MathIsimple
Course 2

Sequences and Limits

Section 1: Sequences and ε-N Definition

Definition 1.1: Sequence

A sequence is a function f:N→Rf: \mathbb{N} \to \mathbb{R}. We denote it as {xn}n=1∞\{x_n\}_{n=1}^{\infty} or simply {xn}\{x_n\}, where xn=f(n)x_n = f(n).

Definition 1.2: Limit of a Sequence (ε-N Definition)

We say lim⁡n→∞xn=a\lim_{n \to \infty} x_n = a (or xn→ax_n \to a) if:

∀ε>0,∃N∈N:∀n>N,∣xn−a∣<ε\forall \varepsilon > 0, \exists N \in \mathbb{N}: \forall n > N, |x_n - a| < \varepsilon

In words: For every positive tolerance ε, there exists a natural number N such that all terms after the Nth term are within ε of a.

Theorem 1.1: Uniqueness of Limits

If a sequence converges, then its limit is unique.

Proof of Theorem 1.1:

Suppose lim⁡n→∞xn=a\lim_{n \to \infty} x_n = a and lim⁡n→∞xn=b\lim_{n \to \infty} x_n = b with a≠ba \neq b.

Let ϵ=∣a−b∣2>0\epsilon = \frac{|a-b|}{2} > 0.

By definition:

  • ∃N1\exists N_1: n>N1⇒∣xn−a∣<ϵn > N_1 \Rightarrow |x_n - a| < \epsilon
  • ∃N2\exists N_2: n>N2⇒∣xn−b∣<ϵn > N_2 \Rightarrow |x_n - b| < \epsilon

For n>max⁡{N1,N2}n > \max\{N_1, N_2\}:

∣a−b∣=∣a−xn+xn−b∣≤∣a−xn∣+∣xn−b∣<2ϵ=∣a−b∣|a - b| = |a - x_n + x_n - b| \leq |a - x_n| + |x_n - b| < 2\epsilon = |a - b|

This gives ∣a−b∣<∣a−b∣|a - b| < |a - b|, a contradiction. Therefore a=ba = b.

∎
Example 1.1: Basic Limit

Prove: lim⁡n→∞1n=0\lim_{n \to \infty} \frac{1}{n} = 0

Proof:

Given ϵ>0\epsilon > 0, we need to find NN such that for n>Nn > N:

∣1n−0∣=1n<ϵ\left|\frac{1}{n} - 0\right| = \frac{1}{n} < \epsilon

This is equivalent to n>1ϵn > \frac{1}{\epsilon}.

Choose N=⌊1ϵ⌋+1N = \left\lfloor \frac{1}{\epsilon} \right\rfloor + 1.

For n>Nn > N: 1n<1N<ϵ\frac{1}{n} < \frac{1}{N} < \epsilon. ∎

Example 1.2: Rational Function

Prove: lim⁡n→∞2n+1n+3=2\lim_{n \to \infty} \frac{2n+1}{n+3} = 2

Proof:

We compute:

∣2n+1n+3−2∣=∣2n+1−2(n+3)n+3∣=∣−5n+3∣=5n+3\left|\frac{2n+1}{n+3} - 2\right| = \left|\frac{2n+1 - 2(n+3)}{n+3}\right| = \left|\frac{-5}{n+3}\right| = \frac{5}{n+3}

Given ϵ>0\epsilon > 0, we need 5n+3<ϵ\frac{5}{n+3} < \epsilon, i.e., n>5ϵ−3n > \frac{5}{\epsilon} - 3.

Choose N=max⁡(0,⌊5ϵ−3⌋+1)N = \max\left(0, \left\lfloor \frac{5}{\epsilon} - 3 \right\rfloor + 1\right).

For n>Nn > N: 5n+3<ϵ\frac{5}{n+3} < \epsilon. ∎

Section 2: Limit Properties

Theorem 2.1: Boundedness of Convergent Sequences

If {xn}\{x_n\} converges, then {xn}\{x_n\} is bounded.

Proof of Theorem 2.1:

Let lim⁡n→∞xn=L\lim_{n \to \infty} x_n = L. Take ϵ=1\epsilon = 1.

∃N\exists N: n>N⇒∣xn−L∣<1⇒∣xn∣<∣L∣+1n > N \Rightarrow |x_n - L| < 1 \Rightarrow |x_n| < |L| + 1

Let M=max⁡{∣x1∣,∣x2∣,…,∣xN∣,∣L∣+1}M = \max\{|x_1|, |x_2|, \ldots, |x_N|, |L| + 1\}.

Then ∣xn∣≤M|x_n| \leq M for all nn.

∎
Theorem 2.2: Limit Laws

Let lim⁡n→∞xn=a\lim_{n \to \infty} x_n = a and lim⁡n→∞yn=b\lim_{n \to \infty} y_n = b. Then:

  • lim⁡(xn+yn)=a+b\lim(x_n + y_n) = a + b
  • lim⁡(xn⋅yn)=a⋅b\lim(x_n \cdot y_n) = a \cdot b
  • lim⁡xnyn=ab\lim\frac{x_n}{y_n} = \frac{a}{b} (if b≠0b \neq 0)
  • lim⁡(cxn)=ca\lim(cx_n) = ca for any constant cc
Proof of Sum Rule:

We show lim⁡(xn+yn)=a+b\lim(x_n + y_n) = a + b.

Given ϵ>0\epsilon > 0:

  • ∃N1\exists N_1: n>N1⇒∣xn−a∣<ϵ2n > N_1 \Rightarrow |x_n - a| < \frac{\epsilon}{2}
  • ∃N2\exists N_2: n>N2⇒∣yn−b∣<ϵ2n > N_2 \Rightarrow |y_n - b| < \frac{\epsilon}{2}

Let N=max⁡(N1,N2)N = \max(N_1, N_2). For n>Nn > N:

∣(xn+yn)−(a+b)∣≤∣xn−a∣+∣yn−b∣<ϵ2+ϵ2=ϵ|(x_n + y_n) - (a + b)| \leq |x_n - a| + |y_n - b| < \frac{\epsilon}{2} + \frac{\epsilon}{2} = \epsilon
∎
Example 2.1: Applying Limit Laws

Find: lim⁡n→∞3n2+2n−12n2−n+5\lim_{n \to \infty} \frac{3n^2 + 2n - 1}{2n^2 - n + 5}

Solution:

Divide numerator and denominator by n2n^2:

lim⁡n→∞3+2n−1n22−1n+5n2\lim_{n \to \infty} \frac{3 + \frac{2}{n} - \frac{1}{n^2}}{2 - \frac{1}{n} + \frac{5}{n^2}}

Using limit laws:

=3+0−02−0+0=32= \frac{3 + 0 - 0}{2 - 0 + 0} = \frac{3}{2}

Section 3: Squeeze Theorem

Theorem 3.1: Squeeze Theorem (Sandwich Theorem)

Let {an}\{a_n\}, {bn}\{b_n\}, {cn}\{c_n\} be sequences satisfying:

  1. ∃N0∈N\exists N_0 \in \mathbb{N}: an≤bn≤cna_n \leq b_n \leq c_n for all n≥N0n \geq N_0
  2. lim⁡n→∞an=L=lim⁡n→∞cn\lim_{n \to \infty} a_n = L = \lim_{n \to \infty} c_n

Then lim⁡n→∞bn=L\lim_{n \to \infty} b_n = L.

Proof of Theorem 3.1:

Given ϵ>0\epsilon > 0:

  • ∃N1\exists N_1: n>N1⇒∣an−L∣<ϵ⇒L−ϵ<ann > N_1 \Rightarrow |a_n - L| < \epsilon \Rightarrow L - \epsilon < a_n
  • ∃N2\exists N_2: n>N2⇒∣cn−L∣<ϵ⇒cn<L+ϵn > N_2 \Rightarrow |c_n - L| < \epsilon \Rightarrow c_n < L + \epsilon

For n>max⁡{N0,N1,N2}n > \max\{N_0, N_1, N_2\}:

L−ϵ<an≤bn≤cn<L+ϵL - \epsilon < a_n \leq b_n \leq c_n < L + \epsilon

Therefore ∣bn−L∣<ϵ|b_n - L| < \epsilon.

∎
Example 3.1: Using Squeeze Theorem

Find: lim⁡n→∞sin⁡nn\lim_{n \to \infty} \frac{\sin n}{n}

Solution:

We have −1≤sin⁡n≤1-1 \leq \sin n \leq 1, so:

−1n≤sin⁡nn≤1n-\frac{1}{n} \leq \frac{\sin n}{n} \leq \frac{1}{n}

Since −1n→0-\frac{1}{n} \to 0 and 1n→0\frac{1}{n} \to 0, by Squeeze Theorem:

lim⁡n→∞sin⁡nn=0\lim_{n \to \infty} \frac{\sin n}{n} = 0

Section 4: Monotone Bounded Theorem

Definition 4.1: Monotone Sequence

A sequence {an}\{a_n\} is:

  • Monotonically increasing if an≤an+1a_n \leq a_{n+1} for all nn
  • Monotonically decreasing if an≥an+1a_n \geq a_{n+1} for all nn
Theorem 4.1: Monotone Bounded Theorem

A bounded monotone sequence converges.

Proof of Theorem 4.1 (Increasing Case):

Let E={an:n∈N}E = \{a_n : n \in \mathbb{N}\}. Since EE is non-empty and bounded above, by the Completeness Axiom, α=sup⁡E\alpha = \sup E exists.

We claim lim⁡n→∞an=α\lim_{n \to \infty} a_n = \alpha.

Given ϵ>0\epsilon > 0:

  • By supremum property: ∃N\exists N such that aN>α−ϵa_N > \alpha - \epsilon
  • By monotonicity: n>N⇒an≥aN>α−ϵn > N \Rightarrow a_n \geq a_N > \alpha - \epsilon
  • By upper bound: an≤α<α+ϵa_n \leq \alpha < \alpha + \epsilon

Therefore ∣an−α∣<ϵ|a_n - \alpha| < \epsilon for n>Nn > N.

∎
Example 4.1: The Number e

Prove: The sequence xn=(1+1n)nx_n = (1 + \frac{1}{n})^n converges.

Solution:

One can show that {xn}\{x_n\} is strictly increasing and bounded above by 3.

By the Monotone Bounded Theorem, it converges. The limit is denoted ee:

e=lim⁡n→∞(1+1n)n≈2.71828...e = \lim_{n \to \infty} \left(1 + \frac{1}{n}\right)^n \approx 2.71828...

Section 5: Subsequences and Bolzano-Weierstrass

Definition 5.1: Subsequence

Let {an}\{a_n\} be a sequence. If {nk}⊂N\{n_k\} \subset \mathbb{N} with n1<n2<n3<⋯n_1 < n_2 < n_3 < \cdots, then {ank}\{a_{n_k}\} is a subsequence of {an}\{a_n\}.

Theorem 5.1: Subsequence Convergence

{an}\{a_n\} converges to aa ⇔\Leftrightarrow Every subsequence of {an}\{a_n\} converges to aa.

Theorem 5.2: Bolzano-Weierstrass Theorem

Every bounded sequence has a convergent subsequence.

Proof of Theorem 5.2:

Method: Every sequence has a monotone subsequence (by peak argument). Since the original is bounded, the monotone subsequence is bounded, hence converges by Monotone Bounded Theorem.

∎
Example 5.1: Divergence via Subsequences

Prove: {(−1)n}\{(-1)^n\} diverges.

{a2k}=1,1,1,…→1\{a_{2k}\} = 1, 1, 1, \ldots \to 1

{a2k−1}=−1,−1,−1,…→−1\{a_{2k-1}\} = -1, -1, -1, \ldots \to -1

Since 1≠−11 \neq -1, the sequence diverges.

Section 6: Cauchy Sequences

Definition 6.1: Cauchy Sequence

A sequence {an}\{a_n\} is a Cauchy sequence if:

∀ϵ>0,∃N∈N,∀n,m>N:∣an−am∣<ϵ\forall \epsilon > 0, \exists N \in \mathbb{N}, \forall n, m > N: |a_n - a_m| < \epsilon
Theorem 6.1: Cauchy Criterion

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

Proof of Theorem 6.1 (Necessity):

Let lim⁡an=L\lim a_n = L. Given ϵ>0\epsilon > 0, ∃N\exists N: n>N⇒∣an−L∣<ϵ2n > N \Rightarrow |a_n - L| < \frac{\epsilon}{2}.

For n,m>Nn, m > N:

∣an−am∣≤∣an−L∣+∣L−am∣<ϵ2+ϵ2=ϵ|a_n - a_m| \leq |a_n - L| + |L - a_m| < \frac{\epsilon}{2} + \frac{\epsilon}{2} = \epsilon
∎
Example 6.1: Harmonic Series is NOT Cauchy

Show: Hn=∑k=1n1kH_n = \sum_{k=1}^n \frac{1}{k} is not Cauchy.

Solution:

∣H2n−Hn∣=∑k=n+12n1k>n⋅12n=12|H_{2n} - H_n| = \sum_{k=n+1}^{2n} \frac{1}{k} > n \cdot \frac{1}{2n} = \frac{1}{2}

This violates the Cauchy criterion, so the harmonic series diverges.

Section 7: Nested Interval Theorem

Theorem 7.1: Cantor's Nested Interval Theorem

If {[an,bn]}\{[a_n, b_n]\} is a sequence of closed intervals with:

  1. [an,bn]⊇[an+1,bn+1][a_n, b_n] \supseteq [a_{n+1}, b_{n+1}] for all nn
  2. lim⁡n→∞(bn−an)=0\lim_{n \to \infty} (b_n - a_n) = 0

Then ∃! ξ∈R\exists!\, \xi \in \mathbb{R}: {ξ}=⋂n=1∞[an,bn]\{\xi\} = \bigcap_{n=1}^{\infty} [a_n, b_n]

Proof of Theorem 7.1:

The sequence {an}\{a_n\} is increasing and bounded above by b1b_1, so it converges to some ξ\xi.

Similarly, {bn}\{b_n\} is decreasing and bounded below, converging to the same ξ\xi (since bn−an→0b_n - a_n \to 0).

Therefore ξ∈[an,bn]\xi \in [a_n, b_n] for all nn, and is unique.

∎
Example 7.1: Bisection Method

Application: The bisection method for finding roots uses nested intervals. Each step halves the interval, and the intersection gives the root.

Work These Ideas by Hand — Then Check Yourself

Practice Quiz: Sequences and Limits
10
Questions
0
Correct
0%
Accuracy
1
Which of the following sequences is convergent?
Easy
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2
The ε-N definition states: lim⁡n→∞xn=a\lim_{n \to \infty} x_n = a if and only if...
Easy
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3
If lim⁡xn=a\lim x_n = a and lim⁡yn=b\lim y_n = b, then lim⁡(xn+yn)\lim(x_n + y_n) equals:
Easy
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4
The Squeeze Theorem applies when:
Medium
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5
A bounded monotone sequence:
Medium
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6
If ∣xn∣≤yn|x_n| \leq y_n and lim⁡yn=0\lim y_n = 0, what is lim⁡xn\lim x_n?
Medium
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7
The sequence xn=(1+1n)nx_n = (1 + \frac{1}{n})^n converges to:
Hard
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8
If lim⁡(xn+yn)\lim(x_n + y_n) exists and lim⁡xn\lim x_n exists, must lim⁡yn\lim y_n exist?
Hard
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9
What's wrong with: 'xn<1x_n < 1 for all n, so lim⁡xn<1\lim x_n < 1'?
Hard
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10
The Stolz Theorem is useful for:
Hard
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Frequently Asked Questions

Why do we need the ε-N definition?

The ε-N definition provides a rigorous framework for limits, eliminating ambiguity. It allows us to prove statements about limits with certainty and handle edge cases that intuitive approaches miss.

What's the intuition behind ε-N?

Think of ε as a tolerance level - how close we want the sequence to be to the limit. N is the starting point after which all terms are within this tolerance. The definition says: no matter how tight we make the tolerance, we can always find a point after which all terms satisfy it.

Can a sequence have more than one limit?

No! If a sequence converges, its limit is unique. This is a fundamental theorem that we prove using the ε-N definition.

What's the difference between bounded and convergent?

Convergent implies bounded, but the converse is false. The sequence {(-1)^n} is bounded but divergent because it oscillates. However, every convergent sequence must be bounded.

How do I choose the right N in a proof?

Work backwards: start with |xₙ - a| < ε and algebraically solve for what condition on n makes this true. The resulting expression tells you how to choose N, often using floor functions or adding 1 to ensure N is a natural number.