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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 ...
, an infinite series of numbers is said to converge absolutely (or to be absolutely convergent) if the sum of the
absolute value In mathematics, the absolute value or modulus of a real number x, is the non-negative value without regard to its sign. Namely, , x, =x if is a positive number, and , x, =-x if x is negative (in which case negating x makes -x positive), an ...
s of the summands is finite. More precisely, a real or complex series \textstyle\sum_^\infty a_n is said to converge absolutely if \textstyle\sum_^\infty \left, a_n\ = L for some real number \textstyle L. Similarly, an improper integral of a function, \textstyle\int_0^\infty f(x)\,dx, is said to converge absolutely if the integral of the absolute value of the integrand is finite—that is, if \textstyle\int_0^\infty , f(x), dx = L. Absolute convergence is important for the study of infinite series because its definition is strong enough to have properties of finite sums that not all convergent series possess - a convergent series that is not absolutely convergent is called conditionally convergent, while absolutely convergent series behave "nicely". For instance, rearrangements do not change the value of the sum. This is not true for conditionally convergent series: The alternating harmonic series 1-\frac+\frac-\frac+\frac-\frac+\cdots converges to \ln 2, while its rearrangement 1+\frac-\frac+\frac+\frac-\frac+\cdots (in which the repeating pattern of signs is two positive terms followed by one negative term) converges to \frac\ln 2.


Background

In finite sums, the order in which terms are added does not matter. 1 + 2 + 3 is the same as 3 + 2 + 1. However, this is not true when adding infinitely many numbers, and wrongly assuming that it is true can lead to apparent paradoxes. One classic example is the alternating sum S = 1 - 1 + 1 - 1 + 1 - 1... whose terms alternate between +1 and -1. What is the value of S? One way to evaluate S is to group the first and second term, the third and fourth, and so on: S_1 = (1 - 1) + (1 - 1) + (1 - 1).... = 0 + 0 + 0 ... = 0 But another way to evaluate S is to leave the first term alone and group the second and third term, then the fourth and fifth term, and so on: S_2 = 1 + (-1 + 1) + (-1 + 1) + (-1 + 1).... = 1 + 0 + 0 + 0 ... = 1 This leads to an apparent paradox: does S = 0 or S = 1 ? The answer is that because S is not absolutely convergent, rearranging its terms changes the value of the sum. This means S_1 and S_2 are not equal. In fact, the series 1 - 1 + 1 - 1 + ... does not converge, so S does not have a value to find in the first place. A series that is absolutely convergent does not have this problem: rearranging its terms does not change the value of the sum.


Definition for real and complex numbers

A sum of real numbers or complex numbers \sum_^ a_n is absolutely convergent if the sum of the absolute values of the terms \sum_^ , a_n, converges.


Sums of more general elements

The same definition can be used for series \sum_^ a_n whose terms a_n are not numbers but rather elements of an arbitrary
abelian topological group Abelian may refer to: Mathematics Group theory * Abelian group, a group in which the binary operation is commutative ** Category of abelian groups (Ab), has abelian groups as objects and group homomorphisms as morphisms * Metabelian group, a gro ...
. In that case, instead of using the
absolute value In mathematics, the absolute value or modulus of a real number x, is the non-negative value without regard to its sign. Namely, , x, =x if is a positive number, and , x, =-x if x is negative (in which case negating x makes -x positive), an ...
, the definition requires the group to have a
norm Naturally occurring radioactive materials (NORM) and technologically enhanced naturally occurring radioactive materials (TENORM) consist of materials, usually industrial wastes or by-products enriched with radioactive elements found in the envir ...
, which is a positive real-valued function \, \cdot\, : G \to \R_+ on an abelian group G (written additively, with identity element 0) such that: # The norm of the identity element of G is zero: \, 0\, = 0. # For every x \in G, \, x\, = 0 implies x = 0. # For every x \in G, \, -x\, = \, x\, . # For every x, y \in G, \, x+y\, \leq \, x\, + \, y\, . In this case, the function d(x,y) = \, x-y\, induces the structure of a metric space (a type of topology) on G. Then, a G-valued series is absolutely convergent if \sum_^ \, a_n\, < \infty. In particular, these statements apply using the norm , x, (
absolute value In mathematics, the absolute value or modulus of a real number x, is the non-negative value without regard to its sign. Namely, , x, =x if is a positive number, and , x, =-x if x is negative (in which case negating x makes -x positive), an ...
) in the space of real numbers or complex numbers.


In topological vector spaces

If X is a topological vector space (TVS) and \left(x_\alpha\right)_ is a (possibly uncountable) family in X then this family is absolutely summable if # \left(x_\alpha\right)_ is summable in X (that is, if the limit \lim_ x_H of the net \left(x_H\right)_ converges in X, where \mathcal(A) is the directed set of all finite subsets of A directed by inclusion \subseteq and x_H := \sum_ x_i), and # for every continuous seminorm p on X, the family \left(p \left(x_\alpha\right)\right)_ is summable in \R. If X is a normable space and if \left(x_\alpha\right)_ is an absolutely summable family in X, then necessarily all but a countable collection of x_\alpha's are 0. Absolutely summable families play an important role in the theory of nuclear spaces.


Relation to convergence

If G is
complete Complete may refer to: Logic * Completeness (logic) * Completeness of a theory, the property of a theory that every formula in the theory's language or its negation is provable Mathematics * The completeness of the real numbers, which implies t ...
with respect to the metric d, then every absolutely convergent series is convergent. The proof is the same as for complex-valued series: use the completeness to derive the Cauchy criterion for convergence—a series is convergent if and only if its tails can be made arbitrarily small in norm—and apply the triangle inequality. In particular, for series with values in any
Banach space In mathematics, more specifically in functional analysis, a Banach space (pronounced ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vector ...
, absolute convergence implies convergence. The converse is also true: if absolute convergence implies convergence in a normed space, then the space is a Banach space. If a series is convergent but not absolutely convergent, it is called conditionally convergent. An example of a conditionally convergent series is the alternating harmonic series. Many standard tests for divergence and convergence, most notably including the ratio test and the root test, demonstrate absolute convergence. This is because a power series is absolutely convergent on the interior of its disk of convergence.


Proof that any absolutely convergent series of complex numbers is convergent

Suppose that \sum \left, a_k\, a_k \in \Complex is convergent. Then equivalently, \sum \left \operatorname\left(a_k\right)^2 + \operatorname\left(a_k\right)^2 \right is convergent, which implies that \sum \left, \operatorname\left(a_k\right)\ and \sum\left, \operatorname\left(a_k\right)\ converge by termwise comparison of non-negative terms. It suffices to show that the convergence of these series implies the convergence of \sum \operatorname\left(a_k\right) and \sum \operatorname\left(a_k\right), for then, the convergence of \sum a_k=\sum \operatorname\left(a_k\right) + i \sum \operatorname\left(a_k\right) would follow, by the definition of the convergence of complex-valued series. The preceding discussion shows that we need only prove that convergence of \sum \left, a_k\, a_k\in\R implies the convergence of \sum a_k. Let \sum \left, a_k\, a_k\in\R be convergent. Since 0 \leq a_k + \left, a_k\ \leq 2\left, a_k\, we have 0 \leq \sum_^n (a_k + \left, a_k\) \leq \sum_^n 2\left, a_k\. Since \sum 2\left, a_k\ is convergent, s_n=\sum_^n \left(a_k + \left, a_k\\right) is a
bounded Boundedness or bounded may refer to: Economics * Bounded rationality, the idea that human rationality in decision-making is bounded by the available information, the cognitive limitations, and the time available to make the decision * Bounded e ...
monotonic sequence of partial sums, and \sum \left(a_k + \left, a_k\\right) must also converge. Noting that \sum a_k = \sum \left(a_k + \left, a_k\\right) - \sum \left, a_k\ is the difference of convergent series, we conclude that it too is a convergent series, as desired.


Alternative proof using the Cauchy criterion and triangle inequality

By applying the Cauchy criterion for the convergence of a complex series, we can also prove this fact as a simple implication of the triangle inequality. By the
Cauchy criterion The Cauchy convergence test is a method used to test infinite series for convergence. It relies on bounding sums of terms in the series. This convergence criterion is named after Augustin-Louis Cauchy who published it in his textbook Cours d'Anal ...
, \sum , a_i, converges if and only if for any \varepsilon > 0, there exists N such that \left, \sum_^n \left, a_i\ \ = \sum_^n , a_i, < \varepsilon for any n > m \geq N. But the triangle inequality implies that \big, \sum_^n a_i\big, \leq \sum_^n , a_i, , so that \left, \sum_^n a_i\ < \varepsilon for any n > m \geq N, which is exactly the Cauchy criterion for \sum a_i.


Proof that any absolutely convergent series in a Banach space is convergent

The above result can be easily generalized to every
Banach space In mathematics, more specifically in functional analysis, a Banach space (pronounced ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vector ...
(X, \, \,\cdot\,\, ). Let \sum x_n be an absolutely convergent series in X. As \sum_^n\, x_k\, is a Cauchy sequence of real numbers, for any \varepsilon > 0 and large enough natural numbers m > n it holds: \left, \sum_^m \, x_k\, - \sum_^n \, x_k\, \ = \sum_^m \, x_k\, < \varepsilon. By the triangle inequality for the norm , one immediately gets: \left\, \sum_^m x_k - \sum_^n x_k\right\, = \left\, \sum_^m x_k\right\, \leq \sum_^m \, x_k\, < \varepsilon, which means that \sum_^n x_k is a Cauchy sequence in X, hence the series is convergent in X.


Rearrangements and unconditional convergence


Real and complex numbers

When a series of real or complex numbers is absolutely convergent, any rearrangement or reordering of that series' terms will still converge to the same value. This fact is one reason absolutely convergent series are useful: showing a series is absolutely convergent allows terms to be paired or rearranged in convenient ways without changing the sum's value. The Riemann rearrangement theorem shows that the converse is also true: every real or complex-valued series whose terms cannot be reordered to give a different value is absolutely convergent.


Series with coefficients in more general space

The term unconditional convergence is used to refer to a series where any rearrangement of its terms still converges to the same value. For any series with values in a normed abelian group G, as long as G is complete, every series which converges absolutely also converges unconditionally. Stated more formally: For series with more general coefficients, the converse is more complicated. As stated in the previous section, for real-valued and complex-valued series, unconditional convergence always implies absolute convergence. However, in the more general case of a series with values in any normed abelian group G, the converse does not always hold: there can exist series which are not absolutely convergent, yet unconditionally convergent. For example, in the
Banach space In mathematics, more specifically in functional analysis, a Banach space (pronounced ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vector ...
, one series which is unconditionally convergent but not absolutely convergent is: \sum_^\infty \tfrac e_n, where \_^ is an orthonormal basis. A theorem of A. Dvoretzky and C. A. Rogers asserts that every infinite-dimensional Banach space has an unconditionally convergent series that is not absolutely convergent.


Proof of the theorem

For any \varepsilon > 0, we can choose some \kappa_\varepsilon, \lambda_\varepsilon \in \N, such that: \begin \text N > \kappa_\varepsilon &\quad \sum_^\infty \, a_n\, < \tfrac \\ \text N > \lambda_\varepsilon &\quad \left\, \sum_^N a_n - A\right\, < \tfrac \end Let \begin N_\varepsilon &=\max \left\ \\ M_ &= \max \left\ \end where \sigma^\left(\left\\right) = \left\ so that M_ is the smallest natural number such that the list a_, \ldots, a_ includes all of the terms a_0, \ldots, a_ (and possibly others). Finally for any integer N > M_ let \begin I_ &= \left\\setminus \sigma^\left(\left \\right) \\ S_ &= \min \sigma\left(I_\right) = \min \left\ \\ L_ &= \max \sigma\left(I_\right) = \max \left\ \\ \end so that \begin \left\, \sum_ a_\right\, &\leq \sum_ \left\, a_\right\, \\ &\leq \sum_^ \left\, a_j\right\, && \text I_ \subseteq \left\ \\ &\leq \sum_^ \left\, a_j\right\, && \text S_ \geq N_ + 1 \\ &< \frac \end and thus \begin \left\, \sum_^N a_-A \right\, &= \left\, \sum_ a_ - A + \sum_ a_ \right\, \\ &\leq \left\, \sum_^ a_j - A \right\, + \left\, \sum_ a_ \right\, \\ &< \left\, \sum_^ a_j - A \right\, + \frac\\ &< \varepsilon \end This shows that \text \varepsilon > 0, \text M_, \text N > M_ \quad \left\, \sum_^N a_ - A\right\, < \varepsilon, that is: \sum_^\infty a_ = A.
Q.E.D. Q.E.D. or QED is an initialism of the Latin phrase , meaning "which was to be demonstrated". Literally it states "what was to be shown". Traditionally, the abbreviation is placed at the end of mathematical proofs and philosophical arguments in pri ...


Products of series

The Cauchy product of two series converges to the product of the sums if at least one of the series converges absolutely. That is, suppose that \sum_^\infty a_n = A \quad \text \quad \sum_^\infty b_n = B. The Cauchy product is defined as the sum of terms c_n where: c_n = \sum_^n a_k b_. If the a_n or b_n sum converges absolutely then \sum_^\infty c_n = A B.


Absolute convergence over sets

A generalization of the absolute convergence of a series, is the absolute convergence of a sum of a function over a set. We can first consider a countable set X and a function f : X \to \R. We will give a definition below of the sum of f over X, written as \sum_ f(x). First note that because no particular enumeration (or "indexing") of X has yet been specified, the series \sum_f(x) cannot be understood by the more basic definition of a series. In fact, for certain examples of X and f, the sum of f over X may not be defined at all, since some indexing may produce a conditionally convergent series. Therefore we define \sum_ f(x) only in the case where there exists some bijection g : \Z^+ \to X such that \sum_^\infty f(g(n)) is absolutely convergent. Note that here, "absolutely convergent" uses the more basic definition, applied to an indexed series. In this case, the value of the sum of f over X is defined by \sum_f(x) := \sum_^\infty f(g(n)) Note that because the series is absolutely convergent, then every rearrangement is identical to a different choice of bijection g. Since all of these sums have the same value, then the sum of f over X is well-defined. Even more generally we may define the sum of f over X when X is uncountable. But first we define what it means for the sum to be convergent. Let X be any set, countable or uncountable, and f : X \to \R a function. We say that the sum of f over X converges absolutely if \sup\left\ < \infty. There is a theorem which states that, if the sum of f over X is absolutely convergent, then f takes non-zero values on a set that is at most countable. Therefore, the following is a consistent definition of the sum of f over X when the sum is absolutely convergent. \sum_ f(x) := \sum_ f(x). Note that the final series uses the definition of a series over a countable set. Some authors define an iterated sum \sum_^\infty \sum_^\infty a_ to be absolutely convergent if the iterated series \sum_^\infty \sum_^\infty , a_, < \infty. This is in fact equivalent to the absolute convergence of \sum_ a_. That is to say, if the sum of f over X, \sum_ a_, converges absolutely, as defined above, then the iterated sum \sum_^\infty \sum_^\infty a_ converges absolutely, and vice versa.


Absolute convergence of integrals

The integral \int_A f(x)\,dx of a real or complex-valued function is said to converge absolutely if \int_A \left, f(x)\\,dx < \infty. One also says that f is absolutely integrable. The issue of absolute integrability is intricate and depends on whether the Riemann,
Lebesgue Henri Léon Lebesgue (; June 28, 1875 – July 26, 1941) was a French mathematician known for his theory of integration, which was a generalization of the 17th-century concept of integration—summing the area between an axis and the curve of ...
, or Kurzweil-Henstock (gauge) integral is considered; for the Riemann integral, it also depends on whether we only consider integrability in its proper sense (f and A both
bounded Boundedness or bounded may refer to: Economics * Bounded rationality, the idea that human rationality in decision-making is bounded by the available information, the cognitive limitations, and the time available to make the decision * Bounded e ...
), or permit the more general case of improper integrals. As a standard property of the Riemann integral, when A= ,b/math> is a bounded interval, every
continuous function In mathematics, a continuous function is a function such that a continuous variation (that is a change without jump) of the argument induces a continuous variation of the value of the function. This means that there are no abrupt changes in value ...
is bounded and (Riemann) integrable, and since f continuous implies , f, continuous, every continuous function is absolutely integrable. In fact, since g\circ f is Riemann integrable on ,b/math> if f is (properly) integrable and g is continuous, it follows that , f, =, \cdot, \circ f is properly Riemann integrable if f is. However, this implication does not hold in the case of improper integrals. For instance, the function f:[1,\infty) \to \R : x \mapsto \frac is improperly Riemann integrable on its unbounded domain, but it is not absolutely integrable: \int_1^\infty \frac\,dx = \frac\bigl[\pi - 2\,\mathrm(1)\bigr] \approx 0.62, \text \int_1^\infty \left, \frac\ dx = \infty. Indeed, more generally, given any series \sum_^\infty a_n one can consider the associated step function f_a: [0,\infty) \to \R defined by f_a([n,n+1)) = a_n. Then \int_0^\infty f_a \, dx converges absolutely, converges conditionally or diverges according to the corresponding behavior of \sum_^\infty a_n. The situation is different for the Lebesgue integral, which does not handle bounded and unbounded domains of integration separately (''see below''). The fact that the integral of , f, is unbounded in the examples above implies that f is also not integrable in the Lebesgue sense. In fact, in the Lebesgue theory of integration, given that f is Measurable function, measurable, f is (Lebesgue) integrable if and only if , f, is (Lebesgue) integrable. However, the hypothesis that f is measurable is crucial; it is not generally true that absolutely integrable functions on ,b/math> are integrable (simply because they may fail to be measurable): let S \subset ,b/math> be a nonmeasurable
subset In mathematics, Set (mathematics), set ''A'' is a subset of a set ''B'' if all Element (mathematics), elements of ''A'' are also elements of ''B''; ''B'' is then a superset of ''A''. It is possible for ''A'' and ''B'' to be equal; if they are ...
and consider f = \chi_S - 1/2, where \chi_S is the characteristic function of S. Then f is not Lebesgue measurable and thus not integrable, but , f, \equiv 1/2 is a constant function and clearly integrable. On the other hand, a function f may be Kurzweil-Henstock integrable (gauge integrable) while , f, is not. This includes the case of improperly Riemann integrable functions. In a general sense, on any
measure space A measure space is a basic object of measure theory, a branch of mathematics that studies generalized notions of volumes. It contains an underlying set, the subsets of this set that are feasible for measuring (the -algebra) and the method that i ...
A, the Lebesgue integral of a real-valued function is defined in terms of its positive and negative parts, so the facts: # f integrable implies , f, integrable # f measurable, , f, integrable implies f integrable are essentially built into the definition of the Lebesgue integral. In particular, applying the theory to the counting measure on a
set Set, The Set, SET or SETS may refer to: Science, technology, and mathematics Mathematics *Set (mathematics), a collection of elements *Category of sets, the category whose objects and morphisms are sets and total functions, respectively Electro ...
S, one recovers the notion of unordered summation of series developed by Moore–Smith using (what are now called) nets. When S = \N is the set of natural numbers, Lebesgue integrability, unordered summability and absolute convergence all coincide. Finally, all of the above holds for integrals with values in a Banach space. The definition of a Banach-valued Riemann integral is an evident modification of the usual one. For the Lebesgue integral one needs to circumvent the decomposition into positive and negative parts with Daniell's more functional analytic approach, obtaining the Bochner integral.


See also

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Notes


References


Works cited

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General references

* * Walter Rudin, ''Principles of Mathematical Analysis'' (McGraw-Hill: New York, 1964). * * * * * {{Authority control Mathematical series Integral calculus Summability theory Convergence (mathematics)