### Heine Definition of Continuity

A real function \(f\left( x \right)\) is said to be continuous at \(a \in \mathbb{R}\) (\(\mathbb{R}-\) is the set of real numbers), if for any sequence \(\left\{ {{x_n}} \right\}\) such that

\[\lim\limits_{n \to \infty } {x_n} = a,\]

it holds that

\[\lim\limits_{n \to \infty } f\left( {{x_n}} \right) = f\left( a \right).\]

In practice, it is convenient to use the following three conditions of continuity of a function \(f\left( x \right)\) at point \(x = a:\)

- Function \(f\left( x \right)\) is defined at \(x = a;\)
- Limit \(\lim\limits_{x \to a} f\left( x \right)\) exists;
- It holds that \(\lim\limits_{x \to a} f\left( x \right) = f\left( a \right).\)

### Cauchy Definition of Continuity \(\left(\varepsilon – \delta -\right.\) Definition)

Consider a function \(f\left( x \right)\) that maps a set \(\mathbb{R}\) of real numbers to another set \(B\) of real numbers. The function \(f\left( x \right)\) is said to be continuous at \(a \in \mathbb{R}\) if for any number \(\varepsilon \gt 0\) there exists some number \(\delta \gt 0\) such that for all \(x \in \mathbb{R}\) with

\[\left| {x – a} \right| \lt \delta ,\]

the value of \(f\left( x \right)\) satisfies:

\[\left| {f\left( x \right) – f\left( a \right)} \right| \lt \varepsilon .\]

### Definition of Continuity in Terms of Differences of Independent Variable and Function

We can also define continuity using differences of independent variable and function. The function \(f\left( x \right)\) is said to be continuous at the point \(x = a\) if the following is valid:

\[{\lim\limits_{\Delta x \to 0} \Delta y }={ \lim\limits_{\Delta x \to 0} \left[ {f\left( {a + \Delta x} \right) – f\left( a \right)} \right] }={ 0,}\]

where \(\Delta x = x – a.\)

All the definitions of continuity given above are equivalent on the set of real numbers.

A function \(f\left( x \right)\) is continuous on a given interval, if it is continuous at every point of the interval.

### Continuity Theorems

#### Theorem \(1.\)

Let the function \(f\left( x \right)\) be continuous at \(x = a\) and let \(C\) be a constant. Then the function \(Cf\left( x \right)\) is also continuous at \(x = a\).

#### Theorem \(2.\)

Let the functions \({f\left( x \right)}\) and \({g\left( x \right)}\) be continuous at \(x = a\). Then the sum of the functions \({f\left( x \right)} + {g\left( x \right)}\) is also continuous at \(x = a.\)

#### Theorem \(3.\)

Let the functions \({f\left( x \right)}\) and \({g\left( x \right)}\) be continuous at \(x = a.\) Then the product of the functions \({f\left( x \right)}{g\left( x \right)}\) is also continuous at \(x = a.\)

#### Theorem \(4.\)

Let the functions \({f\left( x \right)}\) and \({g\left( x \right)}\) be continuous at \(x = a\). Then the quotient of the functions \(\large\frac{{f\left( x \right)}}{{g\left( x \right)}} \normalsize\) is also continuous at \(x = a\) assuming that \({g\left( a \right)} \ne 0\).

#### Theorem \(5.\)

Let \({f\left( x \right)}\) be differentiable at the point \(x = a.\) Then the function \({f\left( x \right)}\) is continuous at that point.

Remark: The converse of the theorem is not true, that is, a function that is continuous at a point is not necessarily differentiable at that point.

#### Theorem \(6\) (Extreme Value Theorem).

If \({f\left( x \right)}\) is continuous on the closed, bounded interval \(\left[ {a,b} \right]\), then it is bounded above and below in that interval. That is, there exist numbers \(m\) and \(M\) such that

\[m \le f\left( x \right) \le M\]

for every \(x\) in \(\left[ {a,b} \right]\) (see Figure \(1\)).

#### Theorem \(7\) (Intermediate Value Theorem).

Let \({f\left( x \right)}\) be continuous on the closed, bounded interval \(\left[ {a,b} \right]\). Then if \(c\) is any number between \({f\left( a \right)}\) and \({f\left( b \right)}\), there is a number \({x_0}\) such that

\[f\left( {{x_0}} \right) = c.\]

The intermediate value theorem is illustrated in Figure \(2.\)

### Continuity of Elementary Functions

All elementary functions are continuous at any point where they are defined.

An elementary function is a function built from a finite number of compositions and combinations using the four operations (addition, subtraction, multiplication, and division) over basic elementary functions. The set of basic elementary functions includes:

- Algebraical polynomials \(A{x^n} + B{x^{n – 1}} + \ldots\) \(+ Kx + L;\)
- Rational fractions \(\large\frac{{A{x^n} + B{x^{n – 1}} + \ldots + Kx + L}}{{M{x^m} + N{x^{m – 1}} + \ldots + Tx + U}}\normalsize\);
- Power functions \({x^p}\);
- Exponential functions \({a^x}\);
- Logarithmic functions \({\log _a}x\);
- Trigonometric functions \(\sin x\), \(\cos x\), \(\tan x\), \(\cot x\), \(\sec x\), \(\csc x\);
- Inverse trigonometric functions \(\arcsin x\), \(\arccos x\), \(\arctan x\), \(\text{arccot }x\), \(\text{arcsec }x\), \(\text{arccsc }x\);
- Hyperbolic functions \(\sinh x\), \(\cosh x\), \(\tanh x\), \(\coth x\), \(\text{sech }x\), \(\text{csch }x\);
- Inverse hyperbolic functions \(\text{arcsinh }x\), \(\text{arccosh }x\), \(\text{arctanh }x\), \(\text{arccoth }x,\) \(\text{arcsech }x\), \(\text{arccsch }x\).

## Solved Problems

Click a problem to see the solution.

### Example 1

Using the Heine definition, prove that the function \(f\left( x \right) = {x^2}\) is continuous at any point \(x = a.\)### Example 2

Using the Heine definition, show that the function \(f\left( x \right) = \sec x\) is continuous for any \(x\) in its domain.### Example 3

Using Cauchy definition, prove that \(\lim\limits_{x \to 4} \sqrt x = 2\).### Example 4

Show that the cubic equation \(2{x^3} – 3{x^2} – 15 = 0\) has a solution in the interval \(\left( {2,3} \right)\).### Example 5

Show that the equation \({x^{1000}} + 1000x – 1 = 0\) has a root.### Example 6

Let### Example 7

If the function### Example 1.

Using the Heine definition, prove that the function \(f\left( x \right) = {x^2}\) is continuous at any point \(x = a.\)Solution.

Using the Heine definition we can write the condition of continuity as follows:

\[

{\lim\limits_{\Delta x \to 0} f\left( {a + \Delta x} \right) = f\left( a \right)\;\;\;}\kern-0.3pt

{\text{or}\;\;\lim\limits_{\Delta x \to 0} \left[ {f\left( {a + \Delta x} \right) – f\left( a \right)} \right] }

= {\lim\limits_{\Delta x \to 0} \Delta y = 0,}

\]

where \(\Delta x\) and \(\Delta y\) are small numbers shown in Figure \(3.\)

At any point \(x = a:\)

\[{f\left( a \right) = {a^2},\;\;\;}\kern-0.3pt{f\left( {a + \Delta x} \right) = {\left( {a + \Delta x} \right)^2}.}\]

So that

\[\require{cancel}

{\Delta y = f\left( {a + \Delta x} \right) – f\left( a \right) }

= {{\left( {a + \Delta x} \right)^2} – {a^2} }

= {\cancel{a^2} + 2a\Delta x + {\left( {\Delta x} \right)^2} – \cancel{a^2} }

= {2a\Delta x + {\left( {\Delta x} \right)^2}.}

\]