2.3. Sequences and SeriesΒΆ

This section collects results on sequences and series of real numbers.

Definition 2.28

A sequence of real numbers is a function f:N→R.

A sequence can be thought of as an ordered (countable) list of real numbers.

Definition 2.29 (Convergence)

A sequence {xn} of real numbers is said to converge to x∈R if for every ϡ>0, there exists a natural number n0 (depending upon ϡ) such that

|xnβˆ’x|<Ο΅βˆ€n>n0.

The real number x is called the limit of the sequence {xn}, and we write xnβ†’x or x=limnβ†’βˆžxn.

In other words, a sequence of real numbers {xn} converges to some real number x if and only if for each Ο΅>0, the terms xn are eventually Ο΅-close to x.

Example 2.6 (Sequence convergence)

Consider the sequence {xn}, where xn=1n. For a given Ο΅>0, choose n0>1Ο΅2. Then, for every n>n0, we have

|1n2βˆ’0|=1n2<Ο΅.

Thus, the sequence converges to 0.

Definition 2.30 (Divergence)

A sequence which doesn’t converge, is said to diverge.

Theorem 2.3 (Sequence Limit Uniqueness)

A sequence of real numbers can have utmost one limit.

Proof. If a sequence diverges, then there is nothing to prove. Otherwise, suppose a sequence {xn} converges to two limits x and y. Thus, for every Ο΅>0, there exist n1,n2∈N such that |xnβˆ’x|<Ο΅βˆ€n>n1 and |xnβˆ’y|<Ο΅βˆ€n>n2. Now, choose n0=max(n1,n2). Then, by triangle inequality, for every n>n0

0≀|xβˆ’y|≀|xβˆ’xn|+|xnβˆ’y|<Ο΅+Ο΅=2Ο΅.

Since this is true for all Ο΅>0, hence x=y. Since x,y are arbitrarily close, they must be equal.

Recall that the notion of sup and inf was introduced in the Definition 2.5. The same notation can be used for sequences also.

Definition 2.31 (Upper and lower bounds )

Let X={xn} be a sequence of R.

  • An upper bound of X is any u∈R such that xn≀uβˆ€n∈N.

  • A lower bound of X is any l∈R such that xnβ‰₯lβˆ€n∈N.

  • If X has an upper bound it is said to be bounded from above.

  • If X has a lower bound it is said to be bounded from below.

  • If X is both bounded from above and below, then X is said to be bounded.

  • A real number is called a least upper bound or supremum of X if it is an upper bound of X, and it is less than or equal to every other upper bound of X.

  • The least upper bound is denoted by sup(X).

  • A real number is called a greatest lower bound or infimum of X if it is a lower bound of X, and it is greater than or equal to every other lower bound of X.

  • The greatest lower bound is denoted by inf(X).

Remark 2.6

Due to the completeness axiom, if a sequence {xn} has an upper bound, it has a least upper bound denoted by sup{xn} and if it has a lower bound, it has a greatest lower bound denoted by inf{xn}.

The notion of upper boundedness and lower boundedness can be subsumed into a single definition.

Definition 2.32 (Boundedness)

A sequence {xn} is said to be bounded if there exists a number M>0 such that |xn|≀Mβˆ€n∈N.

Theorem 2.4

Every convergent sequence is bounded.

Proof. Let {xn} converge to x. Choosing a particular value of Ο΅=1, there exists n0∈N such that |xnβˆ’x|<1βˆ€n>n0. Thus, xn∈(xβˆ’1,x+1). This means that

|xn|<|x|+1βˆ€n>n0.

Now define M=max{|x1|,|x2|,…,|xn0|,|x|+1}. It follows that |xn|≀Mβˆ€n∈N as desired.

Definition 2.33 (Unbounded above )

A sequence {xn} is said to be unbounded above if there exists no u∈R such that xn≀uβˆ€n∈N.

In other words, for every u∈R, there exists an xn>u.

Definition 2.34 (Unbounded below )

A sequence {xn} is said to be unbounded below if there exists no l∈R such that xnβ‰₯lβˆ€n∈N.

In other words, for every l∈R, there exists an xn<l.

2.3.1. Monotone SequencesΒΆ

Definition 2.35 (Monotone sequences)

  • A sequence {xn} is said to be increasing if xn≀xn+1 for each n.

  • A sequence {xn} is said to be decreasing if xnβ‰₯xn+1 for each n.

  • A sequence {xn} is said to be monotone if it is either increasing or decreasing.

  • The notation xn↑x means {xn} is increasing and x=sup{xn}. It applies if {xn} is bounded from above.

  • The notation xn↓x means {xn} is decreasing and x=inf{xn}. It applies if {xn} is bounded from below.

  • If a sequence {xn} satisfies xn=c for all n, then it is called a constant sequence.

An increasing sequence is bounded from below. Its greatest lower bound is x1.

A decreasing sequence is bounded from above. Its least upper bound is x1.

Remark 2.7 (Unbounded increasing sequences)

Let {xn} be an increasing and unbounded sequence. Then for every M>0, there exists n0∈N such that for every n>n0, xn>M.

Remark 2.8 (Unbounded decreasing sequences)

Let {xn} be an decreasing and unbounded sequence. Then for every M<0, there exists n0∈N such that for every n>n0, xn<M.

Theorem 2.5 (Convergence of bounded monotone sequences)

Every monotone bounded sequence of real numbers is convergent.

Proof. Let {xn} be increasing and bounded sequence. From completeness axiom it follows that there exists x=sup{xn}. We claim that x itself is the limit of {xn}. From Proposition 2.6 we recall that for every ϡ>0, there exists a number xn0∈{xn}, such that

xβˆ’Ο΅<xn0≀x.

Since {xn} is increasing, hence

xβˆ’Ο΅<xn≀xβˆ€nβ‰₯n0.

This means that |xβˆ’xn|=xβˆ’xn<Ο΅βˆ€nβ‰₯n0. Thus x is indeed the limit. We follow similar steps to prove for decreasing sequence.

Theorem 2.6 (Convergence of constant sequences)

Let {xn} be a constant sequence with xn=c. Then lim{xn}=c.

Proof. For all Ο΅>0, |xnβˆ’c|=0<Ο΅ for all n∈N.

2.3.2. The Calculus of LimitsΒΆ

Let {xn} and {yn} be convergent sequences of R. Our concern here is to understand what happens to the limits if the sequences are combined.

Let lim{xn}=x and lim{yn}=y. Then:

Theorem 2.7 (Scaling a sequence)

lim{Ξ±xn}=Ξ±xβˆ€Ξ±βˆˆR.

Proof. If Ξ±=0, then we have a constant sequence and the result is trivial. So assume that Ξ±β‰ 0. Then:

|Ξ±xnβˆ’Ξ±x|=|Ξ±||xnβˆ’x|.

Let Ο΅>0 and choose n0∈N such that |xβˆ’xn|<Ο΅|Ξ±| for all n>n0. Then

|Ξ±xnβˆ’Ξ±x|=|Ξ±||xnβˆ’x|<|Ξ±|Ο΅|Ξ±|=Ο΅βˆ€n>n0.

Corollary 2.4 (Negating a sequence)

lim{βˆ’xn}=βˆ’x.

We get this result by choosing Ξ±=βˆ’1.

Theorem 2.8 (Addition of sequences)

lim{xn+yn}=x+y.

Proof. From triangle inequality we get:

|xn+ynβˆ’(x+y)|≀|xnβˆ’x|+|ynβˆ’y|.

For any Ο΅>0, choose n1 such that |xnβˆ’x|<Ο΅2βˆ€n>n1. Similarly, choose n2 such that |ynβˆ’y|<Ο΅2βˆ€n>n2. Now choose n0=max(n1,n2). Then:

|xn+ynβˆ’(x+y)|≀|xnβˆ’x|+|ynβˆ’y|<Ο΅2+Ο΅2=Ο΅βˆ€n>n0.

Corollary 2.5 (Subtraction of sequences)

lim{xnβˆ’yn}=xβˆ’y.

Negate {yn} and add to {xn}.

Theorem 2.9 (Multiplication of sequences)

lim{xnyn}=xy.

Proof. First let us assume that x≠0. We note that:

|xnynβˆ’xy|=|xnynβˆ’xyn+xynβˆ’xy|≀|xnynβˆ’xyn|+|xynβˆ’xy|=|yn||xnβˆ’x|+|x||ynβˆ’y|.

Let Ο΅>0 be arbitrary. Choose n1>0 such that

n>n1⟹|ynβˆ’y|<1|x|Ο΅2.

Since every convergent sequence is bounded, let M>0 be a bound of {yn} (i.e. βˆ’M≀yn≀M). Choose n2>0 such that

n>n2⟹|xnβˆ’x|<1MΟ΅2.

Further choose n0=max(n1,n2). Then, we have

|xnynβˆ’xy|≀|yn||xnβˆ’x|+|x||ynβˆ’y|<|yn|1MΟ΅2+|x|1|x|Ο΅2≀ϡ2+Ο΅2=Ο΅.

Since Ο΅ is arbitrary, hence we have shown that lim{xnyn}=xy.

Now consider the case where x=0. We need to show that lim{xnyn}=0. Let Ο΅>0 and choose n0 such that |xnβˆ’0|=|xn|<Ο΅M for all n>n0. Then

|xnynβˆ’0|≀|xn||yn|≀|xn|M<Ο΅MM=Ο΅.

Theorem 2.10 (Division of sequences)

lim{xn/yn}=x/y provided yβ‰ 0.

Proof. If we can prove that yn→y implies that 1yn→1y whenever y≠0, then the division of sequences reduces to multiplication of sequences {xn} and {1yn}. But

|1ynβˆ’1y|=|yβˆ’yn||y||yn|.

Choose Ο΅0=|y|/2. Then there exists n1∈N such that |yβˆ’yn|<Ο΅0=|y|/2 whenever n>n1. This gives us, |yn|>|y|/2 whenever n>n1 (i.e. yn is so close to y that its magnitude is much larger than |y|/2). Equivalently, we have

1|yn|<2|y|βˆ€n>n1.

Next, for arbitrary Ο΅>0, we choose n2 such that for all n>n2

|ynβˆ’y|<Ο΅|y|22.

Finally, pick n0=max(n1,n2). Then n>n0 implies

|1ynβˆ’1y|=|yβˆ’yn||y||yn|<Ο΅|y|221|y|2|y|=Ο΅.

Thus, yn→y implies that 1yn→1y whenever y≠0. Now division reduces to multiplication and we are done.

Although some elements of {yn} may be zero, but eventually yn becomes arbitrarily close to y and since y≠0, hence,

0<|y|2<|yn|<|y|βˆ€n> some m.

In other words, there comes a point m in the sequence Y so that all elements in Y after ym are non-zero with magnitude larger than |y|/2. We can practically throw away the first m terms from both the sequences X and Y and focus on the convergence of remaining sequence.

Next, we examine some of the order properties of the limits of sequences.

Theorem 2.11 (Order limit theorem)

Assume limxn=x and limyn=y.

  1. If xnβ‰₯0 for all n∈N, then xβ‰₯0.

  2. If xn≀yn for all n∈N, then x≀y.

  3. If there exists α∈R for which α≀yn for all n∈N, then α≀y. Similarly if xn≀α for all n∈N, then x≀α.

In words,

  1. If a sequence is non-negative, then its limit is non-negative.

  2. If one sequence is less than equal to another sequence for every term in the sequence, then its limit is also less than equal to the other sequence.

  3. A lower bound of a sequence is less than equal to its limit. An upper bound of a sequence is greater than equal to its limit.

Proof. (1) By contradiction, assume that x<0. Then x+|x|=0. Now consider Ο΅=|x|. Since {xn} is convergent, there exists n0∈N such that |xnβˆ’x|<Ο΅=|x|. Thus,

|xnβˆ’x|<|x|⟹xβˆ’|x|<xn<x+|x|⟹xn<0.

This is a contradiction. Hence xβ‰₯0.

(2) By Corollary 2.5 we have, lim(ynβˆ’xn)=yβˆ’x. Since ynβ‰₯xn, hence ynβˆ’xnβ‰₯0. From (1), we get yβˆ’xβ‰₯0. This implies yβ‰₯x.

(3) Take xn=Ξ±. Then ynβ‰₯Ξ±=xn⟹yβ‰₯Ξ± (using (2)).

Corollary 2.6 (Order limit theorem extension)

Assume limxn=x and limyn=y.

  1. If xnβ‰₯0 for all n>n0, then xβ‰₯0.

  2. If xn≀yn for all n>n0, then x≀y.

  3. If there exists α∈R for which α≀yn for all n>n0, then α≀y. Similarly if xn≀α for all n>n0, then x≀α.

We throw away the first n0 terms from each sequence and apply the theorem on the remaining part(s).

Example 2.7 (Limits don’t preserve strict inequality)

Consider xn=1n and yn=1n+1. limxn=0. limyn=0.

Thus, xn>yn doesn’t imply limxn>limyn. We only have xn>yn⟹xnβ‰₯yn⟹limxnβ‰₯limyn.

Similarly, xn>0 implies that limxnβ‰₯0. Or xn<r implies that limxn≀r.

Theorem 2.12 (Squeeze theorem for sequences)

If xn≀yn≀zn for all n∈N and if limxn=limzn=l, then limyn=l.

Proof. Let limyn=y. Using order limit theorem, xn≀yn gives us l≀y and yn≀zn gives us y≀l. Thus, l≀y≀l⟹y=l.

Corollary 2.7 (Squeeze theorem for sequences extension)

Let limxn=limzn=l. If there exists n0∈N such that for all n>n0, xn≀yn≀zn, then limyn=l.

Drop the first n0 terms from all the three sequences and then apply the theorem on remaining sequences.

Theorem 2.13 (Convergence of absolute sequence)

If xn→x, then |xn|→x. But the converse is not true.

Proof. Since xnβ†’x, for every Ο΅>0, there exists n0∈N such that n>0 implies |xnβˆ’x|<Ο΅. By triangle inequality

||xn|βˆ’|x||≀|xnβˆ’x|<Ο΅.

This completes the proof.

Now consider the sequence

{1,βˆ’1,1,βˆ’1,1,βˆ’1,…}.

Although in absolute value it converges to 1, the sequence itself doesn’t converge. Thus, the converse is not true.

2.3.3. Infinite SeriesΒΆ

Definition 2.36

Let {xn} be a sequence. An infinite series is a formal expression of the form

βˆ‘n=1∞xn=x1+x2+x3+x4+….

The corresponding sequence of partial sums {sm} is defined as

sm=x1+β‹―+xm.

We say that the series βˆ‘n=1∞xn converges to some s∈R if the sequence {sm} converges to s. In this case we write

βˆ‘n=1∞xn=s.

Example 2.8 (Convergent series)

Consider

βˆ‘n=1∞1n2.

Looking at the partial sums, we observe:

sm=1+14+19β‹―+1m2<1+12β‹…1+13β‹…2+…1mβ‹…(mβˆ’1)=1+(1βˆ’12)+(12βˆ’13)+β‹―+(1mβˆ’1βˆ’1m)=1+1βˆ’1m<2.

Thus, 2 is an upper bound of the sequence of partial sums. Hence, by monotone convergence theorem, the series converges to some (unknown) limit less than 2.

Example 2.9 (Harmonic series)

Consider

βˆ‘n=1∞1n.

We note that

s4=1+12+(13+14)>1+12+(14+14)=2.

Similarly, we find that s8>212. Further, we note that:

s2k=1+12+(13+14)+(15+β‹―+18)+β‹―+(12kβˆ’1+1+β‹―+12k)>1+12+(14+14)+(18+β‹―+18)+β‹―+(12k+β‹―+12k)=1+12+214+418+β‹―+2kβˆ’112k=1+12+12+12+β‹―+12=1+k12.

Thus, the harmonic series is unbounded.

Theorem 2.14 (Cauchy condensation test)

Suppose {xn} is decreasing and satisfies xnβ‰₯0 for all n∈N. Then, the series βˆ‘n=1∞xn converges if and only if the series

βˆ‘n=0∞2nx2n=x1+2x2+4x4+8x8+16x16+…

converges.

Proof. Let yn=2nβˆ’1x2nβˆ’1. Then, the second series is βˆ‘n=1∞yn. Let the partial sums of {xn} be sm and the partial sums of {yn} be tk.

First, assume that βˆ‘n=1∞yn converges. Thus, the sequence {tk} converges. Since every convergent sequence is bounded, the sequence {tk} is bounded. Thus, there exists M>0 such that tk≀M for all k∈N. Since xnβ‰₯0, the partial sums sm are increasing. Thus, if we show that {sm} is bounded, then by monotone convergence theorem, we would have shown that {sm} converges, hence the series βˆ‘n=1∞xn converges.

Let us fix m and choose k to be large enough so that m≀2k+1βˆ’1. Then sm≀s2k+1βˆ’1. Now,

s2k+1βˆ’1=x1+(x2+x3)+(x4+…x7)+β‹―+β‹―+(x2k+β‹―+x2k+1βˆ’1)≀x1+(x2+x2)+(x4+x4+x4+x4)+β‹―+(x2k+β‹―+x2k)=x1+2x2+β‹―+2kx2k=y1+y2+β‹―+yk=tk.

Thus, sm≀tk≀M. {sm} is bounded, hence convergent.

We now show that if βˆ‘n=1∞yn diverges, then βˆ‘n=1∞xn diverges too.

Consider the sum

s2k=x1+x2+(x3+x4)+(x5+β‹―+x8)+β‹―+(x2kβˆ’1+1+…x2k)β‰₯x1+x2+(x4+x4)+(x8+β‹―+x8)+β‹―+(x2k+…x2k)=x1+x2+2x4+4x8+…2kβˆ’1x2k=12x1+12(x1+2x2+4x4+8x8+β‹―+2kx2k)=12x1+tkβ‰₯tk.

Now, since {tk} diverges, hence {s2k} too diverges. Thus, the series diverges.

Definition 2.37 (Absolutely summable)

A series βˆ‘xn is called absolutely summable if βˆ‘|xn| converges.

A sequence {xn} is called absolutely summable if βˆ‘|xn| converges.

2.3.4. SubsequencesΒΆ

Theorem 2.15 (Subsequence convergence)

Subsequences of a convergent sequence converge to the same limit as the original sequence. If limnβ†’βˆžxn=x, then limnβ†’βˆžyn=x for every subsequence {yn} of {xn}.

Conversely, if two different subsequences of {xn} converge to different limits, then the sequence {xn} does not converge.

Proof. Since limnβ†’βˆžxn=x, for every Ο΅>0, there exists n0∈N such that |xβˆ’xn|<Ο΅βˆ€n>n0. Now, if {yn} is a subsequence, then there exists a strictly increasing sequence {kn} of natural numbers (i.e. 1≀k1<k2<k3<…) such that yn=xkn holds for each n. Clearly, there exists a k0>0 such that knβ‰₯n0βˆ€n>k0. Then, |xβˆ’yn|<Ο΅βˆ€n>k0. Thus, {yn} converges to x too.

Theorem 2.16 (Bolzano Weierstrass theorem)

Every bounded sequence contains a convergent subsequence.

The proof of this theorem follows a constructive approach (i.e., we will construct a subsequence and show that it is convergent). We construct a sequence of nested closed intervals with increasingly smaller lengths and pick a point in each such interval to form a subsequence.

Proof. Let {xn} be a bounded sequence. Thus, there exists M>0 such that |xn|≀M for all n∈N. Divide the interval [βˆ’M,M] into two equal closed intervals [βˆ’M,0] and [0,M]. At least one of the two halves must have an infinite number of points in {xn} (since if both halves had finite number of points, then the total number of points in the sequence would be finite which is a contradiction). Choose a half for which this is true, and label this half as I1. Choose a point xn1∈I1. Now divide I1 into two equal closed intervals. Again, since I1 contains infinite number of points, hence at least one of the halves must have infinite number of points. Pick a half which contains infinite number of points and label it as I2. Now, pick a point xn2 from I2 such that n2>n1. In general, construct a closed interval Ik from a half of Ikβˆ’1 containing infinite number of points. Further, we choose a point xnk such that nk>nkβˆ’1>β‹―>n2>n1 and xnk∈Ik. We claim that the subsequence {xnk} is a convergent subsequence. For this, we need a limit for the sequence. Since

I1βŠ‡I2βŠ‡β‹―βŠ‡IkβŠ‡β€¦

are a nested sequence of closed intervals, hence by nested interval property, their intersection I=β‹‚k=1∞Ik is non-empty. Actually, it’s easy to show that this I is a singleton too. If there were two distinct points x,y in I, then considering d=|xβˆ’y|>0, we could find an interval Ij whose length is smaller than d. Thus both x,y could not fit in Ij. Hence I contains only one point. Let I={x}. We now show that xnkβ†’x.

Let Ο΅>0. By construction, the length of Ik is M12kβˆ’1. Since it converges to 0, hence, we can choose n0∈N such that for every k>n0, the length of Ik is less than Ο΅. Since x and xnk are both in Ik, hence it follows that |xnkβˆ’x|<Ο΅.

2.3.5. Cauchy SequenceΒΆ

Definition 2.38 (Cauchy sequence)

A sequence {xn} in R is called a Cauchy sequence if, for every Ο΅>0, there exists n0∈N (depending on Ο΅) such that whenever m,n>n0 it follows that |xmβˆ’xn|<Ο΅.

Remark 2.9

A little thought would show that saying m,n>n0 or m,nβ‰₯n1 doesn’t make much difference in the definition. The two thresholds can be related by : n1=n0+1.

Theorem 2.17 (Boundedness of Cauchy sequences)

A Cauchy sequence is bounded.

Proof. Let {xn}. Choose Ο΅=1. Then there exists n0∈N such that |xnβˆ’xm|<1 whenever m,nβ‰₯n0. In particular, the statement is valid when m=n0. i.e. |xnβˆ’xn0|<1 . But,

|xnβˆ’xn0|<1⟹||xn|βˆ’|xn0||<1⟹|xn|<1+|xn0|βˆ€nβ‰₯n0.

Choosing M=max(|x1|,…,|xn0βˆ’1|,|xn0|+1), it is clear that |xn|≀M, hence {xn} is bounded.

Theorem 2.18 (Convergence of Cauchy sequences)

A Cauchy sequence is convergent.

Proof. Let {xn} be a Cauchy sequence. Hence it is bounded. Hence, by Bolzano Weierstrass theorem, it has a convergent subsequence.

Let {xnk} be such a convergent subsequence with the limit limxnk=x.

Thus, for any ϡ>0, there exists n1∈N such that for all k>n1,

|xnkβˆ’x|<Ο΅2.

Also, since {xn} is Cauchy, there exists n2∈N such that for all n,m>n2,

|xnβˆ’xm|<Ο΅2.

Pick any k>n1 such that nk>n2. Then, for all n>n2,

|xnβˆ’x|≀|xnβˆ’xnk|+|xnkβˆ’x|<Ο΅2+Ο΅2=Ο΅.

Thus, limxn=x.

Theorem 2.19 (Convergence and Cauchyness)

A sequence of real numbers converges if and only if it is a Cauchy sequence.

Proof. Let a sequence {xn} converge to Ο΅. Then for every Ο΅>0, there exists n0∈N such that |xnβˆ’x|<Ο΅/2 for all n>n0. Clearly, if m,n>n0, then

|xmβˆ’xn|≀|xmβˆ’x|+|xβˆ’xn|<Ο΅2+Ο΅2=Ο΅.

Thus, {xn} is Cauchy.

For the converse, in the previous theorem, we proved that a Cauchy sequence is convergent.

Remark 2.10

Let {xn} be a Cauchy sequence with limxn=x. Let Ο΅>0. Choose n0 such that m,n>n0 implies |xmβˆ’xn|<Ο΅.

Then

|xnβˆ’x|β‰€Ο΅βˆ€n>n0.

Proof. We have, for all m,n>n0

|xmβˆ’xn|<ϡ⟺xmβˆ’Ο΅<xn<xm+Ο΅.

We will fix n and vary n to compute the limit inequalities.

  1. Consider the strict inequality: xmβˆ’Ο΅<xn for all m>n0.

  2. Taking the limit on the sequence xm (in L.H.S.), we get: xβˆ’Ο΅β‰€xn.

  3. Consider the strict inequality: xn<xm+Ο΅ for all m>n0.

  4. Taking the limit on the sequence xm (in R.H.S.), we get: xn≀x+Ο΅.

  5. Together, we get: xβˆ’Ο΅β‰€xn≀x+Ο΅.

  6. Combining, we get |xnβˆ’x|≀ϡ for all n>n0.

See also Example 2.7.

2.3.6. Limit Inferior and Limit SuperiorΒΆ

Theorem 2.20 (Sequences of partial suprema and infima)

Let {xn} be a sequence of R. Define

sn=sup{xk|kβ‰₯n}

and

tn=inf{xk|kβ‰₯n}.

If {xn} is not bounded above, then

limnβ†’βˆžsn=∞.

If {xn} is not bounded below, then

limnβ†’βˆžtn=βˆ’βˆž.

If {xn} is bounded from above, then {sn} is a nonincreasing sequence.

If {xn} is bounded from below, then {tn} is a nondecreasing sequence.

If {xn} is bounded, then both the sequences {sn} and {tn} are convergent.

Proof. Let {xn} not be bounded from above.

  1. Then, for any n∈N, the set {xk|kβ‰₯n} is also not bounded from above.

  2. Thus, sn=sup{xk|kβ‰₯n}=∞ for all n∈N.

  3. Thus, limnβ†’βˆžsn=∞.

Let {xn} not be bounded from below.

  1. Then, for any n∈N, the set {xk|kβ‰₯n} is also not bounded from below.

  2. Thus, tn=inf{xk|kβ‰₯n}=βˆ’βˆž for all n∈N.

  3. Thus, limnβ†’βˆžtn=βˆ’βˆž.

We note that for m<n,

{xk|kβ‰₯n}βŠ†{xk|kβ‰₯m}.

Now, assume that {xn} is bounded from above.

  1. Then, sup{xk|kβ‰₯n}≀sup{xk|kβ‰₯m}.

  2. Or sn≀sm.

  3. Thus, m<n implies that smβ‰₯sn.

  4. Thus, {sn} is a nonincreasing sequence.

Now, assume that {xn} is bounded from below.

  1. Then, inf{xk|kβ‰₯n}β‰₯inf{xk|kβ‰₯m}.

  2. Or tnβ‰₯tm.

  3. Thus, m<n implies that tm≀tn.

  4. Thus, {tn} is a nondecreasing sequence.

Now, assume that {xn} is bounded.

  1. From Theorem 2.5, a monotone bounded sequence is convergent.

  2. Since {xn} is bounded, hence {sn} is bounded too.

  3. Since {xn} is bounded, hence {tn} is bounded too.

  4. Thus, both {sn} and {tn} are bounded and monotone.

  5. Thus, both of them are convergent sequences.

Definition 2.39 (Limit superior and inferior)

Let {xn} be a sequence of R. The limit superior of the sequence is defined as:

lim supnβ†’βˆžxnβ‰œlimnβ†’βˆžsup{xk|kβ‰₯n}.

Similarly, the limit inferior of the sequence is defined as:

lim infnβ†’βˆžxnβ‰œlimnβ†’βˆžinf{xk|kβ‰₯n}.

If we define

sn=sup{xk|kβ‰₯n} and tn=inf{xk|kβ‰₯n}

then,

lim supnβ†’βˆžxn=limnβ†’βˆžsn

and

lim infnβ†’βˆžxn=limnβ†’βˆžtn.

It is imperative to establish that the definition of limit inferior and limit superior is justified.

  1. If {xn} is not bounded from above, then sn=∞.

  2. If {xn} is bounded from above then {sn} is nondecreasing.

  3. In this case, if {xn} is bounded from below, then {sn} converges, otherwise it diverges to βˆ’βˆž.

Similar justification applies for the limit inferior too.

Remark 2.11 (Limit superior and inferior for unbounded sequences)

Let {xn} be a sequence of R.

If {xn} is not bounded from above, then

lim supnβ†’βˆžxn=∞.

If {xn} is not bounded from below, then

lim infnβ†’βˆžxn=βˆ’βˆž.

Theorem 2.21 (Limit superior β‰₯ limit inferior)

Let {xn} be a sequence of R. Then,

lim infnβ†’βˆžxn≀lim supnβ†’βˆžxn.

Proof. If we define

sn=sup{xk|kβ‰₯n} and tn=inf{xk|kβ‰₯n}

then, tn≀sn for every n.

Then, by Theorem 2.11,

limnβ†’βˆžtn≀limnβ†’βˆžsn.

Thus,

lim infnβ†’βˆžxn=limnβ†’βˆžtn≀limnβ†’βˆžsn=lim supnβ†’βˆžxn.

Theorem 2.22 (Relationship between limit superior and inferior)

Let {xn} be a sequence of R. Then,

lim supnβ†’βˆž(βˆ’xn)=βˆ’lim infnβ†’βˆžxn.

Proof. We recall that

inf(βˆ’1β‹…A)=βˆ’1β‹…sup(A) and sup(βˆ’1β‹…A)=βˆ’1β‹…infsup(A)

Thus,

lim supnβ†’βˆž(βˆ’xn)=limnβ†’βˆžsup{βˆ’xk|kβ‰₯n}=limnβ†’βˆžβˆ’inf{xk|kβ‰₯n}=βˆ’limnβ†’βˆžinf{xk|kβ‰₯n}=βˆ’lim infnβ†’βˆžxn.

Theorem 2.23 (Characterization of limit superior)

Let {xn} be a sequence of R. Let u∈R. The following are equivalent.

  1. lim supnβ†’βˆžxn=u.

  2. For any ϡ>0, there exists n0∈N such that

    xn<u+Ο΅βˆ€nβ‰₯n0.

    and there exists a subsequence {xkn} of {xn} such that limnβ†’βˆžxkn=u.

Proof. TBD

Theorem 2.24 (Characterization of limit inferior)

Let {xn} be a sequence of R. Let l∈R. The following are equivalent.

  1. lim infnβ†’βˆžxn=l.

  2. For any ϡ>0, there exists n0∈N such that

    xn>lβˆ’Ο΅βˆ€nβ‰₯n0.

    and there exists a subsequence {xkn} of {xn} such that limnβ†’βˆžxkn=l.

Proof. TBD

This leads us to the fact that the limit of a sequence exists if and only if its limit inferior and limit superior are identical.

2.3.6.1. Existence of LimitΒΆ

Theorem 2.25 (Limit = limit superior = limit inferior)

Let {xn} be a sequence of R. Then,

limnβ†’βˆžxn=l if and only if lim supnβ†’βˆžxn=lim infnβ†’βˆžxn=l.

In other words the limit of a sequence exists if and only if both limit superior and limit inferior are equal and in this case, the limit of sequence equals the limit superior and inferior.

Proof. TBD

2.3.6.2. SubsequencesΒΆ

Theorem 2.26 (Convergent subsequences and limit superior/inferior)

Let {xn} be a sequence of R. Let {xkn} be an arbitrary subsequence of {xn}.

Suppose lim supxn=u. If {xkn} converges then

limnβ†’βˆžxkn≀u.

Suppose lim infxn=l. If {xkn} converges then

limnβ†’βˆžxknβ‰₯l.

Proof. Assume that lim supxn=u.

  1. Let Ο΅>0.

  2. By Theorem 2.23, there exists n0 such that for all n>n0

    xn<u+Ο΅.
  3. Let limnβ†’βˆžxkn=s.

  4. Then, there exists n1 such that for all kn>n1

    sβˆ’Ο΅<xkn<s+Ο΅.
  5. Let n2=max(n0,n1).

  6. Then, for all kn>n2

    sβˆ’Ο΅<xkn<u+Ο΅.
  7. Thus, s<u+2Ο΅ for every Ο΅>0.

  8. Thus, s≀u.

The proof for limit inferior is similar.

Remark 2.12 (The set of subsequential limits for bounded sequences)

Let {xn} be a bounded sequence of R. Define

A={x∈R| there exists a subsequence {xkn} with limxkn=x}.

This is the set of limits of convergent subsequences of {xn}. By Theorem 2.16 {xn} has a convergent subsequence since it is bounded. Hence, A is not empty.

Each element of A is called a subsequential limit of {xn}. Due to Theorem 2.20, both lim supxn and lim infxn are finite since {xn} is bounded.

Let a∈A. Then, by Theorem 2.26:

lim infxn≀a≀lim supxn.

By Theorem 2.23, there exists u∈A such that

lim supxn=u.

By Theorem 2.24, there exists l∈A such that

lim infxn=l.

Thus,

lim supxn=maxA and lim infxn=minA.

2.3.6.3. ArithmeticΒΆ

Theorem 2.27 (Arithmetic of limit superior and inferior)

Let {an} and {bn} be sequences of R.

The limit superior satisfies subadditivity.

lim supnβ†’βˆž(an+bn)≀lim supnβ†’βˆžan+lim supnβ†’βˆžbn.

The limit inferior satisfies superadditivity.

lim infnβ†’βˆž(an+bn)β‰₯lim infnβ†’βˆžan+lim infnβ†’βˆžbn.

If both {an} and {bn} are nonnegative, then

lim supnβ†’βˆž(anbn)≀(lim supnβ†’βˆžan)(lim supnβ†’βˆžbn)

and

lim infnβ†’βˆž(anbn)β‰₯(lim infnβ†’βˆžan)(lim infnβ†’βˆžbn).

2.3.6.4. OrderΒΆ

Theorem 2.28 (Order properties of limit superior and inferior)

Let {xn} and {yn} be sequences of R.

  1. If xnβ‰₯0 for all n∈N, then lim infnβ†’βˆžxβ‰₯0.

  2. If xn≀0 for all n∈N, then lim supnβ†’βˆžx≀0.

  3. If xn≀yn for all n∈N, then lim supxn≀lim supyn.

  4. If xnβ‰₯yn for all n∈N, then lim infxnβ‰₯lim infyn.

Proof. Assume that xnβ‰₯0.

  1. Then, inf{xk|kβ‰₯n}β‰₯0.

  2. Thus,

    lim infnβ†’βˆžxn=limnβ†’βˆžinf{xk|kβ‰₯n}β‰₯limnβ†’βˆž0=0.

Assume that xn≀0.

  1. Then, sup{xk|kβ‰₯n}≀0.

  2. Thus,

    lim supnβ†’βˆžxn=limnβ†’βˆžsup{xk|kβ‰₯n}≀limnβ†’βˆž0=0.

Assume that xn≀yn for all n∈N.

  1. Choose any k∈N.

  2. Let Mn=sup{yk|kβ‰₯n}.

  3. Then, yk≀Mn for every kβ‰₯n.

  4. Then, xk≀yk≀Mn for every kβ‰₯n.

  5. Taking supremum over kβ‰₯n, mn=sup{xk|kβ‰₯n}≀Mn.

  6. Thus, mn≀Mn for every n.

  7. Thus, by Theorem 2.11, limmn≀limMn.

  8. Thus, lim supxn≀lim supyn.

A similar argument can be used for xnβ‰₯yn also.

2.3.6.5. Damping and Growing SequencesΒΆ

Theorem 2.29 (Damping sequences)

Let {xn} be a sequence of R such that xn>0 for every n.

Assume that the following holds:

lim supnβ†’βˆžxn+1xn=u<1.

Then, limnβ†’βˆžxn=0.

Proof. We proceed as follows.

  1. Since xn+1xn>0, hence uβ‰₯0.

  2. Since u<1, we can choose an Ο΅>0 such that u+Ο΅<1.

  3. Let q=u+Ο΅. Then, 0<q<1.

  4. By Theorem 2.23, there exists n0∈N such that for all nβ‰₯n0

    xn+1xn<u+Ο΅=q.
  5. Thus, xn+1<qxn for every nβ‰₯n0.

  6. Let x=xn0.

  7. Then, we have xn<qnβˆ’n0x for every n>n0.

  8. Also, limnβ†’βˆžqnβˆ’n0x=0 since q<1.

  9. We have 0<xn<qnβˆ’n0x for all n>n0.

  10. Hence, due to the squeeze theorem, limnβ†’βˆžxn=0.

Theorem 2.30 (Growing sequences)

Let {xn} be a sequence of R such that xn>0 for every n.

Assume that the following holds:

lim infnβ†’βˆžxn+1xn=l>1.

Then, limnβ†’βˆžxn=∞.

Proof. We proceed as follows.

  1. Since l>1, we can choose an Ο΅>0 such that lβˆ’Ο΅>1.

  2. Let q=lβˆ’Ο΅. Then, q>1.

  3. By Theorem 2.24, there exists n0∈N such that for all nβ‰₯n0

    xn+1xn>lβˆ’Ο΅=q.
  4. Thus, xn+1>qxn for every nβ‰₯n0.

  5. Let x=xn0.

  6. Then, we have xn>qnβˆ’n0x for every n>n0.

  7. Also, limnβ†’βˆžqnβˆ’n0x=∞ since q>1.

  8. We have xn>qnβˆ’n0x for all n>n0.

  9. Hence, limxnβ‰₯limqnβˆ’n0x=∞.

  10. Thus, limxn=∞.