In mathematics, a limit is the value that a function (or sequence) "approaches" as the input (or index) "approaches" some value.^{[1]} Limits are essential to calculus (and mathematical analysis in general) and are used to define continuity, derivatives, and integrals.
The concept of a limit of a sequence is further generalized to the concept of a limit of a topological net, and is closely related to limit and direct limit in category theory.
In formulas, a limit of a function is usually written as
and is read as "the limit of f of x as x approaches c equals L". The fact that a function f approaches the limit L as x approaches c is sometimes denoted by a right arrow (→), as in
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Limit of a function
Suppose f is a real-valued function and c is a real number. Intuitively speaking, the expression
means that f(x) can be made to be as close to L as desired by making x sufficiently close to c. In that case, the above equation can be read as "the limit of f of x, as x approaches c, is L".
Augustin-Louis Cauchy in 1821,^{[2]} followed by Karl Weierstrass, formalized the definition of the limit of a function which became known as the (ε, δ)-definition of limit. The definition uses ε (the lowercase Greek letter epsilon) to represent any small positive number, so that "f(x) becomes arbitrarily close to L" means that f(x) eventually lies in the interval (L − ε, L + ε), which can also be written using the absolute value sign as |f(x) − L| < ε.^{[2]} The phrase "as x approaches c" then indicates that we refer to values of x whose distance from c is less than some positive number δ (the lower case Greek letter delta)—that is, values of x within either (c − δ, c) or (c, c + δ), which can be expressed with 0 < |x − c| < δ. The first inequality means that the distance between x and c is greater than 0 and that x ≠ c, while the second indicates that x is within distance δ of c.^{[2]}
The above definition of a limit is true even if f(c) ≠ L. Indeed, the function f need not even be defined at c.
For example, if
then f(1) is not defined (see division by zero), yet as x moves arbitrarily close to 1, f(x) correspondingly approaches 2:
f(0.9) | f(0.99) | f(0.999) | f(1.0) | f(1.001) | f(1.01) | f(1.1) |
1.900 | 1.990 | 1.999 | ⇒ undefined ⇐ | 2.001 | 2.010 | 2.100 |
Thus, f(x) can be made arbitrarily close to the limit of 2 just by making x sufficiently close to 1.
In other words,
This can also be calculated algebraically, as for all real numbers x ≠ 1.
Now since x + 1 is continuous in x at 1, we can now plug in 1 for x, thus .
In addition to limits at finite values, functions can also have limits at infinity. For example, consider
- f(100) = 1.9900
- f(1000) = 1.9990
- f(10000) = 1.99990
As x becomes extremely large, the value of f(x) approaches 2, and the value of f(x) can be made as close to 2 as one could wish just by picking x sufficiently large. In this case, the limit of f(x) as x approaches infinity is 2. In mathematical notation,
Limit of a sequence
Consider the following sequence: 1.79, 1.799, 1.7999,... It can be observed that the numbers are "approaching" 1.8, the limit of the sequence.
Formally, suppose a_{1}, a_{2}, ... is a sequence of real numbers. It can be stated that the real number L is the limit of this sequence, namely:
which is read as
- "The limit of a_{n} as n approaches infinity equals L"
to mean
- For every real number ε > 0, there exists a natural number N such that for all n > N, we have |a_{n} − L| < ε.
Intuitively, this means that eventually all elements of the sequence get arbitrarily close to the limit, since the absolute value |a_{n} − L| is the distance between a_{n} and L. Not every sequence has a limit; if it does, it is called convergent, and if it does not, it is divergent. One can show that a convergent sequence has only one limit.
The limit of a sequence and the limit of a function are closely related. On one hand, the limit as n goes to infinity of a sequence a(n) is simply the limit at infinity of a function defined on the natural numbers n. On the other hand, a limit L of a function f(x) as x goes to infinity, if it exists, is the same as the limit of any arbitrary sequence a_{n} that approaches L, and where a_{n} is never equal to L. One such sequence would be L + 1/n.
Limit as "standard part"
In non-standard analysis (which involves a hyperreal enlargement of the number system), the limit of a sequence can be expressed as the standard part of the value of the natural extension of the sequence at an infinite hypernatural index n=H. Thus,
- .
Here the standard part function "st" rounds off each finite hyperreal number to the nearest real number (the difference between them is infinitesimal). This formalizes the natural intuition that for "very large" values of the index, the terms in the sequence are "very close" to the limit value of the sequence. Conversely, the standard part of a hyperreal represented in the ultrapower construction by a Cauchy sequence , is simply the limit of that sequence:
- .
In this sense, taking the limit and taking the standard part are equivalent procedures.
Convergence and fixed point
A formal definition of convergence can be stated as follows. Suppose as goes from to is a sequence that converges to , with for all . If positive constants and exist with
then as goes from to converges to of order , with asymptotic error constant
Given a function with a fixed point , there is a nice checklist for checking the convergence of the sequence .
- 1) First check that p is indeed a fixed point:
- 2) Check for linear convergence. Start by finding . If....
then there is linear convergence | |
series diverges | |
then there is at least linear convergence and maybe something better, the expression should be checked for quadratic convergence |
- 3) If it is found that there is something better than linear the expression should be checked for quadratic convergence. Start by finding If....
then there is quadratic convergence provided that is continuous | |
then there is something even better than quadratic convergence | |
does not exist | then there is convergence that is better than linear but still not quadratic |
^{[3]}
Computability of the limit
Limits can be difficult to compute. There exists limit expressions whose modulus of convergence is undecidable. In recursion theory, the Limit lemma proves that it is possible to encode undecidable problems using limits.^{[4]}
In topology
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In spaces without a metric
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Limits of sequences can be defined in arbitrary topological spaces, even if the spaces are not metric spaces. In an arbitrary topological space a point is called a limit of the sequence of points in if for every open set containing there exists an index such that if then is contained in that open set. In general topological spaces, unlike for the case of real numbers above, sequences can have more than one limit.
Nets and filters
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Sequences in topological spaces can be generalized to the concepts of nets, along with a corresponding notion of a limit. A related notion, that of filters on topological spaces, also can have limits defined for them.
See also
The Wikibook Calculus has a page on the topic of: Limits |
- Rate of convergence: the rate at which a convergent sequence approaches its limit
- Cauchy sequence
- Limit of a function
- One-sided limit: either of the two limits of functions of a real variable x, as x approaches a point from above or below
- List of limits: list of limits for common functions
- Squeeze theorem: finds a limit of a function via comparison with two other functions
- Modes of convergence
- Convergence of random variables
- Banach limit defined on the Banach space that extends the usual limits.
- Limit in category theory
- Asymptotic analysis: a method of describing limiting behavior
- Big O notation: used to describe the limiting behavior of a function when the argument tends towards a particular value or infinity
- Convergent matrix
Notes
- ^ Stewart, James (2008). Calculus: Early Transcendentals (6th ed.). Brooks/Cole. ISBN 978-0-495-01166-8.
- ^ ^{a} ^{b} ^{c} Larson, Ron; Edwards, Bruce H. (2010). Calculus of a single variable (Ninth ed.). Brooks/Cole, Cengage Learning. ISBN 978-0-547-20998-2.
- ^ Numerical Analysis, 8th Edition, Burden and Faires, Section 2.4 Error Analysis for Iterative Methods
- ^ Recursively enumerable sets and degrees, Soare, Robert I.