Unit 10, lesson 109

Sequence Behavior and Limiting Values

What it means for a sequence to settle on a limiting value, how convergent, divergent and oscillating sequences differ, and why a table of terms suggests a limit but never proves one.

  • Theory part 217
  • Practice part 218
  • Limits

A ball dropped from 2 meters bounces back to 60 percent of its height each time. It rises to 1.2 meters, then 0.72, then 0.432, and the heights keep shrinking without ever reaching zero, yet zero is plainly where they are heading. Other sequences never settle anywhere. They climb forever or keep swinging back and forth. Telling these behaviors apart is the first step toward limits in calculus.

Key terms

Limit of a sequence

Definition Let a1,a2,a3,…a_1, a_2, a_3, \dots be a sequence of real numbers and let LL be a real number. The sequence has limit LL if for every tolerance ε>0\varepsilon > 0 there is an integer NN such that

∣an−L∣<εfor every n>N.\lvert a_n - L \rvert < \varepsilon \quad \text{for every } n > N.

We then write an→La_n \to L or

lim⁡n→∞an=L.\lim_{n \to \infty} a_n = L.

The inequality says that ana_n lies in the horizontal band between L−εL - \varepsilon and L+εL + \varepsilon. So for every band around LL, however thin, all terms from some index on lie inside it. Finitely many early terms may lie outside. Some books write n≥Nn \ge N in place of n>Nn > N, which only moves NN by one and gives the same limits.

In plain words Draw any thin strip around LL. Sooner or later the terms enter the strip and never leave it again.

Example Take an=1+1na_n = 1 + \frac{1}{n}, which gives 2,32,43,542, \frac{3}{2}, \frac{4}{3}, \frac{5}{4} and so on. The distance from 11 is ∣an−1∣=1n\lvert a_n - 1 \rvert = \frac{1}{n}, which shrinks as nn grows.

Band half-width ε\varepsilonSmallest NN that worksReason
0.10.1N=10N = 101n<0.1\frac{1}{n} < 0.1 exactly when n>10n > 10
0.010.01N=100N = 1001n<0.01\frac{1}{n} < 0.01 exactly when n>100n > 100
0.0010.001N=1000N = 10001n<0.001\frac{1}{n} < 0.001 exactly when n>1000n > 1000

For any ε>0\varepsilon > 0, every integer N≥1εN \ge \frac{1}{\varepsilon} works, so the limit is 11.

Convergence

Definition A sequence converges if it has a limit LL that is a real number, and then it converges to LL. A convergent sequence has exactly one limit. Whether a sequence converges, and to what, depends only on its tail, the terms from some index on. Changing, adding or removing finitely many terms changes neither.

In plain words A convergent sequence settles on one number. The first hundred or the first million terms can do anything, since only the long run counts.

Example Take

an=2n+1n+3=2+1n1+3n.a_n = \frac{2n + 1}{n + 3} = \frac{2 + \frac{1}{n}}{1 + \frac{3}{n}}.

As nn grows, 1n\frac{1}{n} and 3n\frac{3}{n} shrink toward 00, which suggests the limit 22. To confirm it, compute the distance to 22,

∣an−2∣=∣2n+1−2(n+3)n+3∣=5n+3.\begin{aligned} \lvert a_n - 2 \rvert &= \left\lvert \frac{2n + 1 - 2(n + 3)}{n + 3} \right\rvert \\[0.8em] &= \frac{5}{n + 3}. \end{aligned}

This is less than 0.010.01 exactly when n+3>500n + 3 > 500, so every term from a498a_{498} on is within 0.010.01 of 22. For a general ε>0\varepsilon > 0 the same steps give n>5ε−3n > \frac{5}{\varepsilon} - 3, so the definition holds for every tolerance and the sequence converges to 22.

Divergence

Definition A sequence diverges if it does not converge. One kind of divergence is growth without bound. We write lim⁡n→∞an=∞\lim_{n \to \infty} a_n = \infty when for every number MM there is an integer NN such that an>Ma_n > M for every n>Nn > N, and lim⁡n→∞an=−∞\lim_{n \to \infty} a_n = -\infty when for every MM the terms satisfy an<Ma_n < M from some index on. Such a sequence still diverges, since ∞\infty is not a real number. The notation only says how it fails to converge.

In plain words A divergent sequence never settles on a single real number. Some run off to infinity, and others wander without settling.

Example The sequence an=2na_n = 2^n gives 2,4,8,162, 4, 8, 16 and so on. Since 210=10242^{10} = 1024 and the terms keep doubling, every term from a10a_{10} on is larger than 10001000. The same works for any bound MM, so 2n→∞2^n \to \infty. Increasing at every step is not enough for this, though. The sequence 1−1n1 - \frac{1}{n} also increases at every step, yet it stays below 11 and converges to 11.

Oscillation

Definition A sequence oscillates if it diverges but does not tend to ∞\infty or to −∞-\infty. Its terms keep moving back and forth without settling. A simple test proves this kind of divergence. If there are numbers p<qp < q such that an≤pa_n \le p for infinitely many nn and an≥qa_n \ge q for infinitely many nn, then the sequence diverges. The reason is that a limit would need a band of width q−pq - p around it to hold all terms from some index on. Two numbers inside such a band differ by less than q−pq - p, while the tail always contains a term at most pp and a term at least qq. Such a sequence cannot tend to ∞\infty or −∞-\infty either, since infinitely many terms stay at most pp and infinitely many stay at least qq, so it oscillates.

In plain words If the terms keep returning to two levels that sit a fixed distance apart, no thin band can ever trap them, so there is no limit. A change of sign alone is not oscillation, as long as the swings shrink to nothing.

Example The sequence (−1)n(-1)^n gives −1,1,−1,1-1, 1, -1, 1 and so on. Here infinitely many terms equal −1-1 and infinitely many equal 11, so with p=−1p = -1 and q=1q = 1 the test shows that it diverges. Compare it with

bn=(−1)nn,which gives−1,12,−13,14 and so on.\begin{gathered} b_n = \frac{(-1)^n}{n}, \quad \text{which gives} \\[0.8em] -1, \frac{1}{2}, -\frac{1}{3}, \frac{1}{4} \text{ and so on.} \end{gathered}

Its terms also switch sign at every step, but their distance from 00 is 1n\frac{1}{n}, which shrinks. So bnb_n converges to 00.

Bounded does not imply convergent

Definition A sequence is bounded if there is a number MM with ∣an∣≤M\lvert a_n \rvert \le M for every nn. Every convergent sequence is bounded. If an→La_n \to L, then all terms after some index NN lie between L−1L - 1 and L+1L + 1, and the finitely many terms up to aNa_N have a largest absolute value. The converse is false, because a bounded sequence can diverge. What is true is that a bounded sequence that never decreases, or one that never increases, converges. That fact rests on the completeness of the real numbers and is proved in calculus.

In plain words Staying inside a fixed range is necessary for convergence but not enough. A sequence can stay in a box forever and still never settle down.

Example The sequence

an=(−1)n nn+1gives−12,23,−34,45,−56 and so on.\begin{gathered} a_n = (-1)^n \, \frac{n}{n + 1} \quad \text{gives} \\[0.8em] -\frac{1}{2}, \frac{2}{3}, -\frac{3}{4}, \frac{4}{5}, -\frac{5}{6} \text{ and so on.} \end{gathered}

Every term has absolute value nn+1<1\frac{n}{n + 1} < 1, so the sequence is bounded. Yet every odd-numbered term is at most −12-\frac{1}{2} and every even-numbered term is at least 23\frac{2}{3}, so the test with p=−12p = -\frac{1}{2} and q=23q = \frac{2}{3} shows that it diverges. The odd terms crowd toward −1-1 and the even terms toward 11, and no single number attracts them all.

Geometric examples

Definition For a real number r≠0r \ne 0 the geometric sequence rnr^n, with n=0,1,2,…n = 0, 1, 2, \dots, behaves as follows.

lim⁡n→∞rn={0,∣r∣<1,1,r=1,∞,r>1.\lim_{n \to \infty} r^n = \begin{cases} 0, & \lvert r \rvert < 1, \\ 1, & r = 1, \\ \infty, & r > 1. \end{cases}

For r≤−1r \le -1 the sequence oscillates. When r=−1r = -1 it alternates between 11 and −1-1, and when r<−1r < -1 it alternates in sign while ∣rn∣\lvert r^n \rvert grows without bound. A sequence c rnc \, r^n with c≠0c \ne 0 has limit 00 when ∣r∣<1\lvert r \rvert < 1 and limit cc when r=1r = 1. It tends to ∞\infty or −∞-\infty when r>1r > 1, depending on the sign of cc, and oscillates when r≤−1r \le -1. These facts decide when an infinite geometric series converges. For r≠1r \ne 1 and a first term a≠0a \ne 0 the sum of the first nn terms is

a+ar+⋯+arn−1=a 1−rn1−r,a + ar + \cdots + ar^{n-1} = a \, \frac{1 - r^n}{1 - r},

so the partial sums converge exactly when rnr^n does, which means ∣r∣<1\lvert r \rvert < 1. For r=1r = 1 the partial sums are nana, which grow without bound in size. So with a≠0a \ne 0 the series converges exactly when ∣r∣<1\lvert r \rvert < 1, and then its sum is a1−r\frac{a}{1 - r}.

In plain words Repeated multiplication by a number smaller than 11 in size shrinks things to zero. A number larger than 11 in size blows them up, and a negative ratio makes the terms flip sign every time.

Example The table lists the first five terms, from n=0n = 0 to n=4n = 4.

Ratio rrTermsBehavior
12\frac{1}{2}1,12,14,18,1161, \frac{1}{2}, \frac{1}{4}, \frac{1}{8}, \frac{1}{16}converges to 00
−12-\frac{1}{2}1,−12,14,−18,1161, -\frac{1}{2}, \frac{1}{4}, -\frac{1}{8}, \frac{1}{16}converges to 00
111,1,1,1,11, 1, 1, 1, 1converges to 11
−1-11,−1,1,−1,11, -1, 1, -1, 1oscillates
221,2,4,8,161, 2, 4, 8, 16tends to ∞\infty
−2-21,−2,4,−8,161, -2, 4, -8, 16oscillates with growing size

The ball from the opening reaches hn=2(0.6)nh_n = 2(0.6)^n meters after nn bounces. Since ∣0.6∣<1\lvert 0.6 \rvert < 1 the heights converge to 00. They drop below 0.010.01 meters for the first time at n=11n = 11, where h11≈0.0073h_{11} \approx 0.0073.

Numerical evidence versus proof

Definition Computing finitely many terms of a sequence, however many, does not prove that it converges, that it diverges, or what its limit is. The limit depends only on the tail, and every finite list stops at some index and leaves out all the terms after it. A proof is an argument that covers every index from some point on, such as an inequality showing ∣an−L∣<ε\lvert a_n - L \rvert < \varepsilon for all n>Nn > N that works for every ε>0\varepsilon > 0.

In plain words A table is a good way to make a guess. Only an argument about all large nn settles the question.

Example The sequence an=10nn!a_n = \frac{10^n}{n!} starts like this.

nn112233445566881010
ana_n10105050166.7166.7416.7416.7833.3833.31388.91388.92480.22480.22755.72755.7

These terms suggest a sequence that grows forever. It does not. Each term comes from the one before by

an+1=10n+1 an,a_{n+1} = \frac{10}{n + 1} \, a_n,

and for n≥19n \ge 19 the factor 10n+1\frac{10}{n + 1} is at most 12\frac{1}{2}. So from a19≈82.2a_{19} \approx 82.2 on, each term is at most half the one before, and

0<an≤a19(12)n−19for n≥19.\begin{gathered} 0 < a_n \le a_{19} \left(\frac{1}{2}\right)^{n - 19} \\[0.8em] \text{for } n \ge 19. \end{gathered}

The right side converges to 00, so ana_n is squeezed to 00 as well. Already a30≈0.0038a_{30} \approx 0.0038.

Check yourself

  1. Find the limit of an=3n−1n+2a_n = \frac{3n - 1}{n + 2}. From which index on are all terms within 0.010.01 of it?
Show the answer

The limit is 33, because

∣an−3∣=∣3n−1−3(n+2)n+2∣=7n+2.\begin{aligned} \lvert a_n - 3 \rvert &= \left\lvert \frac{3n - 1 - 3(n + 2)}{n + 2} \right\rvert \\[0.8em] &= \frac{7}{n + 2}. \end{aligned}

This is less than 0.010.01 exactly when n+2>700n + 2 > 700, so all terms from a699a_{699} on are within 0.010.01 of 33.

  1. Which of these sequences converge? The first is (−0.9)n(-0.9)^n, the second is 1+(−1)n1 + (-1)^n and the third is cos⁡(nπ)n\frac{\cos(n\pi)}{n}.
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The first converges to 00, since it is geometric with ∣r∣=0.9<1\lvert r \rvert = 0.9 < 1. The second alternates between 00 and 22. It is bounded but oscillates, so it diverges. The third converges to 00. Since cos⁡(nπ)=(−1)n\cos(n\pi) = (-1)^n its terms are −1,12,−13,…-1, \frac{1}{2}, -\frac{1}{3}, \dots, whose distance from 00 is 1n\frac{1}{n}.

  1. The first 50 terms of a sequence all lie within 0.0010.001 of 44. Does the sequence converge to 44?
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Not necessarily. The sequence with an=4a_n = 4 for n≤50n \le 50 and an=na_n = n for n>50n > 50 has those first 50 terms, yet it tends to ∞\infty. Finitely many terms say nothing about the tail.

How this lesson connects

Where this leads in Calculus