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In mathematics, an infinite series of numbers is said to **converge absolutely** (or to be **absolutely convergent**) if the sum of the absolute values of the summands is finite. More precisely, a real or complex series is said to **converge absolutely** if for some real number Similarly, an improper integral of a function, is said to converge absolutely if the integral of the absolute value of the integrand is finite—that is, if

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 converges to while its rearrangement (in which the repeating pattern of signs is two positive terms followed by one negative term) converges to

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

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:

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:

This leads to an apparent paradox: does or ?

The answer is that because S is not absolutely convergent, rearranging its terms changes the value of the sum. This means and are not equal. In fact, the series 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.

This is an example of a mathematical sleight of hand. If the terms of S are rearranged in such a way that every term remains in its original position, one finds that S is either the infinite series

or with equal possibility, that

Evaluating S as before, by grouping every -1 with the +1 preceding it or by grouping every +1 except the first with the -1 preceding it, gives in the first case:

and in the second case:

This reveals the trick: the definition of S was interpreted as defining its last term as negative when evaluating but positive when evaluating when in fact the definition of S didn't define (and the rearrangement was independent of) either option.

A sum of real numbers or complex numbers is absolutely convergent if the sum of the absolute values of the terms converges.

The same definition can be used for series whose terms are not numbers but rather elements of an arbitrary abelian topological group. In that case, instead of using the absolute value, the definition requires the group to have a norm, which is a positive real-valued function on an abelian group (written additively, with identity element 0) such that:

- The norm of the identity element of is zero:
- For every implies
- For every
- For every

In this case, the function induces the structure of a metric space (a type of topology) on

Then, a -valued series is absolutely convergent if

In particular, these statements apply using the norm (absolute value) in the space of real numbers or complex numbers.

If is a topological vector space (TVS) and is a (possibly uncountable) family in then this family is **absolutely summable** if^{[1]}

- is
**summable**in (that is, if the limit of the net converges in where is the directed set of all finite subsets of directed by inclusion and ), and - for every continuous seminorm on the family is summable in

If is a normable space and if is an absolutely summable family in then necessarily all but a countable collection of 's are 0.

Absolutely summable families play an important role in the theory of nuclear spaces.

If is complete with respect to the metric 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, 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.^{[a]}

Suppose that is convergent. Then equivalently, is convergent, which implies that and converge by termwise comparison of non-negative terms. It suffices to show that the convergence of these series implies the convergence of and for then, the convergence of would follow, by the definition of the convergence of complex-valued series.

The preceding discussion shows that we need only prove that convergence of implies the convergence of

Let be convergent. Since we have

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.^{[2]} By the Cauchy criterion, converges if and only if for any there exists such that for any But the triangle inequality implies that so that for any which is exactly the Cauchy criterion for

The above result can be easily generalized to every Banach space Let be an absolutely convergent series in As is a Cauchy sequence of real numbers, for any and large enough natural numbers it holds:

By the triangle inequality for the norm ǁ⋅ǁ, one immediately gets:

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.

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 , as long as is complete, every series which converges absolutely also converges unconditionally.

Stated more formally:

**Theorem** — Let be a normed abelian group. Suppose

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 , the converse does not always hold: there can exist series which are not absolutely convergent, yet unconditionally convergent.

For example, in the Banach space ℓ^{∞}, one series which is unconditionally convergent but not absolutely convergent is:

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.^{[4]}

For any we can choose some such that:

Let

Finally for any integer let

Then

This shows that

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

The Cauchy product is defined as the sum of terms where:

If *either* the or sum converges absolutely then

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 and a function We will give a definition below of the sum of over written as

First note that because no particular enumeration (or "indexing") of has yet been specified, the series cannot be understood by the more basic definition of a series. In fact, for certain examples of and the sum of over may not be defined at all, since some indexing may produce a conditionally convergent series.

Therefore we define only in the case where there exists some bijection such that 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 over **^{[5]} is defined by

Note that because the series is absolutely convergent, then every rearrangement is identical to a different choice of bijection Since all of these sums have the same value, then the sum of over is well-defined.

Even more generally we may define the sum of over when is uncountable. But first we define what it means for the sum to be convergent.

Let be any set, countable or uncountable, and a function. We say that **the sum of over converges absolutely** if

There is a theorem which states that, if the sum of over is absolutely convergent, then takes non-zero values on a set that is at most countable. Therefore, the following is a consistent definition of the sum of over when the sum is absolutely convergent.

Note that the final series uses the definition of a series over a countable set.

Some authors define an iterated sum to be absolutely convergent if the iterated series ^{[6]} This is in fact equivalent to the absolute convergence of That is to say, if the sum of over converges absolutely, as defined above, then the iterated sum converges absolutely, and vice versa.

The integral of a real or complex-valued function is said to **converge absolutely** if One also says that is **absolutely integrable**. The issue of absolute integrability is intricate and depends on whether the Riemann, Lebesgue, or Kurzweil-Henstock (gauge) integral is considered; for the Riemann integral, it also depends on whether we only consider integrability in its proper sense ( and both bounded), or permit the more general case of improper integrals.

As a standard property of the Riemann integral, when is a bounded interval, every continuous function is bounded and (Riemann) integrable, and since continuous implies continuous, every continuous function is absolutely integrable. In fact, since is Riemann integrable on if is (properly) integrable and is continuous, it follows that is properly Riemann integrable if is. However, this implication does not hold in the case of improper integrals. For instance, the function is improperly Riemann integrable on its unbounded domain, but it is not absolutely integrable:

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 is unbounded in the examples above implies that is also not integrable in the Lebesgue sense. In fact, in the Lebesgue theory of integration, given that is measurable, is (Lebesgue) integrable if and only if is (Lebesgue) integrable. However, the hypothesis that is measurable is crucial; it is not generally true that absolutely integrable functions on are integrable (simply because they may fail to be measurable): let be a nonmeasurable subset and consider where is the characteristic function of Then is not Lebesgue measurable and thus not integrable, but is a constant function and clearly integrable.

On the other hand, a function may be Kurzweil-Henstock integrable (gauge integrable) while is not. This includes the case of improperly Riemann integrable functions.

In a general sense, on any measure space the Lebesgue integral of a real-valued function is defined in terms of its positive and negative parts, so the facts:

- integrable implies integrable
- measurable, integrable implies integrable

are essentially built into the definition of the Lebesgue integral. In particular, applying the theory to the counting measure on a set one recovers the notion of unordered summation of series developed by Moore–Smith using (what are now called) nets. When 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.

- Cauchy principal value – Method for assigning values to certain improper integrals which would otherwise be undefined
- Conditional convergence
- Convergence of Fourier series
- Fubini's theorem – Conditions for switching order of integration in calculus
- Modes of convergence (annotated index) – An annotated index of various modes of convergence
- Radius of convergence – Domain of convergence of power series
- Riemann series theorem – Unconditional series converge absolutely
- Unconditional convergence
- 1/2 − 1/4 + 1/8 − 1/16 + · · ·
- 1/2 + 1/4 + 1/8 + 1/16 + · · ·

**^**Here, the disk of convergence is used to refer to all points whose distance from the center of the series is less than the radius of convergence. That is, the disk of convergence is made up of all points for which the power series converges.

**^**Schaefer & Wolff 1999, pp. 179–180.**^**Rudin, Walter (1976).*Principles of Mathematical Analysis*. New York: McGraw-Hill. pp. 71–72. ISBN 0-07-054235-X.**^**Megginson, Robert E. (1998),*An introduction to Banach space theory*, Graduate Texts in Mathematics, vol. 183, New York: Springer-Verlag, p. 20, ISBN 0-387-98431-3 (Theorem 1.3.9)**^**Dvoretzky, A.; Rogers, C. A. (1950), "Absolute and unconditional convergence in normed linear spaces", Proc. Natl. Acad. Sci. U.S.A.**36**:192–197.**^**Tao, Terrance (2016).*Analysis I*. New Delhi: Hindustan Book Agency. pp. 188–191. ISBN 978-9380250649.**^**Strichartz, Robert (2000).*The Way of Analysis*. Jones & Bartlett Learning. pp. 259, 260. ISBN 978-0763714970.

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