[Springer Science+Business Media|Springer]] | chapter=Chapter&nbsp;3: Topics in Integration | isbn=978-0-387-95452-3 }}.
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* {{citation | author=W3C | year=2006<!--January--> | title=Arabic mathematical notation<!--W3C Interest Group Note 31--> | url=http://www.w3.org/TR/arabic-math/}}
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{{reflist}}
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==External links==
   
== External links ==
 
* [http://www.cut-the-knot.org/Curriculum/Calculus/RiemannSums.shtml Riemann Sums - Function Integration (a Java simulation)] at [[cut-the-knot]]
 
* [http://www.cut-the-knot.org/Curriculum/Calculus/CubicSpline.shtml Function, Derivative and Integral (a Java simulation)] at [[cut-the-knot]]
 
 
* [http://integrals.wolfram.com/ The Integrator] by [[Wolfram Research]]
 
* [http://integrals.wolfram.com/ The Integrator] by [[Wolfram Research]]
* [http://wims.unice.fr/wims/wims.cgi?module=tool/analysis/function.en Function Calculator] from [[WIMS]]
+
* [http://wims.unice.fr/wims/wims.cgi?module=tool/analysis/function.en Function Calculator] from [http://wims.unice.fr WIMS]
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* [http://user.mendelu.cz/marik/maw/index.php?lang=en&form=integral Mathematical Assistant on Web] online calculation of integrals, allows to integrate in small steps (includes also hints for next step which cover techniques like by parts, substitution, partial fractions, application of formulas and others, powered by [[Maxima (software)]])
  +
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===Online books===
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* Keisler, H. Jerome, [http://www.math.wisc.edu/~keisler/calc.html Elementary Calculus: An Approach Using Infinitesimals], University of Wisconsin
  +
* Stroyan, K.D., [http://www.math.uiowa.edu/~stroyan/InfsmlCalculus/InfsmlCalc.htm A Brief Introduction to Infinitesimal Calculus], University of Iowa
  +
* Mauch, Sean, [http://www.its.caltech.edu/~sean/book/unabridged.html ''Sean's Applied Math Book''], CIT, an online textbook that includes a complete introduction to calculus
  +
* Crowell, Benjamin, [http://www.lightandmatter.com/calc/ ''Calculus''], Fullerton College, an online textbook
  +
* Garrett, Paul, [http://www.math.umn.edu/~garrett/calculus/ Notes on First-Year Calculus]
  +
* Hussain, Faraz, [http://www.understandingcalculus.com Understanding Calculus], an online textbook
  +
* Kowalk, W.P., [http://einstein.informatik.uni-oldenburg.de/20910.html ''Integration Theory''], University of Oldenburg. A new concept to an old problem. Online textbook
  +
* Sloughter, Dan, [http://math.furman.edu/~dcs/book Difference Equations to Differential Equations], an introduction to calculus
  +
* [http://numericalmethods.eng.usf.edu/topics/integration.html Numerical Methods of Integration] at ''Holistic Numerical Methods Institute''
 
* P.S. Wang, [http://www.lcs.mit.edu/publications/specpub.php?id=660 Evaluation of Definite Integrals by Symbolic Manipulation] (1972) - a cookbook of definite integral techniques
 
* P.S. Wang, [http://www.lcs.mit.edu/publications/specpub.php?id=660 Evaluation of Definite Integrals by Symbolic Manipulation] (1972) - a cookbook of definite integral techniques
* [http://en.wikibooks.org/wiki/Calculus Wikibook of Calculus]
 
   
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File:Integral example.png

A definite integral of a function can be represented as the signed area of the region bounded by its graph.

Integration is an important concept in mathematics, specifically in the field of calculus and, more broadly, mathematical analysis. Given a function ƒ of a real variable x and an interval [ab] of the real line, the integral

is defined informally to be the net signed area of the region in the xy-plane bounded by the graph of ƒ, the x-axis, and the vertical lines x = a and x = b.

The term "integral" may also refer to the notion of antiderivative, a function F whose derivative is the given function ƒ. In this case it is called an indefinite integral, while the integrals discussed in this article are termed definite integrals. Some authors maintain a distinction between antiderivatives and indefinite integrals.

The principles of integration were formulated independently by Isaac Newton and Gottfried Leibniz in the late seventeenth century. Through the fundamental theorem of calculus, which they independently developed, integration is connected with differentiation: if ƒ is a continuous real-valued function defined on a closed interval [ab], then, once an antiderivative F of ƒ is known, the definite integral of ƒ over that interval is given by

Integrals and derivatives became the basic tools of calculus, with numerous applications in science and engineering. A rigorous mathematical definition of the integral was given by Bernhard Riemann. It is based on a limiting procedure which approximates the area of a curvilinear region by breaking the region into thin vertical slabs. Beginning in the nineteenth century, more sophisticated notions of integral began to appear, where the type of the function as well as the domain over which the integration is performed has been generalised. A line integral is defined for functions of two or three variables, and the interval of integration [ab] is replaced by a certain curve connecting two points on the plane or in the space. In a surface integral, the curve is replaced by a piece of a surface in the three-dimensional space. Integrals of differential forms play a fundamental role in modern differential geometry. These generalizations of integral first arose from the needs of physics, and they play an important role in the formulation of many physical laws, notably those of electrodynamics. Modern concepts of integration are based on the abstract mathematical theory known as Lebesgue integration, developed by Henri Lebesgue.

History

See also: History of calculus

Pre-calculus integration

Integration can be traced as far back as ancient Egypt, circa 1800 BC, with the Moscow Mathematical Papyrus demonstrating knowledge of a formula for the volume of a pyramidal frustum. The first documented systematic technique capable of determining integrals is the method of exhaustion of Eudoxus (circa 370 BC), which sought to find areas and volumes by breaking them up into an infinite number of shapes for which the area or volume was known. This method was further developed and employed by Archimedes and used to calculate areas for parabolas and an approximation to the area of a circle. Similar methods were independently developed in China around the 3rd Century AD by Liu Hui, who used it to find the area of the circle. This method was later used in the 5th century by Chinese father and son mathematicians Zu Chongzhi and Zu Geng to find the volume of a sphere.[1] That same century, the Indian mathematician Aryabhata used a similar method in order to find the volume of a cube.[2]

The next major step in integral calculus came in the 11th century, when the Iraqi mathematician, Ibn al-Haytham (known as Alhazen in Europe), devised what is now known as "Alhazen's problem", which leads to an equation of the fourth degree, in his Book of Optics. While solving this problem, he performed an integration in order to find the volume of a paraboloid. Using mathematical induction, he was able to generalize his result for the integrals of polynomials up to the fourth degree. He thus came close to finding a general formula for the integrals of polynomials, but he was not concerned with any polynomials higher than the fourth degree.[3] Some ideas of integral calculus are also found in the Siddhanta Shiromani, a 12th century astronomy text by Indian mathematician Bhāskara II.

The next significant advances in integral calculus did not begin to appear until the 16th century. At this time the work of Cavalieri with his method of indivisibles, and work by Fermat, began to lay the foundations of modern calculus. Further steps were made in the early 17th century by Barrow and Torricelli, who provided the first hints of a connection between integration and differentiation.

Newton and Leibniz

The major advance in integration came in the 17th century with the independent discovery of the fundamental theorem of calculus by Newton and Leibniz. The theorem demonstrates a connection between integration and differentiation. This connection, combined with the comparative ease of differentiation, can be exploited to calculate integrals. In particular, the fundamental theorem of calculus allows one to solve a much broader class of problems. Equal in importance is the comprehensive mathematical framework that both Newton and Leibniz developed. Given the name infinitesimal calculus, it allowed for precise analysis of functions within continuous domains. This framework eventually became modern calculus, whose notation for integrals is drawn directly from the work of Leibniz.

Formalizing integrals

While Newton and Leibniz provided a systematic approach to integration, their work lacked a degree of rigor. Bishop Berkeley memorably attacked infinitesimals as "the ghosts of departed quantities". Calculus acquired a firmer footing with the development of limits and was given a suitable foundation by Cauchy in the first half of the 19th century. Integration was first rigorously formalized, using limits, by Riemann. Although all bounded piecewise continuous functions are Riemann integrable on a bounded interval, subsequently more general functions were considered, to which Riemann's definition does not apply, and Lebesgue formulated a different definition of integral, founded in measure theory (a subfield of real analysis). Other definitions of integral, extending Riemann's and Lebesgue's approaches, were proposed.

Notation

Isaac Newton used a small vertical bar above a variable to indicate integration, or placed the variable inside a box. The vertical bar was easily confused with or , which Newton used to indicate differentiation, and the box notation was difficult for printers to reproduce, so these notations were not widely adopted.

The modern notation for the indefinite integral was introduced by Gottfried Leibniz in 1675 (Burton 1988, p. 359; Leibniz 1899, p. 154). He adapted the integral symbol, "", from an elongated letter "s", standing for summa (Latin for "sum" or "total"). The modern notation for the definite integral, with limits above and below the integral sign, was first used by Joseph Fourier in Mémoires of the French Academy around 1819–20, reprinted in his book of 1822 (Cajori 1929, pp. 249–250; Fourier 1822, §231). In so-called modern Arabic mathematical notation, which aims at pre-university levels of education in the Arab world and is written from right to left, an inverted integral symbol File:ArabicIntegralSign.svg is used (W3C 2006).

Terminology and notation

If a function has an integral, it is said to be integrable. The function for which the integral is calculated is called the integrand. The region over which a function is being integrated is called the domain of integration. If the integral does not have a domain of integration, it is considered indefinite (one with a domain is considered definite). In general, the integrand may be a function of more than one variable, and the domain of integration may be an area, volume, a higher dimensional region, or even an abstract space that does not have a geometric structure in any usual sense.

The simplest case, the integral of a real-valued function f of one real variable x on the interval [a, b], is denoted by

The ∫ sign, an elongated "s", represents integration; a and b are the lower limit and upper limit of integration, defining the domain of integration; f is the integrand, to be evaluated as x varies over the interval [a,b]; and dx is the variable of integration. In correct mathematical typography, the dx is separated from the integrand by a space (as shown). Some authors use an upright d (that is, instead of dx).

The variable of integration dx has different interpretations depending on the theory being used. For example, it can be seen as strictly a notation indicating that x is a dummy variable of integration, as a reflection of the weights in the Riemann sum, a measure (in Lebesgue integration and its extensions), an infinitesimal (in non-standard analysis) or as an independent mathematical quantity: a differential form. More complicated cases may vary the notation slightly.

Introduction

Integrals appear in many practical situations. Consider a swimming pool. If it is rectangular, then from its length, width, and depth we can easily determine the volume of water it can contain (to fill it), the area of its surface (to cover it), and the length of its edge (to rope it). But if it is oval with a rounded bottom, all of these quantities call for integrals. Practical approximations may suffice for such trivial examples, but precision engineering (of any discipline) requires exact and rigorous values for these elements.

File:Integral approximations.svg

Approximations to integral of √x from 0 to 1, with  5 right samples (above) and  12 left samples (below)

To start off, consider the curve y = f(x) between x = 0 and x = 1, with f(x) = √x. We ask:

What is the area under the function f, in the interval from 0 to 1?

and call this (yet unknown) area the integral of f. The notation for this integral will be

As a first approximation, look at the unit square given by the sides x = 0 to x = 1 and y = f(0) = 0 and y = f(1) = 1. Its area is exactly 1. As it is, the true value of the integral must be somewhat less. Decreasing the width of the approximation rectangles shall give a better result; so cross the interval in five steps, using the approximation points 0, 15, 25, and so on to 1. Fit a box for each step using the right end height of each curve piece, thus √15, √25, and so on to √1 = 1. Summing the areas of these rectangles, we get a better approximation for the sought integral, namely

Notice that we are taking a sum of finitely many function values of f, multiplied with the differences of two subsequent approximation points. We can easily see that the approximation is still too large. Using more steps produces a closer approximation, but will never be exact: replacing the 5 subintervals by twelve as depicted, we will get an approximate value for the area of 0.6203, which is too small. The key idea is the transition from adding finitely many differences of approximation points multiplied by their respective function values to using infinitely fine, or infinitesimal steps.

As for the actual calculation of integrals, the fundamental theorem of calculus, due to Newton and Leibniz, is the fundamental link between the operations of differentiating and integrating. Applied to the square root curve, f(x) = x1/2, it says to look at the antiderivative F(x) = 23x3/2, and simply take F(1) − F(0), where 0 and 1 are the boundaries of the interval [0,1]. (This is a case of a general rule, that for f(x) = xq, with q ≠ −1, the related function, the so-called antiderivative is F(x) = (xq+1)/(q + 1).) So the exact value of the area under the curve is computed formally as

The notation

conceives the integral as a weighted sum, denoted by the elongated "s", of function values, f(x), multiplied by infinitesimal step widths, the so-called differentials, denoted by dx. The multiplication sign is usually omitted.

Historically, after the failure of early efforts to rigorously interpret infinitesimals, Riemann formally defined integrals as a limit of weighted sums, so that the dx suggested the limit of a difference (namely, the interval width). Shortcomings of Riemann's dependence on intervals and continuity motivated newer definitions, especially the Lebesgue integral, which is founded on an ability to extend the idea of "measure" in much more flexible ways. Thus the notation

refers to a weighted sum in which the function values are partitioned, with μ measuring the weight to be assigned to each value. Here A denotes the region of integration.

Differential geometry, with its "calculus on manifolds", gives the familiar notation yet another interpretation. Now f(x) and dx become a differential form, ω = f(x) dx, a new differential operator d, known as the exterior derivative appears, and the fundamental theorem becomes the more general Stokes' theorem,

from which Green's theorem, the divergence theorem, and the fundamental theorem of calculus follow.

More recently, infinitesimals have reappeared with rigor, through modern innovations such as non-standard analysis. Not only do these methods vindicate the intuitions of the pioneers, they also lead to new mathematics.

Although there are differences between these conceptions of integral, there is considerable overlap. Thus the area of the surface of the oval swimming pool can be handled as a geometric ellipse, as a sum of infinitesimals, as a Riemann integral, as a Lebesgue integral, or as a manifold with a differential form. The calculated result will be the same for all.

Formal definitions

There are many ways of formally defining an integral, not all of which are equivalent. The differences exist mostly to deal with differing special cases which may not be integrable under other definitions, but also occasionally for pedagogical reasons. The most commonly used definitions of integral are Riemann integrals and Lebesgue integrals.

Riemann integral

Main article: Riemann integral
File:Integral Riemann sum.png

Integral approached as Riemann sum based on tagged partition, with irregular sampling positions and widths (max in red). True value is 3.76; estimate is 3.648.

The Riemann integral is defined in terms of Riemann sums of functions with respect to tagged partitions of an interval. Let [a,b] be a closed interval of the real line; then a tagged partition of [a,b] is a finite sequence

File:Riemann sum convergence.png

Riemann sums converging as intervals halve, whether sampled at  right,  minimum,  maximum, or  left.

This partitions the interval [a,b] into i sub-intervals [xi−1, xi], each of which is "tagged" with a distinguished point ti ∈ [xi−1, xi]. Let Δi = xixi−1 be the width of sub-interval i; then the mesh of such a tagged partition is the width of the largest sub-interval formed by the partition, maxi=1…n Δi. A Riemann sum of a function f with respect to such a tagged partition is defined as

thus each term of the sum is the area of a rectangle with height equal to the function value at the distinguished point of the given sub-interval, and width the same as the sub-interval width. The Riemann integral of a function f over the interval [a,b] is equal to S if:

For all ε > 0 there exists δ > 0 such that, for any tagged partition [a,b] with mesh less than δ, we have

When the chosen tags give the maximum (respectively, minimum) value of each interval, the Riemann sum becomes an upper (respectively, lower) Darboux sum, suggesting the close connection between the Riemann integral and the Darboux integral.

Lebesgue integral

Main article: Lebesgue integration

The Riemann integral is not defined for a wide range of functions and situations of importance in applications (and of interest in theory). For example, the Riemann integral can easily integrate density to find the mass of a steel beam, but cannot accommodate a steel ball resting on it. This motivates other definitions, under which a broader assortment of functions is integrable (Rudin 1987). The Lebesgue integral, in particular, achieves great flexibility by directing attention to the weights in the weighted sum.

The definition of the Lebesgue integral thus begins with a measure, μ. In the simplest case, the Lebesgue measure μ(A) of an interval A = [a,b] is its width, ba, so that the Lebesgue integral agrees with the (proper) Riemann integral when both exist. In more complicated cases, the sets being measured can be highly fragmented, with no continuity and no resemblance to intervals.

To exploit this flexibility, Lebesgue integrals reverse the approach to the weighted sum. As Folland (1984, p. 56) puts it, "To compute the Riemann integral of f, one partitions the domain [a,b] into subintervals", while in the Lebesgue integral, "one is in effect partitioning the range of f".

One common approach first defines the integral of the indicator function of a measurable set A by:

.

This extends by linearity to a measurable simple function s, which attains only a finite number, n, of distinct non-negative values:

(where the image of Ai under the simple function s is the constant value ai). Thus if E is a measurable set one defines

Then for any non-negative measurable function f one defines

that is, the integral of f is set to be the supremum of all the integrals of simple functions that are less than or equal to f. A general measurable function f, is split into its positive and negative values by defining

Finally, f is Lebesgue integrable if

and then the integral is defined by

When the measure space on which the functions are defined is also a locally compact topological space (as is the case with the real numbers R), measures compatible with the topology in a suitable sense (Radon measures, of which the Lebesgue measure is an example) and integral with respect to them can be defined differently, starting from the integrals of continuous functions with compact support. More precisely, the compactly supported functions form a vector space that carries a natural topology, and a (Radon) measure can be defined as any continuous linear functional on this space; the value of a measure at a compactly supported function is then also by definition the integral of the function. One then proceeds to expand the measure (the integral) to more general functions by continuity, and defines the measure of a set as the integral of its indicator function. This is the approach taken by Bourbaki (2004) and a certain number of other authors. For details see Radon measures.

Other integrals

Although the Riemann and Lebesgue integrals are the most important definitions of the integral, a number of others exist, including:

  • The Riemann-Stieltjes integral, an extension of the Riemann integral.
  • The Lebesgue-Stieltjes integral, further developed by Johann Radon, which generalizes the Riemann-Stieltjes and Lebesgue integrals.
  • The Daniell integral, which subsumes the Lebesgue integral and Lebesgue-Stieltjes integral without the dependence on measures.
  • The Henstock-Kurzweil integral, variously defined by Arnaud Denjoy, Oskar Perron, and (most elegantly, as the gauge integral) Jaroslav Kurzweil, and developed by Ralph Henstock. Robert Bartle[4] gave perhaps the most compelling introduction to this integral in a paper for which he earned a writing award from the Mathematical Association of America.
  • The Itō integral and Stratonovich integral, which define integration with respect to stochastic processes such as Brownian motion.

Properties of integration

Linearity

  • The collection of Riemann integrable functions on a closed interval [a, b] forms a vector space under the operations of pointwise addition and multiplication by a scalar, and the operation of integration
is a linear functional on this vector space. Thus, firstly, the collection of integrable functions is closed under taking linear combinations; and, secondly, the integral of a linear combination is the linear combination of the integrals,
  • Similarly, the set of real-valued Lebesgue integrable functions on a given measure space E with measure μ is closed under taking linear combinations and hence form a vector space, and the Lebesgue integral
is a linear functional on this vector space, so that
  • More generally, consider the vector space of all measurable functions on a measure space (E,μ), taking values in a locally compact complete topological vector space V over a locally compact topological field K, f : EV. Then one may define an abstract integration map assigning to each function f an element of V or the symbol ,
that is compatible with linear combinations. In this situation the linearity holds for the subspace of functions whose integral is an element of V (i.e. "finite"). The most important special cases arise when K is R, C, or a finite extension of the field Qp of p-adic numbers, and V is a finite-dimensional vector space over K, and when K=C and V is a complex Hilbert space.

Linearity, together with some natural continuity properties and normalisation for a certain class of "simple" functions, may be used to give an alternative definition of the integral. This is the approach of Daniell for the case of real-valued functions on a set X, generalized by Nicolas Bourbaki to functions with values in a locally compact topological vector space. See (Hildebrandt 1953) for an axiomatic characterisation of the integral.

Inequalities for integrals

A number of general inequalities hold for Riemann-integrable functions defined on a closed and bounded interval [a, b] and can be generalized to other notions of integral (Lebesgue and Daniell).

  • Upper and lower bounds. An integrable function f on [a, b], is necessarily bounded on that interval. Thus there are real numbers m and M so that mf (x) ≤ M for all x in [a, b]. Since the lower and upper sums of f over [a, b] are therefore bounded by, respectively, m(ba) and M(ba), it follows that
  • Inequalities between functions. If f(x) ≤ g(x) for each x in [a, b] then each of the upper and lower sums of f is bounded above by the upper and lower sums, respectively, of g. Thus
This is a generalization of the above inequalities, as M(ba) is the integral of the constant function with value M over [a, b].
  • Subintervals. If [c, d] is a subinterval of [a, b] and f(x) is non-negative for all x, then
  • Products and absolute values of functions. If f and g are two functions then we may consider their pointwise products and powers, and absolute values:
If f is Riemann-integrable on [a, b] then the same is true for |f|, and
Moreover, if f and g are both Riemann-integrable then f 2, g 2, and fg are also Riemann-integrable, and
This inequality, known as the Cauchy–Schwarz inequality, plays a prominent role in Hilbert space theory, where the left hand side is interpreted as the inner product of two square-integrable functions f and g on the interval [a, b].
  • Hölder's inequality. Suppose that p and q are two real numbers, 1 ≤ p, q ≤ ∞ with 1/p + 1/q = 1, and f and g are two Riemann-integrable functions. Then the functions |f|p and |g|q are also integrable and the following Hölder's inequality holds:
For p = q = 2, Hölder's inequality becomes the Cauchy–Schwarz inequality.
  • Minkowski inequality. Suppose that p ≥ 1 is a real number and f and g are Riemann-integrable functions. Then |f|p, |g|p and |f + g|p are also Riemann integrable and the following Minkowski inequality holds:
An analogue of this inequality for Lebesgue integral is used in construction of Lp spaces.

Conventions

In this section f is a real-valued Riemann-integrable function. The integral

over an interval [a, b] is defined if a < b. This means that the upper and lower sums of the function f are evaluated on a partition a = x0x1 ≤ . . . ≤ xn = b whose values xi are increasing. Geometrically, this signifies that integration takes place "left to right", evaluating f within intervals [xi , xi +1] where an interval with a higher index lies to the right of one with a lower index. The values a and b, the end-points of the interval, are called the limits of integration of f. Integrals can also be defined if a > b:

  • Reversing limits of integration. If a > b then define

This, with a = b, implies:

  • Integrals over intervals of length zero. If a is a real number then

The first convention is necessary in consideration of taking integrals over subintervals of [a, b]; the second says that an integral taken over a degenerate interval, or a point, should be zero. One reason for the first convention is that the integrability of f on an interval [a, b] implies that f is integrable on any subinterval [c, d], but in particular integrals have the property that:

  • Additivity of integration on intervals. If c is any element of [a, b], then

With the first convention the resulting relation

is then well-defined for any cyclic permutation of a, b, and c.

Instead of viewing the above as conventions, one can also adopt the point of view that integration is performed on oriented manifolds only. If M is such an oriented m-dimensional manifold, and M' is the same manifold with opposed orientation and ω is an m-form, then one has (see below for integration of differential forms):

Fundamental theorem of calculus

Main article: Fundamental theorem of calculus

The fundamental theorem of calculus is the statement that differentiation and integration are inverse operations: if a continuous function is first integrated and then differentiated, the original function is retrieved. An important consequence, sometimes called the second fundamental theorem of calculus, allows one to compute integrals by using an antiderivative of the function to be integrated.

Statements of theorems

then F is continuous on [a, b]. If f is continuous at x in [a, b], then F is differentiable at x, and F ′(x) = f(x).
  • Second fundamental theorem of calculus. Let f be a real-valued integrable function defined on a closed interval [a, b]. If F is a function such that F ′(x) = f(x) for all x in [a, b] (that is, F is an antiderivative of f), then
  • Corollary. If f is a continuous function on [a, b], then f is integrable on [a, b], and F, defined by
is an anti-derivative of f on [a, b]. Moreover,

Extensions

Improper integrals

Main article: Improper integral
File:Improper integral.svg

The improper integral

has unbounded intervals for both domain and range.

A "proper" Riemann integral assumes the integrand is defined and finite on a closed and bounded interval, bracketed by the limits of integration. An improper integral occurs when one or more of these conditions is not satisfied. In some cases such integrals may be defined by considering the limit of a sequence of proper Riemann integrals on progressively larger intervals.

If the interval is unbounded, for instance at its upper end, then the improper integral is the limit as that endpoint goes to infinity.

If the integrand is only defined or finite on a half-open interval, for instance (a,b], then again a limit may provide a finite result.

That is, the improper integral is the limit of proper integrals as one endpoint of the interval of integration approaches either a specified real number, or ∞, or −∞. In more complicated cases, limits are required at both endpoints, or at interior points.

Consider, for example, the function integrated from 0 to ∞ (shown right). At the lower bound, as x goes to 0 the function goes to ∞, and the upper bound is itself ∞, though the function goes to 0. Thus this is a doubly improper integral. Integrated, say, from 1 to 3, an ordinary Riemann sum suffices to produce a result of . To integrate from 1 to ∞, a Riemann sum is not possible. However, any finite upper bound, say t (with t > 1), gives a well-defined result, . This has a finite limit as t goes to infinity, namely . Similarly, the integral from 13 to 1 allows a Riemann sum as well, coincidentally again producing . Replacing 13 by an arbitrary positive value s (with s < 1) is equally safe, giving . This, too, has a finite limit as s goes to zero, namely . Combining the limits of the two fragments, the result of this improper integral is

This process is not guaranteed success; a limit may fail to exist, or may be unbounded. For example, over the bounded interval 0 to 1 the integral of does not converge; and over the unbounded interval 1 to ∞ the integral of does not converge.

It may also happen that an integrand is unbounded at an interior point, in which case the integral must be split at that point, and the limit integrals on both sides must exist and must be bounded. Thus

But the similar integral

cannot be assigned a value in this way, as the integrals above and below zero do not independently converge. (However, see Cauchy principal value.)

Multiple integration

Main article: Multiple integral
File:Volume under surface.png

Double integral as volume under a surface.

Integrals can be taken over regions other than intervals. In general, an integral over a set E of a function f is written:

Here x need not be a real number, but can be another suitable quantity, for instance, a vector in R3. Fubini's theorem shows that such integrals can be rewritten as an iterated integral. In other words, the integral can be calculated by integrating one coordinate at a time.

Just as the definite integral of a positive function of one variable represents the area of the region between the graph of the function and the x-axis, the double integral of a positive function of two variables represents the volume of the region between the surface defined by the function and the plane which contains its domain. (The same volume can be obtained via the triple integral — the integral of a function in three variables — of the constant function f(x, y, z) = 1 over the above-mentioned region between the surface and the plane.) If the number of variables is higher, then the integral represents a hypervolume, a volume of a solid of more than three dimensions that cannot be graphed.

For example, the volume of the cuboid of sides 4 × 6 × 5 may be obtained in two ways:

  • By the double integral
of the function f(x, y) = 5 calculated in the region D in the xy-plane which is the base of the cuboid. For example, if a rectangular base of such a cuboid is given via the xy inequalities 2 ≤ x ≤ 7, 4 ≤ y ≤ 9, our above double integral now reads
From here, integration is conducted with respect to either x or y first; in this example, integration is first done with respect to x as the interval corresponding to x is the inner integral. Once the first integration is completed via the method or otherwise, the result is again integrated with respect to the other variable. The result will equate to the volume under the surface.
  • By the triple integral
of the constant function 1 calculated on the cuboid itself.

Line integrals

Main article: Line integral
File:Line-Integral.gif

A line integral sums together elements along a curve.

The concept of an integral can be extended to more general domains of integration, such as curved lines and surfaces. Such integrals are known as line integrals and surface integrals respectively. These have important applications in physics, as when dealing with vector fields.

A line integral (sometimes called a path integral) is an integral where the function to be integrated is evaluated along a curve. Various different line integrals are in use. In the case of a closed curve it is also called a contour integral.

The function to be integrated may be a scalar field or a vector field. The value of the line integral is the sum of values of the field at all points on the curve, weighted by some scalar function on the curve (commonly arc length or, for a vector field, the scalar product of the vector field with a differential vector in the curve). This weighting distinguishes the line integral from simpler integrals defined on intervals. Many simple formulas in physics have natural continuous analogs in terms of line integrals; for example, the fact that work is equal to force multiplied by distance may be expressed (in terms of vector quantities) as:

;

which is paralleled by the line integral:

;

which sums up vector components along a continuous path, and thus finds the work done on an object moving through a field, such as an electric or gravitational field

Surface integrals

Main article: Surface integral
File:Surface integral illustration.png

The definition of surface integral relies on splitting the surface into small surface elements.

A surface integral is a definite integral taken over a surface (which may be a curved set in space); it can be thought of as the double integral analog of the line integral. The function to be integrated may be a scalar field or a vector field. The value of the surface integral is the sum of the field at all points on the surface. This can be achieved by splitting the surface into surface elements, which provide the partitioning for Riemann sums.

For an example of applications of surface integrals, consider a vector field v on a surface S; that is, for each point x in S, v(x) is a vector. Imagine that we have a fluid flowing through S, such that v(x) determines the velocity of the fluid at x. The flux is defined as the quantity of fluid flowing through S in unit amount of time. To find the flux, we need to take the dot product of v with the unit surface normal to S at each point, which will give us a scalar field, which we integrate over the surface:

The fluid flux in this example may be from a physical fluid such as water or air, or from electrical or magnetic flux. Thus surface integrals have applications in physics, particularly with the classical theory of electromagnetism.

Integrals of differential forms

Main article: differential form

A differential form is a mathematical concept in the fields of multivariable calculus, differential topology and tensors. The modern notation for the differential form, as well as the idea of the differential forms as being the wedge products of exterior derivatives forming an exterior algebra, was introduced by Élie Cartan.

We initially work in an open set in Rn. A 0-form is defined to be a smooth function f. When we integrate a function f over an m-dimensional subspace S of Rn, we write it as

(The superscripts are indices, not exponents.) We can consider dx1 through dxn to be formal objects themselves, rather than tags appended to make integrals look like Riemann sums. Alternatively, we can view them as covectors, and thus a measure of "density" (hence integrable in a general sense). We call the dx1, …,dxn basic 1-forms.

We define the wedge product, "∧", a bilinear "multiplication" operator on these elements, with the alternating property that

for all indices a. Note that alternation along with linearity implies dxbdxa = −dxadxb. This also ensures that the result of the wedge product has an orientation.

We define the set of all these products to be basic 2-forms, and similarly we define the set of products of the form dxadxbdxc to be basic 3-forms. A general k-form is then a weighted sum of basic k-forms, where the weights are the smooth functions f. Together these form a vector space with basic k-forms as the basis vectors, and 0-forms (smooth functions) as the field of scalars. The wedge product then extends to k-forms in the natural way. Over Rn at most n covectors can be linearly independent, thus a k-form with k > n will always be zero, by the alternating property.

In addition to the wedge product, there is also the exterior derivative operator d. This operator maps k-forms to (k+1)-forms. For a k-form ω = f dxa over Rn, we define the action of d by:

with extension to general k-forms occurring linearly.

This more general approach allows for a more natural coordinate-free approach to integration on manifolds. It also allows for a natural generalisation of the fundamental theorem of calculus, called Stokes' theorem, which we may state as

where ω is a general k-form, and ∂Ω denotes the boundary of the region Ω. Thus in the case that ω is a 0-form and Ω is a closed interval of the real line, this reduces to the fundamental theorem of calculus. In the case that ω is a 1-form and Ω is a 2-dimensional region in the plane, the theorem reduces to Green's theorem. Similarly, using 2-forms, and 3-forms and Hodge duality, we can arrive at Stokes' theorem and the divergence theorem. In this way we can see that differential forms provide a powerful unifying view of integration.

Methods

Computing integrals

The most basic technique for computing definite integrals of one real variable is based on the fundamental theorem of calculus. It proceeds like this:

  1. Let f(x) be the function of x to be integrated over a given interval [a, b].
  2. Find an antiderivative of f, that is, a function F such that F' = f on the interval.
  3. Then, by the fundamental theorem of calculus, provided the integrand and integral have no singularities on the path of integration,

Note that the integral is not actually the antiderivative, but the fundamental theorem allows us to use antiderivatives to evaluate definite integrals.

The difficult step is often finding an antiderivative of f. It is rarely possible to glance at a function and write down its antiderivative. More often, it is necessary to use one of the many techniques that have been developed to evaluate integrals. Most of these techniques rewrite one integral as a different one which is hopefully more tractable. Techniques include:

  • Integration by substitution
  • Integration by parts
  • Changing the order of integration
  • Integration by trigonometric substitution
  • Integration by partial fractions
  • Integration by reduction formulae
  • Integration using parametric derivatives
  • Integrating trigonometric products as complex exponentials
  • Differentiation under the integral sign
  • Contour Integration

Even if these techniques fail, it may still be possible to evaluate a given integral. Many nonelementary integrals can be expanded in a Taylor series and integrated term by term. Occasionally, the resulting infinite series can be summed analytically. The method of convolution using Meijer G-functions can also be used, assuming that the integrand can be written as a product of Meijer G-functions. There are also many less common ways of calculating definite integrals; for instance, Parseval's identity can be used to transform an integral over a rectangular region into an infinite sum. Occasionally, an integral can be evaluated by a trick; for an example of this, see Gaussian integral.

Computations of volumes of solids of revolution can usually be done with disk integration or shell integration.

Specific results which have been worked out by various techniques are collected in the list of integrals.

Symbolic algorithms

Main article: Symbolic integration

Many problems in mathematics, physics, and engineering involve integration where an explicit formula for the integral is desired. Extensive tables of integrals have been compiled and published over the years for this purpose. With the spread of computers, many professionals, educators, and students have turned to computer algebra systems that are specifically designed to perform difficult or tedious tasks, including integration. Symbolic integration presents a special challenge in the development of such systems.

A major mathematical difficulty in symbolic integration is that in many cases, a closed formula for the antiderivative of a rather simple-looking function does not exist. For instance, it is known that the antiderivatives of the functions exp ( x2), xx and sin x /x cannot be expressed in the closed form involving only rational and exponential functions, logarithm, trigonometric and inverse trigonometric functions, and the operations of multiplication and composition; in other words, none of the three given functions is integrable in elementary functions. Differential Galois theory provides general criteria that allow one to determine whether the antiderivative of an elementary function is elementary. Unfortunately, it turns out that functions with closed expressions of antiderivatives are the exception rather than the rule. Consequently, computerized algebra systems have no hope of being able to find an antiderivative for a randomly constructed elementary function. On the positive side, if the 'building blocks' for antiderivatives are fixed in advance, it may be still be possible to decide whether the antiderivative of a given function can be expressed using these blocks and operations of multiplication and composition, and to find the symbolic answer whenever it exists. The Risch algorithm, implemented in Mathematica and other computer algebra systems, does just that for functions and antiderivatives built from rational functions, radicals, logarithm, and exponential functions.

Some special integrands occur often enough to warrant special study. In particular, it may be useful to have, in the set of antiderivatives, the special functions of physics (like the Legendre functions, the hypergeometric function, the Gamma function and so on). Extending the Risch-Norman algorithm so that it includes these functions is possible but challenging.

Most humans are not able to integrate such general formulae, so in a sense computers are more skilled at integrating highly complicated formulae. Very complex formulae are unlikely to have closed-form antiderivatives, so how much of an advantage this presents is a philosophical question that is open for debate.

Numerical quadrature

Main article: numerical integration

The integrals encountered in a basic calculus course are deliberately chosen for simplicity; those found in real applications are not always so accommodating. Some integrals cannot be found exactly, some require special functions which themselves are a challenge to compute, and others are so complex that finding the exact answer is too slow. This motivates the study and application of numerical methods for approximating integrals, which today use floating point arithmetic on digital electronic computers. Many of the ideas arose much earlier, for hand calculations; but the speed of general-purpose computers like the ENIAC created a need for improvements.

The goals of numerical integration are accuracy, reliability, efficiency, and generality. Sophisticated methods can vastly outperform a naive method by all four measures (Dahlquist & Björck 2008; Kahaner, Moler & Nash 1989; Stoer & Bulirsch 2002). Consider, for example, the integral

which has the exact answer 9425 = 3.76. (In ordinary practice the answer is not known in advance, so an important task — not explored here — is to decide when an approximation is good enough.) A “calculus book” approach divides the integration range into, say, 16 equal pieces, and computes function values.

Spaced function values
x −2.00 −1.50 −1.00 −0.50  0.00  0.50  1.00  1.50  2.00
f(x)  2.22800  2.45663  2.67200  2.32475  0.64400 −0.92575 −0.94000 −0.16963  0.83600
x   −1.75 −1.25 −0.75 −0.25  0.25  0.75  1.25  1.75
f(x)  2.33041  2.58562  2.62934  1.64019 −0.32444 −1.09159 −0.60387  0.31734
File:Numerical quadrature 4up.png

Numerical quadrature methods:  Rectangle,  Trapezoid,  Romberg,  Gauss

Using the left end of each piece, the rectangle method sums 16 function values and multiplies by the step width, h, here 0.25, to get an approximate value of 3.94325 for the integral. The accuracy is not impressive, but calculus formally uses pieces of infinitesimal width, so initially this may seem little cause for concern. Indeed, repeatedly doubling the number of steps eventually produces an approximation of 3.76001. However 218 pieces are required, a great computational expense for so little accuracy; and a reach for greater accuracy can force steps so small that arithmetic precision becomes an obstacle.

A better approach replaces the horizontal tops of the rectangles with slanted tops touching the function at the ends of each piece. This trapezium rule is almost as easy to calculate; it sums all 17 function values, but weights the first and last by one half, and again multiplies by the step width. This immediately improves the approximation to 3.76925, which is noticeably more accurate. Furthermore, only 210 pieces are needed to achieve 3.76000, substantially less computation than the rectangle method for comparable accuracy.

Romberg's method builds on the trapezoid method to great effect. First, the step lengths are halved incrementally, giving trapezoid approximations denoted by T(h0), T(h1), and so on, where hk+1 is half of hk. For each new step size, only half the new function values need to be computed; the others carry over from the previous size (as shown in the table above). But the really powerful idea is to interpolate a polynomial through the approximations, and extrapolate to T(0). With this method a numerically exact answer here requires only four pieces (five function values)! The Lagrange polynomial interpolating {hk,T(hk)}k=0…2 = {(4.00,6.128), (2.00,4.352), (1.00,3.908)} is 3.76+0.148h2, producing the extrapolated value 3.76 at h = 0.

Gaussian quadrature often requires noticeably less work for superior accuracy. In this example, it can compute the function values at just two x positions, ±2√3, then double each value and sum to get the numerically exact answer. The explanation for this dramatic success lies in error analysis, and a little luck. An n-point Gaussian method is exact for polynomials of degree up to 2n−1. The function in this example is a degree 3 polynomial, plus a term that cancels because the chosen endpoints are symmetric around zero. (Cancellation also benefits the Romberg method.)

Shifting the range left a little, so the integral is from −2.25 to 1.75, removes the symmetry. Nevertheless, the trapezoid method is rather slow, the polynomial interpolation method of Romberg is acceptable, and the Gaussian method requires the least work — if the number of points is known in advance. As well, rational interpolation can use the same trapezoid evaluations as the Romberg method to greater effect.

Quadrature method cost comparison
Method Trapezoid Romberg Rational Gauss
Points 1048577 257 129 36
Rel. Err. −5.3×10−13 −6.3×10−15 8.8×10−15 3.1×10−15
Value

In practice, each method must use extra evaluations to ensure an error bound on an unknown function; this tends to offset some of the advantage of the pure Gaussian method, and motivates the popular Gauss–Kronrod quadrature formulas. Symmetry can still be exploited by splitting this integral into two ranges, from −2.25 to −1.75 (no symmetry), and from −1.75 to 1.75 (symmetry). More broadly, adaptive quadrature partitions a range into pieces based on function properties, so that data points are concentrated where they are needed most.

This brief introduction omits higher-dimensional integrals (for example, area and volume calculations), where alternatives such as Monte Carlo integration have great importance.

A calculus text is no substitute for numerical analysis, but the reverse is also true. Even the best adaptive numerical code sometimes requires a user to help with the more demanding integrals. For example, improper integrals may require a change of variable or methods that can avoid infinite function values; and known properties like symmetry and periodicity may provide critical leverage.

See also

  • Lists of integrals - integrals of the most common functions.
  • Multiple integral
  • Antiderivative
  • Numerical integration
  • Integral equation
  • Riemann integral
  • Riemann-Stieltjes integral
  • Henstock–Kurzweil integral
  • Lebesgue integration
  • Darboux integral
  • Riemann sum
  • Product integral


References

  1. Shea, Marilyn (May 2007), Biography of Zu Chongzhi, University of Maine, http://hua.umf.maine.edu/China/astronomy/tianpage/0014ZuChongzhi9296bw.html, retrieved on 9 January 2009 
    Katz, Victor J. (2004), A History of Mathematics, Brief Version, Addison-Wesley, pp. 125–126, ISBN 978-0-321-16193-2 
  2. Victor J. Katz (1995), "Ideas of Calculus in Islam and India", Mathematics Magazine 68 (3): 163-174 [165]
  3. Victor J. Katz (1995), "Ideas of Calculus in Islam and India", Mathematics Magazine 68 (3): 163–174 [165–9 & 173–4]
  4. Bartle, Robert G. (1996). Return of the Riemann Integral. The American Mathematical Monthly 103: 625-632.

External links

  • The Integrator by Wolfram Research
  • Function Calculator from WIMS
  • Mathematical Assistant on Web online calculation of integrals, allows to integrate in small steps (includes also hints for next step which cover techniques like by parts, substitution, partial fractions, application of formulas and others, powered by Maxima (software))

Online books

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