Limit of a function
In mathematics, the limit of a function is a fundamental concept in calculus and analysis concerning the behavior of that function near a particular input.
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Formal definitions, first devised in the early 19th century, are given below. Informally, a function f assigns an output f(x) to every input x. We say the function has a limit L at an input p: this means f(x) gets closer and closer to L as x moves closer and closer to p. More specifically, when f is applied to any input sufficiently close to p, the output value is forced arbitrarily close to L. On the other hand, if some inputs very close to p are taken to outputs that stay a fixed distance apart, we say the limit does not exist.
The notion of a limit has many applications in modern calculus. In particular, the many definitions of continuity employ the limit: roughly, a function is continuous if all of its limits agree with the values of the function. It also appears in the definition of the derivative: in the calculus of one variable, this is the limiting value of the slope of secant lines to the graph of a function.
History
Although implicit in the development of calculus of the 17th and 18th centuries, the modern idea of the limit of a function goes back to Bolzano who, in 1817, introduced the basics of the epsilondelta technique to define continuous functions. However, his work was not known during his lifetime.[1] Cauchy discussed variable quantities, infinitesimals, and limits and defined continuity of by saying that an infinitesimal change in x necessarily produces an infinitesimal change in y in his 1821 book Cours d'analyse, while (Grabiner 1983) claims that he only gave a verbal definition.[2] Weierstrass first introduced the epsilondelta definition of limit in the form it is usually written today. He also introduced the notations lim and lim_{x→x0}.[3]
The modern notation of placing the arrow below the limit symbol is due to Hardy in his book A Course of Pure Mathematics in 1908.[4]
Motivation
Imagine a person walking over a landscape represented by the graph of y = f(x). Her horizontal position is measured by the value of x, much like the position given by a map of the land or by a global positioning system. Her altitude is given by the coordinate y. She is walking towards the horizontal position given by x = p. As she gets closer and closer to it, she notices that her altitude approaches L. If asked about the altitude of x = p, she would then answer L.
What, then, does it mean to say that her altitude approaches L? It means that her altitude gets nearer and nearer to L except for a possible small error in accuracy. For example, suppose we set a particular accuracy goal for our traveler: she must get within ten meters of L. She reports back that indeed she can get within ten vertical meters of L, since she notes that when she is within fifty horizontal meters of p, her altitude is always ten meters or less from L.
The accuracy goal is then changed: can she get within one vertical meter? Yes. If she is anywhere within seven horizontal meters of p, then her altitude always remains within one meter from the target L. In summary, to say that the traveler's altitude approaches L as her horizontal position approaches p means that for every target accuracy goal, however small it may be, there is some neighborhood of p whose altitude fulfills that accuracy goal.
The initial informal statement can now be explicated:
 The limit of a function f(x) as x approaches p is a number L with the following property: given any target distance from L, there is a distance from p within which the values of f(x) remain within the target distance.
This explicit statement is quite close to the formal definition of the limit of a function with values in a topological space.
To say that
means that ƒ(x) can be made as close as desired to L by making x close enough, but not equal, to p.
The following definitions (known as (ε, δ)definitions) are the generally accepted ones for the limit of a function in various contexts.
Functions of a single variable
Suppose f : R → R is defined on the real line and p, L ∈ R. It is said the limit of f, as x approaches p, is L and written
or alternatively as:
 as
if the following property holds:
 For every real ε > 0, there exists a real δ > 0 such that for all real x, 0 <  x − p  < δ implies  f(x) − L  < ε.
The value of the limit does not depend on the value of f(p).
A more general definition applies for functions defined on subsets of the real line. Let (a, b) be an open interval in R, and p a point of (a, b). Let f be a realvalued function defined on all of (a, b) except possibly at p itself. It is then said that the limit of f as x approaches p is L if, for every real ε > 0, there exists a real δ > 0 such that 0 <  x − p  < δ and x ∈ (a, b) implies  f(x) − L  < ε.
Here the value of the limit does not depend on f being defined at p, nor on the value f(p), if it is defined.
The letters ε and δ can be understood as "error" and "distance", and in fact Cauchy used ε as an abbreviation for "error" in some of his work,[2] though in his definition of continuity he used an infinitesimal rather than either ε or δ (see Cours d'Analyse). In these terms, the error (ε) in the measurement of the value at the limit can be made as small as desired by reducing the distance (δ) to the limit point. As discussed below this definition also works for functions in a more general context. The idea that δ and ε represent distances helps suggest these generalizations.
Existence and onesided limits
Alternatively x may approach p from above (right) or below (left), in which case the limits may be written as
or
respectively. If these limits exist at p and are equal there, then this can be referred to as the limit of f(x) at p. If the onesided limits exist at p, but are unequal, there is no limit at p (the limit at p does not exist). If either onesided limit does not exist at p, the limit at p does not exist.
A formal definition is as follows. The limit of f(x) as x approaches p from above is L if, for every ε > 0, there exists a δ > 0 such that f(x) − L < ε whenever 0 < x − p < δ. The limit of f(x) as x approaches p from below is L if, for every ε > 0, there exists a δ > 0 such that f(x) − L < ε whenever 0 < p − x < δ.
If the limit does not exist then the oscillation of f at p is nonzero.
More general subsets
Apart from open intervals, limits can be defined for functions on arbitrary subsets of R, as follows (Bartle & Sherbert 2000). Let f be a realvalued function defined on a subset S of the real line. Let p be a limit point of S—that is, p is the limit of some sequence of elements of S distinct from p. The limit of f, as x approaches p from values in S, is L if, for every ε > 0, there exists a δ > 0 such that 0 < x − p < δ and x ∈ S implies f(x) − L < ε.
This limit is often written
The condition that f be defined on S is that S be a subset of the domain of f. This generalization includes as special cases limits on an interval, as well as lefthanded limits of realvalued functions (e.g., by taking S to be an open interval of the form ), and righthanded limits (e.g., by taking S to be an open interval of the form ). It also extends the notion of onesided limits to the included endpoints of (half)closed intervals, so the Square root function f(x)=√x can have limit 0 as x approaches 0 from above.
Deleted versus nondeleted limits
The definition of limit given here does not depend on how (or whether) f is defined at p. Bartle (1967), refers to this as a deleted limit, because it excludes the value of f at p. The corresponding nondeleted limit does depend on the value of f at p, if p is in the domain of f:
 A number L is the nondeleted limit of f as x approaches p if, for every ε > 0, there exists a δ > 0 such that  x − p  < δ and x ∈ Dm(f) implies  f(x) − L  < ε.
The definition is the same, except that the neighborhood  x − p  < δ now includes the point p, in contrast to the deleted neighborhood 0 <  x − p  < δ. This makes the definition of a nondeleted limit less general. One of the advantages of working with nondeleted limits is that they allow to state the theorem about limits of compositions without any constraints on the functions (other than the existence of their nondeleted limits) (Hubbard (2015)).
Bartle (1967) notes that although by "limit" some authors do mean this nondeleted limit, deleted limits are the most popular. For example, Apostol (1974), Courant (1924), Hardy (1921), Rudin (1964), Whittaker & Watson (1902) all by "limit" mean the deleted version.
Examples
Nonexistence of onesided limit(s)
The function
has no limit at (the lefthand limit does not exist due to the oscillatory nature of the sine function, and the righthand limit does not exist due to the asymptotic behaviour of the reciprocal function), but has a limit at every other xcoordinate.
The function
(the Dirichlet function) has no limit at any xcoordinate.
Nonequality of onesided limits
The function
has a limit at every nonzero xcoordinate (the limit equals 1 for negative x and equals 2 for positive x). The limit at x = 0 does not exist (the lefthand limit equals 1, whereas the righthand limit equals 2).
Limits at only one point
The functions
and
both have a limit at x = 0 and it equals 0.
Limits at countably many points
The function
has a limit at any xcoordinate of the form , where n is any integer.
Functions on metric spaces
Suppose M and N are subsets of metric spaces A and B, respectively, and f : M → N is defined between M and N, with x ∈ M, p a limit point of M and L ∈ N. It is said that the limit of f as x approaches p is L and write
if the following property holds:
 For every ε > 0, there exists a δ > 0 such that d_{B}(f(x), L) < ε whenever 0 < d_{A}(x, p) < δ.
Again, note that p need not be in the domain of f, nor does L need to be in the range of f, and even if f(p) is defined it need not be equal to L.
An alternative definition using the concept of neighbourhood is as follows:
if, for every neighbourhood V of L in B, there exists a neighbourhood U of p in A such that f(U ∩ M − {p}) ⊆ V.
Functions on topological spaces
Suppose X,Y are topological spaces with Y a Hausdorff space. Let p be a limit point of Ω ⊆ X, and L ∈Y. For a function f : Ω → Y, it is said that the limit of f as x approaches p is L (i.e., f(x) → L as x → p) and written
if the following property holds:
 For every open neighborhood V of L, there exists an open neighborhood U of p such that f(U ∩ Ω − {p}) ⊆ V.
This last part of the definition can also be phrased "there exists an open punctured neighbourhood U of p such that f(U∩Ω) ⊆ V ".
Note that the domain of f does not need to contain p. If it does, then the value of f at p is irrelevant to the definition of the limit. In particular, if the domain of f is X − {p} (or all of X), then the limit of f as x → p exists and is equal to L if, for all subsets Ω of X with limit point p, the limit of the restriction of f to Ω exists and is equal to L. Sometimes this criterion is used to establish the nonexistence of the twosided limit of a function on R by showing that the onesided limits either fail to exist or do not agree. Such a view is fundamental in the field of general topology, where limits and continuity at a point are defined in terms of special families of subsets, called filters, or generalized sequences known as nets.
Alternatively, the requirement that Y be a Hausdorff space can be relaxed to the assumption that Y be a general topological space, but then the limit of a function may not be unique. In particular, one can no longer talk about the limit of a function at a point, but rather a limit or the set of limits at a point.
A function is continuous at a limit point p of and in its domain if and only if f(p) is the (or, in the general case, a) limit of f(x) as x tends to p.
Limits involving infinity
Limits at infinity
For f(x) a real function, the limit of f as x approaches infinity is L, denoted
means that for all , there exists c such that whenever x > c. Or, symbolically:
 .
Similarly, the limit of f as x approaches negative infinity is L, denoted
means that for all there exists c such that whenever x < c. Or, symbolically:
 .
For example,
Infinite limits
For a function whose values grow without bound, the function diverges and the usual limit does not exist. However, in this case one may introduce limits with infinite values. For example, the statement the limit of f as x approaches a is infinity, denoted
means that for all there exists such that whenever
These ideas can be combined in a natural way to produce definitions for different combinations, such as
For example,
Limits involving infinity are connected with the concept of asymptotes.
These notions of a limit attempt to provide a metric space interpretation to limits at infinity. In fact, they are consistent with the topological space definition of limit if
 a neighborhood of −∞ is defined to contain an interval [−∞, c) for some c ∈ R,
 a neighborhood of ∞ is defined to contain an interval (c, ∞] where c ∈ R, and
 a neighborhood of a ∈ R is defined in the normal way metric space R.
In this case, R is a topological space and any function of the form f: X → Y with X, Y⊆ R is subject to the topological definition of a limit. Note that with this topological definition, it is easy to define infinite limits at finite points, which have not been defined above in the metric sense.
Alternative notation
Many authors[5] allow for the projectively extended real line to be used as a way to include infinite values as well as extended real line. With this notation, the extended real line is given as R ∪ {−∞, +∞} and the projectively extended real line is R ∪ {∞} where a neighborhood of ∞ is a set of the form {x: x > c}. The advantage is that one only needs three definitions for limits (left, right, and central) to cover all the cases. As presented above, for a completely rigorous account, we would need to consider 15 separate cases for each combination of infinities (five directions: −∞, left, central, right, and +∞; three bounds: −∞, finite, or +∞). There are also noteworthy pitfalls. For example, when working with the extended real line, does not possess a central limit (which is normal):
In contrast, when working with the projective real line, infinities (much like 0) are unsigned, so, the central limit does exist in that context:
In fact there are a plethora of conflicting formal systems in use. In certain applications of numerical differentiation and integration, it is, for example, convenient to have signed zeroes. A simple reason has to do with the converse of , namely, it is convenient for to be considered true. Such zeroes can be seen as an approximation to infinitesimals.
Limits at infinity for rational functions
There are three basic rules for evaluating limits at infinity for a rational function f(x) = p(x)/q(x): (where p and q are polynomials):
 If the degree of p is greater than the degree of q, then the limit is positive or negative infinity depending on the signs of the leading coefficients;
 If the degree of p and q are equal, the limit is the leading coefficient of p divided by the leading coefficient of q;
 If the degree of p is less than the degree of q, the limit is 0.
If the limit at infinity exists, it represents a horizontal asymptote at y = L. Polynomials do not have horizontal asymptotes; such asymptotes may however occur with rational functions.
Functions of more than one variable
By noting that x − p represents a distance, the definition of a limit can be extended to functions of more than one variable. In the case of a function f : R^{2} → R,
if
 for every ε > 0 there exists a δ > 0 such that for all (x,y) with 0 < (x,y) − (p,q) < δ, then f(x,y) − L < ε
where (x,y) − (p,q) represents the Euclidean distance. This can be extended to any number of variables.
Sequential limits
Let f : X → Y be a mapping from a topological space X into a Hausdorff space Y, p ∈ X a limit point of X and L ∈ Y.
 The sequential limit of f as x tends to p is L if, for every sequence (x_{n}) in X − {p} that converges to p, the sequence f(x_{n}) converges to L.
If L is the limit (in the sense above) of f as x approaches p, then it is a sequential limit as well, however the converse need not hold in general. If in addition X is metrizable, then L is the sequential limit of f as x approaches p if and only if it is the limit (in the sense above) of f as x approaches p.
Other characterizations
In terms of sequences
For functions on the real line, one way to define the limit of a function is in terms of the limit of sequences. (This definition is usually attributed to Eduard Heine.) In this setting:
if and only if for all sequences (with not equal to a for all n) converging to the sequence converges to . It was shown by Sierpiński in 1916 that proving the equivalence of this definition and the definition above, requires and is equivalent to a weak form of the axiom of choice. Note that defining what it means for a sequence to converge to requires the epsilon, delta method.
Similarly as it was the case of Weierstrass's definition, a more general Heine definition applies to functions defined on subsets of the real line. Let f be a realvalued function with the domain Dm(f). Let a be the limit of a sequence of elements of Dm(f) \ {a}. Then the limit (in this sense) of f is L as x approaches p if for every sequence ∈ Dm(f) \ {a} (so that for all n, is not equal to a) that converges to a, the sequence converges to . This is the same as the definition of a sequential limit in the preceding section obtained by regarding the subset Dm(f) of R as a metric space with the induced metric.
In nonstandard calculus
In nonstandard calculus the limit of a function is defined by:
if and only if for all , is infinitesimal whenever is infinitesimal. Here are the hyperreal numbers and is the natural extension of f to the nonstandard real numbers. Keisler proved that such a hyperreal definition of limit reduces the quantifier complexity by two quantifiers.[6] On the other hand, Hrbacek writes that for the definitions to be valid for all hyperreal numbers they must implicitly be grounded in the εδ method, and claims that, from the pedagogical point of view, the hope that nonstandard calculus could be done without εδ methods cannot be realized in full.[7] Bŀaszczyk et al. detail the usefulness of microcontinuity in developing a transparent definition of uniform continuity, and characterize Hrbacek's criticism as a "dubious lament".[8]
In terms of nearness
At the 1908 international congress of mathematics F. Riesz introduced an alternate way defining limits and continuity in concept called "nearness". A point is defined to be near a set if for every there is a point so that . In this setting the
if and only if for all , is near whenever is near . Here is the set . This definition can also be extended to metric and topological spaces.
Relationship to continuity
The notion of the limit of a function is very closely related to the concept of continuity. A function ƒ is said to be continuous at c if it is both defined at c and its value at c equals the limit of f as x approaches c:
(We have here assumed that c is a limit point of the domain of f.)
Properties
If a function f is realvalued, then the limit of f at p is L if and only if both the righthanded limit and lefthanded limit of f at p exist and are equal to L.
The function f is continuous at p if and only if the limit of f(x) as x approaches p exists and is equal to f(p). If f : M → N is a function between metric spaces M and N, then it is equivalent that f transforms every sequence in M which converges towards p into a sequence in N which converges towards f(p).
If N is a normed vector space, then the limit operation is linear in the following sense: if the limit of f(x) as x approaches p is L and the limit of g(x) as x approaches p is P, then the limit of f(x) + g(x) as x approaches p is L + P. If a is a scalar from the base field, then the limit of af(x) as x approaches p is aL.
If f is a realvalued (or complexvalued) function, then taking the limit is compatible with the algebraic operations, provided the limits on the right sides of the equations below exist (the last identity only holds if the denominator is nonzero). This fact is often called the algebraic limit theorem.
In each case above, when the limits on the right do not exist, or, in the last case, when the limits in both the numerator and the denominator are zero, nonetheless the limit on the left, called an indeterminate form, may still exist—this depends on the functions f and g. These rules are also valid for onesided limits, for the case p = ±∞, and also for infinite limits using the rules
 q + ∞ = ∞ for q ≠ −∞
 q × ∞ = ∞ if q > 0
 q × ∞ = −∞ if q < 0
 q / ∞ = 0 if q ≠ ± ∞
(see extended real number line).
Note that there is no general rule for the case q / 0; it all depends on the way 0 is approached. Indeterminate forms—for instance, 0/0, 0×∞, ∞−∞, and ∞/∞—are also not covered by these rules, but the corresponding limits can often be determined with L'Hôpital's rule or the Squeeze theorem.
Limits of compositions of functions
In general, from knowing that
 and ,
it does not follow that . However, this "chain rule" does hold if one of the following additional conditions holds:
 f(b) = c (that is, f is continuous at b), or
 g does not take the value b near a (that is, there exists a such that if then ).
As an example of this phenomenon, consider the following functions that violates both additional restrictions:
Since the value at f(0) is a removable discontinuity,
 for all .
Thus, the naïve chain rule would suggest that the limit of f(f(x)) is 0. However, it is the case that
and so
 for all .
Limits of special interest
Rational functions
For a nonnegative integer and constants and ,
This can be proven by dividing both the numerator and denominator by . If the numerator is a polynomial of higher degree, the limit does not exist. If the denominator is of higher degree, the limit is 0.
Trigonometric functions
Exponential functions
Logarithmic functions
L'Hôpital's rule
This rule uses derivatives to find limits of indeterminate forms 0/0 or ±∞/∞, and only applies to such cases. Other indeterminate forms may be manipulated into this form. Given two functions f(x) and g(x), defined over an open interval I containing the desired limit point c, then if:
 or , and
 and are differentiable over , and
 for all , and
 exists,
then:
Normally, the first condition is the most important one.
For example:
Summations and integrals
Specifying an infinite bound on a summation or integral is a common shorthand for specifying a limit.
A short way to write the limit is . An important example of limits of sums such as these are series.
A short way to write the limit is .
A short way to write the limit is .
See also
Wikimedia Commons has media related to Limit of a function. 
Notes
 Felscher, Walter (2000), "Bolzano, Cauchy, Epsilon, Delta", American Mathematical Monthly, 107 (9): 844–862, doi:10.2307/2695743, JSTOR 2695743
 Grabiner, Judith V. (1983), "Who Gave You the Epsilon? Cauchy and the Origins of Rigorous Calculus", American Mathematical Monthly, 90 (3): 185–194, doi:10.2307/2975545, JSTOR 2975545, collected in Who Gave You the Epsilon?, ISBN 9780883855690 pp. 5–13. Also available at: http://www.maa.org/pubs/Calc_articles/ma002.pdf
 Burton, David M. (1997), The History of Mathematics: An introduction (Third ed.), New York: McGraw–Hill, pp. 558–559, ISBN 9780070094659
 Miller, Jeff (1 December 2004), Earliest Uses of Symbols of Calculus, retrieved 18 December 2008
 For example, "Limit" at Encyclopaedia of Mathematics
 Keisler, H. Jerome (2008), "Quantifiers in limits" (PDF), Andrzej Mostowski and foundational studies, IOS, Amsterdam, pp. 151–170
 Hrbacek, K. (2007), "Stratified Analysis?", in Van Den Berg, I.; Neves, V. (eds.), The Strength of Nonstandard Analysis, Springer
 Bŀaszczyk, Piotr; Katz, Mikhail; Sherry, David (2012), "Ten misconceptions from the history of analysis and their debunking", Foundations of Science, 18 (1): 43–74, arXiv:1202.4153, doi:10.1007/s1069901292858
References
 Apostol, Tom M. (1974), Mathematical Analysis (2 ed.), Addison–Wesley, ISBN 0201002884
 Bartle, Robert (1967), The elements of real analysis, Wiley
 Courant, Richard (1924), Vorlesungen über Differential und Integralrechnung, Springer Verlag
 Hardy, G.H. (1921), A course in pure mathematics, Cambridge University Press
 Hubbard, John H. (2015), Vector calculus, linear algebra, and differential forms: A unified approach (Fifth ed.), Matrix Editions
 Page, Warren; Hersh, Reuben; Selden, Annie; et al., eds. (2002), "Media Highlights", The College Mathematics, 33 (2): 147–154, JSTOR 2687124.
 Rudin, Walter (1964), Principles of mathematical analysis, McGrawHill
 Sutherland, W. A. (1975), Introduction to Metric and Topological Spaces, Oxford: Oxford University Press, ISBN 0198531613
 Sherbert, Robert (2000), Introduction to real analysis, Wiley
 Whittaker; Watson (1904), A course of modern analysis, Cambridge University Press
External links
 MacTutor History of Weierstrass.
 MacTutor History of Bolzano
 Visual Calculus by Lawrence S. Husch, University of Tennessee (2001)