3. Sequences and Series

3.1 Real-valued Sequences

3.1.1 Introductory Terms

Definition 3.1 (Real-valued sequence): A real-valued sequence is a function f:NRf: \N \to \R. We use the notation f=(an)nNf = \sequence a for a real-valued sequence and f(n)=anf(n) = a_n for the values of ff at nn.

In this section we treat only real-valued sequences. Thus, for now, a sequence is a real-valued sequence.

Definition 3.2 (Convergent sequence): Let (an)nN\sequence a be a sequence. (an)nN\sequence a is said to be convergent if there exists a number aRa \in \R s.t. ε>0  NN  nN:ana<ε \forall \epsilon > 0 \sep \exists N \in \N \sep \forall n \geq N : \abs{a_n - a} < \epsilon
Note: The number aa is called the limit of (an)nN\sequence a. We write limn=a\lim_{n\to\infty} = a or annaa_n \convginfty a.
Example (Convergent sequence): Let an=1na_n = \frac{1}{n}. We show that (an)nN\sequence a is convergent with limit 00. Let ε>0\epsilon > 0 be an arbitrary strictly positive real number. As we know, for any xRx \in \R there exists nNn \in \N s.t. n>xn > x, we pick NNN \in \N s.t. N>1εN > \frac{1}{\epsilon}. Then, for any nNn \geq N, an0=1n1N<ε\abs{a_n - 0} = \frac{1}{n} \leq \frac{1}{N} < \epsilon.
Proposition 3.3 (Uniqueness of limit): If (an)nN\sequence a is convergent, then its limit aa is unique.

3.1.2 Results on Real-valued Sequences

Definition 3.4 (Bounded sequence): A sequence (an)nN\sequence a is said to be
  • bounded if there exists a real number M>0M > 0 s.t. nN:anM\forall n \in \N : \abs{a_n} \leq M.
  • bounded from below if there exists a real number MM s.t. nN:anM\forall n \in \N : a_n \geq M.
  • bounded from above if there exists a real number MM s.t. nN:anM\forall n \in \N : a_n \leq M.
Proposition 3.5 (Convergent implies bounded): If (an)nN\sequence a is convergent, then it is bounded.
Definition 3.6 (Increasing, decreasing sequence): A sequence (an)nN\sequence a is
  • increasing if nN:anan+1\forall n \in \N : a_n \leq a_{n+1}.
  • decreasing if nN:anan+1\forall n \in \N : a_n \geq a_{n+1}.
  • monotonic if it is either increasing or decreasing.
Note: If (an)nN\sequence a is increasing with limit aa we write anaa_n \uparrow a, if it is decreasing with limit aa we write anaa_n \downarrow a.
Proposition 3.7 (Bounded, monotonic implies convergent): A bounded and monotonic sequence (an)nN\sequence a is convergent.
Example (Bounded, decreasing implies convergent): Let r<1\abs{r} < 1, and consider an=rna_n = \abs{r}^n, nNn \in \N. For any nNn \in \N, an<1a_n < 1 and rn+1=rnrrn\abs{r}^{n+1} = \abs{r}^n \abs{r} \leq \abs{r}^n. Thus, (an)nN\sequence a is bounded and decreasing and hence there exists an LL s.t. limnan=L\lim_{n\to\infty} a_n = L.
Proposition 3.8 (Arithmetic of limits): Let (an)nN\sequence a and (bn)nN\sequence b be two convergent sequences s.t. annaa_n \convginfty a and bnnbb_n \convginfty b. The following properties hold:
  1. an+bnna+ba_n + b_n \convginfty a+b
  2. anbnnaba_n b_n \convginfty ab
  3. anbnnab\frac{a_n}{b_n} \convginfty \frac{a}{b} if b0b\neq 0
Proposition 3.9 (Order persists on converging limits): Let (an)nN\sequence a and (bn)nN\sequence b be two convergent sequences s.t. annaa_n \convginfty a and bnnbb_n \convginfty b.
  • If nN:anbn\forall n \in \N : a_n \leq b_n, then aba \leq b.
  • If nN:anbn\forall n \in \N : a_n \geq b_n, then aba \geq b.
Proposition 3.10 (Limit of sandwiched sequence): Let (an)nN\sequence a and (bn)nN\sequence b be two convergent sequences that converge to the same limit, i.e., annaa_n \convginfty a and bnnab_n \convginfty a. Let (cn)nN\sequence c be another sequence which is s.t. nN:ancnbn\forall n \in \N : a_n \leq c_n \leq b_n. Then, cnnac_n \convginfty a.
Example (Limit of rnr^n in unit disk): TODO

3.1.3 On Diverging Sequences

Definition 3.11 (Diverging sequence): Let (an)nN\sequence a be a sequence. We write:
  • (an)nNn\sequence a \convginfty \infty if MR  NN  nN:anM\forall M \in \R \sep \exists N \in \N \sep \forall n \geq N : a_n \geq M
  • (an)nNn\sequence a \convginfty -\infty if MR  NN  nN:anM\forall M \in \R \sep \exists N \in \N \sep \forall n \geq N : a_n \leq M
If (an)nNn\sequence a \convginfty \infty or (an)nNn\sequence a \convginfty -\infty, we say that (an)nN\sequence a diverges.
Note: We refer to limnan\liminfty a_n as well-defined if limnanR\liminfty a_n \in \Rext, i.e. the sequnece converges or diverges. Notice that if limnan\liminfty a_n exists it is unique.
Proposition 3.12 (Diverging monotonic sequences): Let (an)nN\sequence a be a monotonic sequence. If (an)nN\sequence a diverges
  • and is increasing, then it diverges to ana_n \uparrow \infty.
  • and is decreasing, then it diverges to ana_n \downarrow -\infty.
Note: If (an)nN\sequence a is monotnoic, then limnan\liminfty a_n always exists.

We can now formulate a more general proposition on the order of limits, not necessarily requiring convergence.

Proposition 3.13 (Order persists on limits): Let (an)nN\sequence a and (bn)nN\sequence b be two monotonic sequences, either both increasing or both decreasing, with nN:anbn\forall n \in N : a_n \leq b_n, then limnanlimnbn\liminfty a_n \leq \liminfty b_n.

3.2 Series

Definition 3.14 (Series): Let (an)nN\sequence a be a sequence. The series iNai=i=1an\sumN a_i = \sum_{i = 1}^\infty a_n is understood as the sequence (sn)nN=i=1ai\sequence s = \sum_{i=1}^{\infty} a_i.
Note: If limnsn\liminfty s_n exists we write limnsn=iNa\liminfty s_n = \sumN a for the limit.
Proposition 3.15 (Positive series): Let iNai\sumN a_i be a series where iN:ai0\forall i \in \N : a_i \geq 0, then either iNai<\sumN a_i < \infty or iNai=\sumN a_i = \infty.
Example: TODO
Proposition 3.16 (Sandwiched converging series): Let iNai\sumN a_i be a series and iNbi\sumN b_i be a series s.t. bi0b_i \geq 0 for any iNi \in \N and iNbi<\sumN b_i < \infty. Suppose that iN:aibi\forall i \in \N : \abs{a_i} \leq b_i, then iNai<\sumN a_i < \infty.
Proposition 3.17 (Doubly indexed series): Let I,JN\setI, \setJ \subset \N and f:I×JRf : \setI \times \setJ \to \R. Set ai,j=f(i,j)a_{i,j} = f(i,j). Suppose that either i,j:ai,j0\forall i,j : a_{i,j} \geq 0 or (i,j)I×Jai,j<\sum_{(i,j) \in \setI \times \setJ} \abs{a_{i,j}} < \infty. Then (i,j)I×Jai,j=iIjJai,j=jJiIai,j \sum_{(i,j) \in \setI \times \setJ} a_{i,j} = \sum_{i \in \setI} \sum_{j \in \setJ} a_{i,j} = \sum_{j \in \setJ} \sum_{i \in \setI} a_{i,j} exists and we are allowed to change the order of summation.
Note: If I=J\setI = \setJ, we use the notation (i,j)I2ai,j=i,jIai,j\sum_{(i,j) \in \setI^2} a_{i,j} = \sum_{i,j \in \setI} a_{i,j} for the sum over all the pairs (i,j)I2(i,j) \in \setI^2.

3.3 Study of Convergence

3.3.1 Subsequences

We remain in the setting of the previous Section, i.e. any sequence (an)nN\sequence a is a real-valude sequence.

Definition 3.18 (Subsequence): Let f=(an)nNf = \sequence a be a sequence. A subsequence of (an)nN\sequence a is a new sequence g=(bn)nNg = \sequence b where g=fsg = f \circ s with s:NNs: \N \to \N s.t. s(n)<s(n+1)s(n) < s(n+1).
Note: For any nNn \in \N we have bn=g(n)=f(s(n))=as(n)b_n = g(n) = f(s(n)) = a_{s(n)}.
Example (Subsequence): Let an=1na_n = \frac{1}{n}, then (bn)nN\sequence{b} with bn=a2nb_n = a_{2n} is a subsequence.
Theorem 3.19 (Bolzano-Weierstrass): Let (an)nN\sequence a be a sequence. If (an)nN\sequence a is bounded, then there exists a subsequence of (an)nN\sequence a which is convergent.
Example (Bolzano-Weierstrass): Let an=(1)na_n = (-1)^n, nNn \in \N. We have seen that (an)nN\sequence a is not convergent. However, (bn)nN\sequence b with bn=a2nb_n = a_{2n} is convergent with limit bnn1b_n \convginfty 1.
Definition 3.20 (Accumulation point): Let (an)nN\sequence a be a sequence and (bn)nN\sequence b be a subsequence s.t. limnbn=b\liminfty b_n = b. Then bb is said to be an accumulation point of (an)nN\sequence a.
Example (Accumulation point): Let an=(1)na_n = (-1)^n, then (an)nN\sequence a has two accumulation points, 1-1 and 11.
Proposition 3.21 (Points around accumulation): Let bb be an accumulation point (an)nN\sequence a, then for any ε>0\epsilon > 0 there are infintely many ana_n s.t. an(aε,a+ε)a_n \in (a - \epsilon, a + \epsilon).
Proposition 3.22 (Convergent series has one accumulation): Let (an)nN\sequence a be a convergent sequence with limit aa, then every subsequence of (an)nN\sequence a converges to a. That is, a convergent sequence has only one accumulation point.
Proposition 3.23 (Diverging subsequence): Let (an)nN\sequence a be a sequence.
  • If (an)nN\sequence a is increasing and there exists a subsequence (bn)nN\sequence b s.t. bnnb_n \convginfty \infty, then anna_n \convginfty \infty.
  • If (an)nN\sequence a is decreasing and there exists a subsequence (bn)nN\sequence b s.t. bnnb_n \convginfty -\infty, then anna_n \convginfty -\infty.
Example: TODO

3.3.2 Limit Inferior and Limit superior

Note: We use the notation infnNan=inf{an | nN}\infN a_n = \inf \set{a_n \mid n \in \N} and supnNan=sup{an | nN}\supN a_n = \sup \set{a_n \mid n \in \N}.
Proposition 3.24 (inf, sup of unbounded sequences): Let (an)nN\sequence a be a sequence.
  • If (an)nN\sequence a is not bounded from below, then infnNan=\infN a_n = -\infty.
  • If (an)nN\sequence a is not bounded from above, then supnNan=\supN a_n = \infty.
Note: We use the notation infknak=inf{ak | kn}\infkn a_k = \inf \set{a_k \mid k \geq n} and supknak=sup{ak | kn}\supkn a_k = \sup \set{a_k \mid k \geq n}.
Proposition 3.25 (Limit of inf and sup sequences): Let (an)nN\sequence a be a sequence.
  • If (an)nN\sequence a is bounded from below, the sequence (mn)nN\sequence m with mn=infknakm_n = \infkn a_k is increasing with limnmn=supnNmn=supnNinfknak \liminfty m_n = \supN m_n = \supN \infkn a_k
  • If (an)nN\sequence a is bounded from above, the sequence (Mn)nN\sequence M with Mn=supknakM_n = \supkn a_k is decreasing with limnMn=infnNMn=infnNsupknak \liminfty M_n = \infN M_n = \infN \supkn a_k
Definition 3.26 (Limit inferior): The limit inferior of (an)nN\sequence a is lim infnan=supnNinfknak \liminfinfty a_n = \supN \infkn a_k if (an)nN\sequence a is bounded from below and lim infnan=\liminfinfty a_n = -\infty otherwise.
Definition 3.27 (Limit superior): The limit superior of (an)nN\sequence a is lim supnan=infnNsupknak \limsupinfty a_n = \infN \supkn a_k if (an)nN\sequence a is bounded from above and lim supnan=\limsupinfty a_n = \infty otherwise.
Proposition 3.28 (Order of liminf and limsup): Let (an)nN\sequence a be a sequence. We have that lim infnanlim supnan\liminfinfty a_n \leq \limsupinfty a_n.

The following proposition gives another characterization of convergence.

Proposition 3.29 (Convergence with liminf and limsup): Let (an)nN\sequence a be a bounded sequence. Then (an)nN\sequence a is convergent with limit aa if and only if lim infnan=a=lim supnan \liminfinfty a_n = a = \limsupinfty a_n

This characterization is useful as lim inf\liminf and lim sup\limsup are defined without using limits and solely by using inf\inf and sup\sup which may be easier to work with. A more general statement that includes diverging sequences is the following.

Theorem 3.30 (Existence of limit): Let (an)nN\sequence a be a sequence. Then the limit of the sequence exists with limnan=aR\liminfty a_n = a \in \Rext if and only if lim infnan=a=lim supnan \liminfinfty a_n = a = \limsupinfty a_n

3.4 Vector-valued Sequences

The previous section on real-valued sequences can easily be extended to the notion of vector-valued sequences.

Definition 3.31 (Vector-valued sequence): An Rk\R^k-values sequence is a function f:NRkf : \N \to \R^k, where we write f(n)=(a1,n,,ak,n)=anf(n) = (a_{1,n}, \ldots, a_{k,n}) = \dvec a_n for ff evaluated at an instance nNn \in \N.
Note: We rely on the notation f=(an)nNf = \sequence{\dvec a} for a real vector-valued sequence.

We notice that the coordinate functions fi=(ai,n)nNf_i = \sequence*{a}{i,n}{n} of an Rk\R^k-valued sequence (an)nN\sequence{\dvec a} are real-valued sequences. If k=1k=1 then (an)nN\sequence a is a real-valued sequence. Upon the Euclidean metric xy\norm{\dvec x - \dvec y} we can introduce the notion of convergence for Rk\R^k-valued sequences.

Definition 3.32 (Convergence of vector-valued sequences): (an)nN\sequence{\dvec a} is said to be convergent if there exists an aRk\dvec a \in \R^k s.t. for any ε>0\epsilon > 0 there exists NNN \in \N s.t. ana<ε\norm{\dvec a_n - \dvec a} < \epsilon for any nNn \geq N.
Note: We write anna\dvec a_n \convginfty \dvec a to indicate that (an)nN\sequence{\dvec a} converges to a\dvec a.

The following result shows that in order to prove that an Rk\R^k-valued sequence converges, it is enough to study the convergence of the individual coordinates.

Proposition 3.33 (Convergence of coordinates implies convergence): Let (an)nN\sequence{\dvec a} and aR\dvec a \in \R. Then anna\dvec a_n \convginfty \dvec a if and only if i{1,,k}:ai,nnai\forall i \in \set{1, \ldots, k} : a_{i,n} \convginfty a_i.

We point out that the notion of convergence enables a characterization of continuity known as the sequence criterion.

Proposition 3.34 (Sequence criterion for continuity): Let ERmE \subset \R^m, f:ERkf : E \to \R^k and xE\dvec x \in E. Then ff is continuous in x\dvec x if and only if for any Rm\R^m-valued sequence (xn)nN\sequence{\dvec x}, xnE\dvec x_n \in E, it follows that xnnx\dvec x_n \convginfty \dvec x implies f(xn)nf(x)f(\dvec x_n) \convginfty f(\dvec x).

We recall some classical examples of continuos functions.

Example (Continuous functions): The following functions are continuous
  • f:RkRf : \R^k \to \R, f(x)=i=1kxkf(\dvec x) = \sum_{i=1}^k x_k
  • g:RkRg : \R^k \to \R, g(x)=i=1kxkg(\dvec x) = \prod_{i=1}^k x_k
  • h:R{0}R{0}h : \R \setminus \set{0} \to \R \setminus \set{0}, h(x)=1xh(x) = \frac{1}{x}

3.5 Sequences in the Extended Real Numbers

Definition 3.35 (Extended real-valued sequence): A sequence (an)nN\sequence a with values in the extended real numbers is a sequence that can obtain any values in R\Rext.
Note: Let (an)nN\sequence a be a sequence with values in R\Rext, then the definitions of boundedness, monotony, limit inferior and limit superior also apply to (an)nN\sequence a.
Example (Extended real-valued sequence): Let an={1if n is oddif n is even a_n = \begin{cases} 1 & \text{if } n \text{ is odd} \\ \infty & \text{if } n \text{ is even} \end{cases}

Regarding convergence, we make the following definition.

Definition 3.36 (Convergence of extended real-valued sequences): Let (an)nN\sequence a be a sequence with values in R\Rext. Then (an)nN\sequence a is said to be convergent with limnan=a\liminfty a_n = a if and only if lim infnan=alim supnan\liminfinfty a_n = a \limsupinfty a_n.
Note: Notice that in contrast to real-valued sequences, if limnan=\liminfty a_n = \infty or limnan=\liminfty a_n = -\infty then (an)nN\sequence a is said to be convergent instead of divergent. In fact, divergence does not exist for sequences in the extended real numbers.
Example (Non-convergence): Let again an={1if n is oddif n is even a_n = \begin{cases} 1 & \text{if } n \text{ is odd} \\ \infty & \text{if } n \text{ is even} \end{cases} then lim infnan=1\liminfinfty a_n = 1 and lim supnan=\limsupinfty a_n = \infty, hence (an)nN\sequence a can not be convergent.

3.6 On Sequences of Functions

Definition 3.37 (Sequence of functions): Let A\setA and B\setB be sets. A sequence of functions is a collection of functions gn:ABg_n : \setA \to \setB for nNn \in \N.

We primarily focus on the case where B=Rk\setB = \R^k for k1k \geq 1 or B=R\setB = \Rext.

Definition 3.38 (Pointwise inf and sup): Let gn:ARg_n : \setA \to \Rext be a sequence of functions. Then, given IN\setI \subset \N, we define the function infnIgn:AR\inf_{n \in \setI} g_n : \setA \to \Rext as infnIgn(x)=inf{yR | nI:gn(x)=y} \inf_{n \in \setI} g_n(x) = \inf \set{y \in \Rext \mid \exists n \in \setI : g_n(x) = y} and supnIgn:AR\sup_{n \in \setI} g_n : \setA \to \Rext as supnIgn(x)=sup{yR | nI:gn(x)=y} \sup_{n \in \setI} g_n(x) = \sup \set{y \in \Rext \mid \exists n \in \setI : g_n(x) = y}
Definition 3.39 (Pointwise limit): Let gn:ARg_n : \setA \to \Rext be a sequence of functions. gng_n has the limit limngn(x)\liminfty g_n(x) in the point xAx \in \setA if and only if lim infngn(x)=limngn(x)=lim supngn(x) \liminfinfty g_n(x) = \liminfty g_n(x) = \limsupinfty g_n(x)
Note: We say that the sequence of functions gn:ARg_n : \setA \to \Rext converges pointwise on a set CA\setC \subset \setA if xC:limngn(x)R\forall x \in \setC : \liminfty g_n(x) \in \R.
Example (Pointwise non-convergence): Let gn:[0,π]Rg_n : [0, \pi] \to \R with gn(x)=cos(nx)g_n(x) = \cos(nx). We note lim infng(π)=1\liminfinfty g(\pi) = -1 and lim supngn(π)=1\limsupinfty g_n(\pi) = 1. Hence, gng_n does not converge pointwise on [0,π][0,\pi].