# Dominated convergence theorem

In measure theory, Lebesgue's **dominated convergence theorem** provides sufficient conditions under which almost everywhere convergence of a sequence of functions implies convergence in the *L*^{1} norm. Its power and utility are two of the primary theoretical advantages of Lebesgue integration over Riemann integration.

It is widely used in probability theory, since it gives a sufficient condition for the convergence of expected values of random variables.

## Statement of the theorem

**Lebesgue's Dominated Convergence Theorem.** Let {*f _{n}*} be a sequence of real-valued measurable functions on a measure space (

*S*, Σ, μ). Suppose that the sequence converges pointwise to a function

*f*and is dominated by some integrable function

*g*in the sense that

for all numbers *n* in the index set of the sequence and all points *x* ∈ *S*.
Then *f* is integrable and

which also implies

**Remark 1.** The statement "*g* is integrable" is meant in the sense of Lebesgue; that is

**Remark 2.** The convergence of the sequence and domination by *g* can be relaxed to hold only μ-almost everywhere provided the measure space (*S*, Σ, μ) is complete or *f* is chosen as a measurable function which agrees μ-almost everywhere with the μ-almost everywhere existing pointwise limit. (These precautions are necessary, because otherwise there might exist a non-measurable subset of a μ-null set *N* ∈ Σ, hence *f* might not be measurable.)

**Remark 3.** If μ(*S*) < ∞, the condition that there is a dominating integrable function *g* can be relaxed to uniform integrability of the sequence {*f _{n}*}, see Vitali convergence theorem.

## Proof of the theorem

Lebesgue's dominated convergence theorem is a special case of the Fatou–Lebesgue theorem. Below, however, is a direct proof that uses Fatou’s lemma as the essential tool.

Since *f* is the pointwise limit of the sequence *(f _{n})* of measurable functions that are dominated by

*g*, it is also measurable and dominated by

*g*, hence it is integrable. Furthermore (these will be needed later),

for all *n* and

The second of these is trivially true (by the very definition of *f*). Using linearity and monotonicity of the Lebesgue integral,

By the reverse Fatou lemma (it is here that we use the fact that |*f*−*f _{n}*| is bounded above by an integrable function)

which implies that the limit exists and vanishes i.e.

Finally, since

we have that

The theorem now follows.

If the assumptions hold only μ-almost everywhere, then there exists a μ-null set *N* ∈ Σ such that the functions *f _{n}*

**1**

_{N}satisfy the assumptions everywhere on

*S*. Then

*f*(

*x*) is the pointwise limit of

*f*(

_{n}*x*) for

*x*∈

*S*\

*N*and

*f*(

*x*) = 0 for

*x*∈

*N*, hence

*f*is measurable. The values of the integrals are not influenced by this μ-null set

*N*.

DCT holds even if f_{n} converges to f in measure (finite measure) and the dominating function is non-negative almost everywhere.

## Discussion of the assumptions

The assumption that the sequence is dominated by some integrable *g* cannot be dispensed with. This may be seen as follows: define *f _{n}*(

*x*) =

*n*for

*x*in the interval (0, 1/

*n*] and

*f*

_{n}(

*x*) = 0 otherwise. Any

*g*which dominates the sequence must also dominate the pointwise supremum

*h*= sup

_{n}

*f*. Observe that

_{n}by the divergence of the harmonic series. Hence, the monotonicity of the Lebesgue integral tells us that there exists no integrable function which dominates the sequence on [0,1]. A direct calculation shows that integration and pointwise limit do not commute for this sequence:

because the pointwise limit of the sequence is the zero function. Note that the sequence {*f _{n}*} is not even uniformly integrable, hence also the Vitali convergence theorem is not applicable.

## Bounded convergence theorem

One corollary to the dominated convergence theorem is the **bounded convergence theorem**, which states that if {*f _{n}*} is a sequence of uniformly bounded real-valued measurable functions which converges pointwise on a bounded measure space (

*S*, Σ, μ) (i.e. one in which μ(

*S*) is finite) to a function

*f*, then the limit

*f*is an integrable function and

**Remark:** The pointwise convergence and uniform boundedness of the sequence can be relaxed to hold only μ-almost everywhere, provided the measure space (*S*, Σ, μ) is complete or *f* is chosen as a measurable function which agrees μ-almost everywhere with the μ-almost everywhere existing pointwise limit.

### Proof

Since the sequence is uniformly bounded, there is a real number *M* such that |*f _{n}*(

*x*)| ≤

*M*for all

*x*∈

*S*and for all

*n*. Define

*g*(

*x*) =

*M*for all

*x*∈

*S*. Then the sequence is dominated by

*g*. Furthermore,

*g*is integrable since it is a constant function on a set of finite measure. Therefore the result follows from the dominated convergence theorem.

If the assumptions hold only μ-almost everywhere, then there exists a μ-null set *N* ∈ Σ such that the functions *f _{n}*

**1**

_{N}satisfy the assumptions everywhere on

*S*.

## Dominated convergence in *L*^{p}-spaces (corollary)

Let be a measure space, 1 ≤ *p* < ∞ a real number and {*f _{n}*} a sequence of -measurable functions .

Assume the sequence {*f _{n}*} converges μ-almost everywhere to an -measurable function

*f*, and is dominated by a , i.e., for every natural number

*n*we have: |

*f*| ≤

_{n}*g*, μ-almost everywhere.

Then all *f _{n}* as well as

*f*are in and the sequence {

*f*} converges to

_{n}*f*in the sense of , i.e.:

Idea of the proof: Apply the original theorem to the function sequence with the dominating function .

## Extensions

The dominated convergence theorem applies also to measurable functions with values in a Banach space, with the dominating function still being non-negative and integrable as above. The assumption of convergence almost everywhere can be weakened to require only convergence in measure.

## See also

- Convergence of random variables, Convergence in mean
- Monotone convergence theorem (does not require domination by an integrable function but assumes monotonicity of the sequence instead)
- Scheffé’s lemma
- Uniform integrability
- Vitali convergence theorem (a generalization of Lebesgue's dominated convergence theorem)

## References

- Bartle, R.G. (1995).
*The Elements of Integration and Lebesgue Measure*. Wiley Interscience. - Royden, H.L. (1988).
*Real Analysis*. Prentice Hall. - Williams, D. (1991).
*Probability with martingales*. Cambridge University Press. ISBN 0-521-40605-6.