MathIsimple
Course 4

Continuity Theorems

Section 1: Boundedness Theorem

Theorem 1.1: Boundedness Theorem

If f∈C[a,b]f \in C[a, b], then ff is bounded on [a,b][a, b]:

∃M>0:∣f(x)∣≤M for all x∈[a,b]\exists M > 0: |f(x)| \leq M \text{ for all } x \in [a, b]
Proof of Theorem 1.1 (by contradiction):

Suppose ff is unbounded. Then ∀n∈N\forall n \in \mathbb{N}, ∃xn∈[a,b]\exists x_n \in [a,b] with ∣f(xn)∣>n|f(x_n)| > n.

By Bolzano-Weierstrass, {xn}\{x_n\} has a convergent subsequence xnk→c∈[a,b]x_{n_k} \to c \in [a,b].

Since ff is continuous at cc: f(xnk)→f(c)f(x_{n_k}) \to f(c).

But ∣f(xnk)∣>nk→∞|f(x_{n_k})| > n_k \to \infty, contradiction. ∎

∎
Example 1.1: Verifying Boundedness

Show f(x) = sin(x)/x on [1, 10] is bounded.

Solution:

f is continuous on [1, 10] (ratio of continuous functions, denominator ≠ 0).

By Boundedness Theorem, f is bounded. Since |sin x| ≤ 1 and x ≥ 1, we have |f(x)| ≤ 1.

Section 2: Extreme Value Theorem

Theorem 2.1: Extreme Value Theorem (EVT)

If f∈C[a,b]f \in C[a, b], then ff attains its maximum and minimum on [a,b][a, b]:

∃xm,xM∈[a,b]:f(xm)=min⁡x∈[a,b]f(x),f(xM)=max⁡x∈[a,b]f(x)\exists x_m, x_M \in [a, b]: f(x_m) = \min_{x \in [a,b]} f(x), \quad f(x_M) = \max_{x \in [a,b]} f(x)
Proof of Theorem 2.1:

By Boundedness Theorem, M=sup⁡x∈[a,b]f(x)M = \sup_{x \in [a,b]} f(x) exists and is finite.

By supremum property, ∃xn∈[a,b]\exists x_n \in [a,b] with f(xn)→Mf(x_n) \to M.

By Bolzano-Weierstrass, xnk→xM∈[a,b]x_{n_k} \to x_M \in [a,b].

By continuity, f(xM)=lim⁡f(xnk)=Mf(x_M) = \lim f(x_{n_k}) = M. Similarly for minimum. ∎

∎
Example 2.1: Finding Extrema

Find max and min of f(x) = x³ - 3x on [-2, 2].

Solution:

f is continuous on [-2, 2], so by EVT, max and min exist.

f'(x) = 3x² - 3 = 3(x² - 1) = 0 when x = ±1.

Check: f(-2) = -8 + 6 = -2, f(-1) = -1 + 3 = 2, f(1) = 1 - 3 = -2, f(2) = 8 - 6 = 2.

Max = 2 at x = -1 and x = 2, Min = -2 at x = -2 and x = 1.

Section 3: Intermediate Value Theorem

Theorem 3.1: Intermediate Value Theorem (IVT)

If f∈C[a,b]f \in C[a, b] and kk is between f(a)f(a) and f(b)f(b), then:

∃c∈(a,b):f(c)=k\exists c \in (a, b): f(c) = k
Corollary 3.1: Bolzano's Theorem (Zero Theorem)

If f∈C[a,b]f \in C[a, b] and f(a)⋅f(b)<0f(a) \cdot f(b) < 0 (opposite signs), then:

∃c∈(a,b):f(c)=0\exists c \in (a, b): f(c) = 0
Proof of Corollary 3.1 (Bisection):

WLOG f(a)<0<f(b)f(a) < 0 < f(b). Let c=(a+b)/2c = (a+b)/2.

If f(c)=0f(c) = 0, done. If f(c)>0f(c) > 0, apply to [a,c][a, c]. If f(c)<0f(c) < 0, apply to [c,b][c, b].

Get nested intervals [an,bn][a_n, b_n] with bn−an=(b−a)/2n→0b_n - a_n = (b-a)/2^n \to 0.

By completeness, an,bn→ca_n, b_n \to c. By continuity, f(c)=0f(c) = 0. ∎

∎
Example 3.1: Root Finding

Show: x3+x−1=0x^3 + x - 1 = 0 has a root in (0,1)(0, 1).

Let f(x)=x3+x−1f(x) = x^3 + x - 1. Then f(0)=−1<0f(0) = -1 < 0 and f(1)=1>0f(1) = 1 > 0.

By Bolzano's theorem, ∃c∈(0,1)\exists c \in (0, 1) with f(c)=0f(c) = 0.

Section 4: Uniform Continuity

Definition 4.1: Uniform Continuity

ff is uniformly continuous on DD if:

∀ε>0,∃δ>0:∀x,y∈D,∣x−y∣<δ⇒∣f(x)−f(y)∣<ε\forall \varepsilon > 0, \exists \delta > 0: \forall x, y \in D, |x - y| < \delta \Rightarrow |f(x) - f(y)| < \varepsilon

Key: the same δ\delta works for ALL x,yx, y in DD.

Theorem 4.1: Heine-Cantor Theorem

If f∈C[a,b]f \in C[a, b], then ff is uniformly continuous on [a,b][a, b].

Proof of Theorem 4.1 (by contradiction):

Suppose not. Then ∃ε0>0\exists \varepsilon_0 > 0 such that ∀δ>0\forall \delta > 0, ∃x,y\exists x, y with ∣x−y∣<δ|x - y| < \delta but ∣f(x)−f(y)∣≥ε0|f(x) - f(y)| \geq \varepsilon_0.

Take δ=1/n\delta = 1/n. Get sequences xn,ynx_n, y_n with ∣xn−yn∣<1/n|x_n - y_n| < 1/n but ∣f(xn)−f(yn)∣≥ε0|f(x_n) - f(y_n)| \geq \varepsilon_0.

By Bolzano-Weierstrass, xnk→c∈[a,b]x_{n_k} \to c \in [a,b]. Then ynk→cy_{n_k} \to c too.

By continuity: f(xnk)→f(c)f(x_{n_k}) \to f(c) and f(ynk)→f(c)f(y_{n_k}) \to f(c), so ∣f(xnk)−f(ynk)∣→0|f(x_{n_k}) - f(y_{n_k})| \to 0. Contradiction! ∎

∎
Example 4.1: Non-Uniform Continuity

Show: f(x)=1/xf(x) = 1/x is NOT uniformly continuous on (0,1)(0, 1).

Take ε=1\varepsilon = 1. For any δ>0\delta > 0, let x=δ/2x = \delta/2, y=δ/4y = \delta/4.

Then ∣x−y∣=δ/4<δ|x - y| = \delta/4 < \delta, but ∣f(x)−f(y)∣=2/δ→∞|f(x) - f(y)| = 2/\delta \to \infty as δ→0\delta \to 0.

Section 5: Lipschitz Continuity

Definition 5.1: Lipschitz Function

A function f:D→Rf: D \to \mathbb{R} is Lipschitz continuous if there exists L>0L > 0 such that:

∣f(x)−f(y)∣≤L∣x−y∣∀x,y∈D|f(x) - f(y)| \leq L|x - y| \quad \forall x, y \in D

The smallest such LL is called the Lipschitz constant.

Theorem 5.1: Lipschitz Implies Uniform Continuity

If ff is Lipschitz continuous, then ff is uniformly continuous.

Proof:

Given ε>0\varepsilon > 0, take δ=ε/L\delta = \varepsilon/L.

Then ∣x−y∣<δ⇒∣f(x)−f(y)∣≤L∣x−y∣<L⋅εL=ε|x - y| < \delta \Rightarrow |f(x) - f(y)| \leq L|x - y| < L \cdot \frac{\varepsilon}{L} = \varepsilon.

∎
Example 5.1: Lipschitz Examples
  • f(x)=xf(x) = x is Lipschitz with L=1L = 1
  • f(x)=∣x∣f(x) = |x| is Lipschitz with L=1L = 1
  • f(x)=sin⁡xf(x) = \sin x is Lipschitz with L=1L = 1 (by Mean Value Theorem)
  • f(x)=xf(x) = \sqrt{x} on [1,∞)[1, \infty) is NOT Lipschitz

Section 6: Fixed Point Theorem

Definition 6.1: Fixed Point

A point cc is a fixed point of ff if f(c)=cf(c) = c.

Theorem 6.1: Brouwer Fixed Point Theorem (1D)

If f:[a,b]→[a,b]f: [a, b] \to [a, b] is continuous, then ff has at least one fixed point.

Proof:

Consider g(x)=f(x)−xg(x) = f(x) - x. Then g(a)=f(a)−a≥0g(a) = f(a) - a \geq 0 and g(b)=f(b)−b≤0g(b) = f(b) - b \leq 0.

By Intermediate Value Theorem, ∃c∈[a,b]\exists c \in [a, b] with g(c)=0g(c) = 0, i.e., f(c)=cf(c) = c.

∎
Example 6.1: Application

The function f(x)=cos⁡xf(x) = \cos x on [0,1][0, 1] maps into [cos⁡1,1]⊂[0,1][\cos 1, 1] \subset [0, 1], so it has a fixed point.

Section 7: Continuity and Limits

Theorem 7.1: Continuity via Limits

A function ff is continuous at x0x_0 if and only if:

lim⁡x→x0f(x)=f(x0)\lim_{x \to x_0} f(x) = f(x_0)
Theorem 7.2: Composition of Continuous Functions

If ff is continuous at x0x_0 and gg is continuous at f(x0)f(x_0), then g∘fg \circ f is continuous at x0x_0.

Example 7.1: Composition

Since f(x)=x2f(x) = x^2 and g(x)=sin⁡xg(x) = \sin x are continuous, (g∘f)(x)=sin⁡(x2)(g \circ f)(x) = \sin(x^2) is continuous.

Work These Ideas by Hand — Then Check Yourself

Practice Quiz: Continuity Theorems
10
Questions
0
Correct
0%
Accuracy
1
The Intermediate Value Theorem requires ff to be:
Easy
Not attempted
2
If f∈C[a,b]f \in C[a,b] with f(a)<0<f(b)f(a) < 0 < f(b), then:
Easy
Not attempted
3
The Extreme Value Theorem states that f∈C[a,b]f \in C[a,b]:
Medium
Not attempted
4
Uniform continuity means:
Medium
Not attempted
5
Is f(x)=1/xf(x) = 1/x uniformly continuous on (0,1)(0,1)?
Hard
Not attempted
6
If f∈C[a,b]f \in C[a,b], then ff is:
Easy
Not attempted
7
The Boundedness Theorem requires:
Easy
Not attempted
8
If ff is Lipschitz continuous, then:
Medium
Not attempted
9
Bolzano's theorem is a special case of:
Medium
Not attempted
10
On which interval is f(x)=x2f(x) = x^2 uniformly continuous?
Hard
Not attempted
Advertisement

Frequently Asked Questions

Why must the interval be closed for EVT?

On open intervals, f can 'escape to infinity' near endpoints. Example: f(x) = 1/x on (0,1) is continuous but has no max.

What's the difference between continuity and uniform continuity?

Continuity: for each x₀ and ε, find δ (may depend on x₀). Uniform: for each ε, find δ that works for ALL x simultaneously.

How is IVT used to find roots?

If f(a) and f(b) have opposite signs and f is continuous, there's a root in (a,b). Bisection method repeatedly applies this.

Does IVT guarantee uniqueness of roots?

No! IVT only proves existence. A function can have multiple roots. Example: sin x = 0 has infinitely many solutions.

What is the Heine-Cantor theorem?

If f is continuous on a closed bounded interval [a,b], then f is uniformly continuous on [a,b]. This is a fundamental result connecting continuity and uniform continuity.