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As the positive integer n becomes larger and larger, the value n\cdot \sin\left(\tfrac1\right) becomes arbitrarily close to 1. We say that "the limit of the sequence n\cdot \sin\left(\tfrac1\right) equals 1."
In
mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, the limit of a sequence is the value that the terms of a sequence "tend to", and is often denoted using the \lim symbol (e.g., \lim_a_n).Courant (1961), p. 29. If such a limit exists, the sequence is called convergent. A sequence that does not converge is said to be divergent. The limit of a sequence is said to be the fundamental notion on which the whole of
mathematical analysis Analysis is the branch of mathematics dealing with continuous functions, limits, and related theories, such as differentiation, integration, measure, infinite sequences, series, and analytic functions. These theories are usually studied ...
ultimately rests. Limits can be defined in any metric or
topological space In mathematics, a topological space is, roughly speaking, a geometrical space in which closeness is defined but cannot necessarily be measured by a numeric distance. More specifically, a topological space is a set whose elements are called poin ...
, but are usually first encountered in the
real number In mathematics, a real number is a number that can be used to measure a ''continuous'' one-dimensional quantity such as a distance, duration or temperature. Here, ''continuous'' means that values can have arbitrarily small variations. Every ...
s.


History

The Greek philosopher Zeno of Elea is famous for formulating paradoxes that involve limiting processes. Leucippus, Democritus, Antiphon, Eudoxus, and Archimedes developed the
method of exhaustion The method of exhaustion (; ) is a method of finding the area of a shape by inscribing inside it a sequence of polygons whose areas converge to the area of the containing shape. If the sequence is correctly constructed, the difference in are ...
, which uses an infinite sequence of approximations to determine an area or a volume. Archimedes succeeded in summing what is now called a geometric series. Grégoire de Saint-Vincent gave the first definition of limit (terminus) of a geometric series in his work ''Opus Geometricum'' (1647): "The ''terminus'' of a progression is the end of the series, which none progression can reach, even not if she is continued in infinity, but which she can approach nearer than a given segment." Newton dealt with series in his works on ''Analysis with infinite series'' (written in 1669, circulated in manuscript, published in 1711), ''Method of fluxions and infinite series'' (written in 1671, published in English translation in 1736, Latin original published much later) and ''Tractatus de Quadratura Curvarum'' (written in 1693, published in 1704 as an Appendix to his ''Optiks''). In the latter work, Newton considers the binomial expansion of (''x'' + ''o'')''n'', which he then linearizes by ''taking the limit'' as ''o'' tends to 0. In the 18th century, mathematicians such as Euler succeeded in summing some ''divergent'' series by stopping at the right moment; they did not much care whether a limit existed, as long as it could be calculated. At the end of the century, Lagrange in his ''Théorie des fonctions analytiques'' (1797) opined that the lack of rigour precluded further development in calculus. Gauss in his etude of hypergeometric series (1813) for the first time rigorously investigated the conditions under which a series converged to a limit. The modern definition of a limit (for any ε there exists an index ''N'' so that ...) was given by Bernard Bolzano (''Der binomische Lehrsatz'', Prague 1816, which was little noticed at the time), and by Karl Weierstrass in the 1870s.


Real numbers

In the real numbers, a number L is the limit of the sequence (x_n), if the numbers in the sequence become closer and closer to L, and not to any other number.


Examples

*If x_n = c for constant ''c'', then x_n \to c.''Proof'': Choose N = 1. For every n \geq N, , x_n - c, = 0 < \varepsilon *If x_n = \frac, then x_n \to 0.''Proof'': choose N = \left\lfloor\frac\right\rfloor + 1 (the floor function). For every n \geq N, , x_n - 0, \le x_N = \frac < \varepsilon. *If x_n = \frac when n is even, and x_n = \frac when n is odd, then x_n \to 0. (The fact that x_ > x_n whenever n is odd is irrelevant.) *Given any real number, one may easily construct a sequence that converges to that number by taking decimal approximations. For example, the sequence 0.3, 0.33, 0.333, 0.3333, \dots converges to 1/3. Note that the decimal representation 0.3333\dots is the ''limit'' of the previous sequence, defined by 0.3333... : = \lim_ \sum_^n \frac *Finding the limit of a sequence is not always obvious. Two examples are \lim_ \left(1 + \tfrac\right)^n (the limit of which is the number ''e'') and the Arithmetic–geometric mean. The squeeze theorem is often useful in the establishment of such limits.


Definition

We call x the limit of the sequence (x_n), which is written :x_n \to x, or :\lim_ x_n = x, if the following condition holds: :For each
real number In mathematics, a real number is a number that can be used to measure a ''continuous'' one-dimensional quantity such as a distance, duration or temperature. Here, ''continuous'' means that values can have arbitrarily small variations. Every ...
\varepsilon > 0, there exists a
natural number In mathematics, the natural numbers are those numbers used for counting (as in "there are ''six'' coins on the table") and ordering (as in "this is the ''third'' largest city in the country"). Numbers used for counting are called '' cardinal ...
N such that, for every natural number n \geq N, we have , x_n - x, < \varepsilon. In other words, for every measure of closeness \varepsilon, the sequence's terms are eventually that close to the limit. The sequence (x_n) is said to converge to or tend to the limit x. Symbolically, this is: :\forall \varepsilon > 0 \left(\exists N \in \N \left(\forall n \in \N \left(n \geq N \implies , x_n - x, < \varepsilon \right)\right)\right). If a sequence (x_n) converges to some limit x, then it is convergent and x is the only limit; otherwise (x_n) is divergent. A sequence that has zero as its limit is sometimes called a null sequence.


Illustration

File:Folgenglieder im KOSY.svg, Example of a sequence which converges to the limit a. File:Epsilonschlauch.svg, Regardless which \varepsilon > 0 we have, there is an index N_0, so that the sequence lies afterwards completely in the epsilon tube (a-\varepsilon,a+\varepsilon). File:Epsilonschlauch klein.svg, There is also for a smaller \varepsilon_1 > 0 an index N_1, so that the sequence is afterwards inside the epsilon tube (a-\varepsilon_1,a+\varepsilon_1). File:Epsilonschlauch2.svg, For each \varepsilon > 0 there are only finitely many sequence members outside the epsilon tube.


Properties

Some other important properties of limits of real sequences include the following: *When it exists, the limit of a sequence is unique. *Limits of sequences behave well with respect to the usual arithmetic operations. If \lim_ a_n and \lim_ b_n exists, then ::\lim_ (a_n \pm b_n) = \lim_ a_n \pm \lim_ b_n ::\lim_ c a_n = c \cdot \lim_ a_n ::\lim_ (a_n \cdot b_n) = \left(\lim_ a_n \right)\cdot \left( \lim_ b_n \right) ::\lim_ \left(\frac\right) = \frac provided \lim_ b_n \ne 0 ::\lim_ a_n^p = \left( \lim_ a_n \right)^p *For any continuous function ''f'', if \lim_x_n exists, then \lim_ f \left(x_n \right) exists too. In fact, any real-valued function ''f'' is continuous if and only if it preserves the limits of sequences (though this is not necessarily true when using more general notions of continuity). *If a_n \leq b_n for all n greater than some N, then \lim_ a_n \leq \lim_ b_n. *( Squeeze theorem) If a_n \leq c_n \leq b_n for all n greater than some N, and \lim_ a_n = \lim_ b_n = L, then \lim_ c_n = L. *( Monotone convergence theorem) If a_n is bounded and monotonic for all n greater than some N, then it is convergent. *A sequence is convergent if and only if every subsequence is convergent. *If every subsequence of a sequence has its own subsequence which converges to the same point, then the original sequence converges to that point. These properties are extensively used to prove limits, without the need to directly use the cumbersome formal definition. For example, once it is proven that 1/n \to 0, it becomes easy to show—using the properties above—that \frac \to \frac (assuming that b \ne 0).


Infinite limits

A sequence (x_n) is said to tend to infinity, written :x_n \to \infty, or :\lim_x_n = \infty, if the following holds: :For every real number K, there is a natural number N such that for every natural number n \geq N, we have x_n > K; that is, the sequence terms are eventually larger than any fixed K. Symbolically, this is: :\forall K \in \mathbb \left(\exists N \in \N \left(\forall n \in \N \left(n \geq N \implies x_n > K \right)\right)\right). Similarly, we say a sequence tends to minus infinity, written :x_n \to -\infty, or :\lim_x_n = -\infty, if the following holds: :For every real number K, there is a natural number N such that for every natural number n \geq N, we have x_n < K; that is, the sequence terms are eventually smaller than any fixed K. Symbolically, this is: :\forall K \in \mathbb \left(\exists N \in \N \left(\forall n \in \N \left(n \geq N \implies x_n < K \right)\right)\right). If a sequence tends to infinity or minus infinity, then it is divergent. However, a divergent sequence need not tend to plus or minus infinity, and the sequence x_n=(-1)^n provides one such example.


Metric spaces


Definition

A point x of the
metric space In mathematics, a metric space is a set together with a notion of '' distance'' between its elements, usually called points. The distance is measured by a function called a metric or distance function. Metric spaces are the most general setti ...
(X, d) is the limit of the sequence (x_n) if: :For each
real number In mathematics, a real number is a number that can be used to measure a ''continuous'' one-dimensional quantity such as a distance, duration or temperature. Here, ''continuous'' means that values can have arbitrarily small variations. Every ...
\varepsilon > 0, there is a
natural number In mathematics, the natural numbers are those numbers used for counting (as in "there are ''six'' coins on the table") and ordering (as in "this is the ''third'' largest city in the country"). Numbers used for counting are called '' cardinal ...
N such that, for every natural number n \geq N, we have d(x_n, x) < \varepsilon . Symbolically, this is: :\forall \varepsilon > 0 \left(\exists N \in \N \left(\forall n \in \N \left(n \geq N \implies d(x_n, x) < \varepsilon \right)\right)\right). This coincides with the definition given for real numbers when X = \R and d(x, y) = , x-y, .


Properties

*When it exists, the limit of a sequence is unique, as distinct points are separated by some positive distance, so for \varepsilon less than half this distance, sequence terms cannot be within a distance \varepsilon of both points. *For any continuous function ''f'', if \lim_ x_n exists, then \lim_ f(x_n) = f\left(\lim_x_n \right). In fact, a function ''f'' is continuous if and only if it preserves the limits of sequences.


Cauchy sequences

A Cauchy sequence is a sequence whose terms ultimately become arbitrarily close together, after sufficiently many initial terms have been discarded. The notion of a Cauchy sequence is important in the study of sequences in metric spaces, and, in particular, in real analysis. One particularly important result in real analysis is the ''Cauchy criterion for convergence of sequences'': a sequence of real numbers is convergent if and only if it is a Cauchy sequence. This remains true in other complete metric spaces.


Topological spaces


Definition

A point x \in X of the topological space (X, \tau) is a or of the sequence \left(x_n\right)_ if: :For every
neighbourhood A neighbourhood (British English, Irish English, Australian English and Canadian English) or neighborhood (American English; see spelling differences) is a geographically localised community within a larger city, town, suburb or rural a ...
U of x, there exists some N \in \N such that for every n \geq N, we have x_n \in U. This coincides with the definition given for metric spaces, if (X, d) is a metric space and \tau is the topology generated by d. A limit of a sequence of points \left(x_n\right)_ in a topological space T is a special case of a limit of a function: the
domain Domain may refer to: Mathematics *Domain of a function, the set of input values for which the (total) function is defined ** Domain of definition of a partial function ** Natural domain of a partial function **Domain of holomorphy of a function * ...
is \N in the space \N \cup \lbrace + \infty \rbrace, with the induced topology of the affinely extended real number system, the range is T, and the function argument n tends to +\infty, which in this space is a limit point of \N.


Properties

In a
Hausdorff space In topology and related branches of mathematics, a Hausdorff space ( , ), separated space or T2 space is a topological space where, for any two distinct points, there exist neighbourhoods of each which are disjoint from each other. Of the ma ...
, limits of sequences are unique whenever they exist. Note that this need not be the case in non-Hausdorff spaces; in particular, if two points x and y are topologically indistinguishable, then any sequence that converges to x must converge to y and vice versa.


Hyperreal numbers

The definition of the limit using the hyperreal numbers formalizes the intuition that for a "very large" value of the index, the corresponding term is "very close" to the limit. More precisely, a real sequence (x_n) tends to ''L'' if for every infinite hypernatural ''H'', the term x_H is infinitely close to ''L'' (i.e., the difference x_H - L is infinitesimal). Equivalently, ''L'' is the standard part of x_H: : L = (x_H). Thus, the limit can be defined by the formula :\lim_ x_n= (x_H). where the limit exists if and only if the righthand side is independent of the choice of an infinite ''H''.


Sequence of more than one index

Sometimes one may also consider a sequence with more than one index, for example, a double sequence (x_). This sequence has a limit L if it becomes closer and closer to L when both ''n'' and ''m'' becomes very large.


Example

*If x_ = c for constant ''c'', then x_ \to c. *If x_ = \frac, then x_ \to 0. *If x_ = \frac, then the limit does not exist. Depending on the relative "growing speed" of ''n'' and ''m'', this sequence can get closer to any value between 0 and 1.


Definition

We call x the double limit of the sequence (x_), written :x_ \to x, or :\lim_ x_ = x, if the following condition holds: :For each
real number In mathematics, a real number is a number that can be used to measure a ''continuous'' one-dimensional quantity such as a distance, duration or temperature. Here, ''continuous'' means that values can have arbitrarily small variations. Every ...
\varepsilon > 0, there exists a
natural number In mathematics, the natural numbers are those numbers used for counting (as in "there are ''six'' coins on the table") and ordering (as in "this is the ''third'' largest city in the country"). Numbers used for counting are called '' cardinal ...
N such that, for every pair of natural numbers n, m \geq N, we have , x_ - x, < \varepsilon. In other words, for every measure of closeness \varepsilon, the sequence's terms are eventually that close to the limit. The sequence (x_) is said to converge to or tend to the limit x. Symbolically, this is: :\forall \varepsilon > 0 \left(\exists N \in \N \left(\forall n, m \in \N \left(n, m \geq N \implies , x_ - x, < \varepsilon \right)\right)\right) . Note that the double limit is different from taking limit in ''n'' first, and then in ''m''. The latter is known as iterated limit. Given that both the double limit and the iterated limit exists, they have the same value. However, it is possible that one of them exist but the other does not.


Infinite limits

A sequence (x_) is said to tend to infinity, written :x_ \to \infty, or :\lim_x_ = \infty, if the following holds: :For every real number K, there is a natural number N such that for every pair of natural numbers n,m \geq N, we have x_ > K; that is, the sequence terms are eventually larger than any fixed K. Symbolically, this is: :\forall K \in \mathbb \left(\exists N \in \N \left(\forall n, m \in \N \left(n, m \geq N \implies x_ > K \right)\right)\right). Similarly, a sequence (x_) tends to minus infinity, written :x_ \to -\infty, or :\lim_x_ = -\infty, if the following holds: :For every real number K, there is a natural number N such that for every pair of natural numbers n,m \geq N, we have x_ < K; that is, the sequence terms are eventually smaller than any fixed K. Symbolically, this is: :\forall K \in \mathbb \left(\exists N \in \N \left(\forall n, m \in \N \left(n, m \geq N \implies x_ < K \right)\right)\right). If a sequence tends to infinity or minus infinity, then it is divergent. However, a divergent sequence need not tend to plus or minus infinity, and the sequence x_=(-1)^ provides one such example.


Pointwise limits and uniform limits

For a double sequence (x_), we may take limit in one of the indices, say, n \to \infty, to obtain a single sequence (y_m). In fact, there are two possible meanings when taking this limit. The first one is called pointwise limit, denoted :x_ \to y_m\quad \text, or :\lim_ x_ = y_m\quad \text, which means: :For each
real number In mathematics, a real number is a number that can be used to measure a ''continuous'' one-dimensional quantity such as a distance, duration or temperature. Here, ''continuous'' means that values can have arbitrarily small variations. Every ...
\varepsilon > 0 and each fixed
natural number In mathematics, the natural numbers are those numbers used for counting (as in "there are ''six'' coins on the table") and ordering (as in "this is the ''third'' largest city in the country"). Numbers used for counting are called '' cardinal ...
m, there exists a natural number N(\varepsilon, m) > 0 such that, for every natural number n \geq N, we have , x_ - y_m, < \varepsilon. Symbolically, this is: :\forall \varepsilon > 0 \left( \forall m \in \mathbb \left(\exists N \in \N \left(\forall n \in \N \left(n \geq N \implies , x_ - y_m, < \varepsilon \right)\right)\right)\right). When such a limit exists, we say the sequence (x_) converges pointwise to (y_m). The second one is called uniform limit, denoted :x_ \to y_m \quad \text, :\lim_ x_ = y_m \quad \text, :x_ \rightrightarrows y_m , or :\underset \; x_ = y_m , which means: :For each
real number In mathematics, a real number is a number that can be used to measure a ''continuous'' one-dimensional quantity such as a distance, duration or temperature. Here, ''continuous'' means that values can have arbitrarily small variations. Every ...
\varepsilon > 0, there exists a natural number N(\varepsilon) > 0 such that, for every
natural number In mathematics, the natural numbers are those numbers used for counting (as in "there are ''six'' coins on the table") and ordering (as in "this is the ''third'' largest city in the country"). Numbers used for counting are called '' cardinal ...
m and for every natural number n \geq N, we have , x_ - y_m, < \varepsilon. Symbolically, this is: :\forall \varepsilon > 0 \left(\exists N \in \N \left( \forall m \in \mathbb \left(\forall n \in \N \left(n \geq N \implies , x_ - y_m, < \varepsilon \right)\right)\right)\right). In this definition, the choice of N is independent of m. In other words, the choice of N is ''uniformly applicable'' to all natural numbers m. Hence, one can easily see that uniform convergence is a stronger property than pointwise convergence: the existence of uniform limit implies the existence and equality of pointwise limit: :If x_ \to y_m uniformly, then x_ \to y_m pointwise. When such a limit exists, we say the sequence (x_)
converges uniformly In the mathematical field of analysis, uniform convergence is a mode of convergence of functions stronger than pointwise convergence. A sequence of functions (f_n) converges uniformly to a limiting function f on a set E if, given any arbitrarily s ...
to (y_m).


Iterated limit

For a double sequence (x_), we may take limit in one of the indices, say, n \to \infty, to obtain a single sequence (y_m), and then take limit in the other index, namely m \to \infty, to get a number y. Symbolically, :\lim_ \lim_ x_ = \lim_ y_m = y. This limit is known as iterated limit of the double sequence. Note that the order of taking limits may affect the result, i.e., :\lim_ \lim_ x_ \ne \lim_ \lim_ x_ in general. A sufficient condition of equality is given by the Moore-Osgood theorem, which requires the limit \lim_x_ = y_m to be uniform in ''m''.


See also

* Limit point * Subsequential limit * Limit superior and limit inferior * Limit of a function * Limit of a sequence of functions * Limit of a sequence of sets * Limit of a net *
Pointwise convergence In mathematics, pointwise convergence is one of various senses in which a sequence of functions can converge to a particular function. It is weaker than uniform convergence, to which it is often compared. Definition Suppose that X is a set an ...
* Uniform convergence * Modes of convergence


Notes


Proofs


References

* * * Courant, Richard (1961). "Differential and Integral Calculus Volume I", Blackie & Son, Ltd., Glasgow. * Frank Morley and James Harknessbr>A treatise on the theory of functions
(New York: Macmillan, 1893)


External links

*

{{Calculus topics Limits (mathematics) Sequences and series