# Why is sin 1 x differentiable

## encyclopedia

Property that measures how often a function can be distinguished

In mathematical analysis, that is **smoothness** of a function is a property measured by the number of continuous derivatives it has over a given range.^{[1]}^{[2]} At least a function could be considered “smoothly” if it is differentiable everywhere (hence continuous).^{[3]} At the other end, it could also have derivatives of all orders in its domain, in which case it should be **infinitely differentiable** and referred to as **C-infinity function** (or

Function).^{[4]}

### Differentiability classes [edit]

**Differentiability class** is a classification of functions according to the properties of their derivatives. It is a measure of the highest order of derivation that exists for a function.

Consider an open crowd on the real line and a function *f* defined on this set with real values. To let *k* be a non-negative integer. The function *f* should be of (differentiability) **class C.^{k}** when the derivatives

*f*‘,

*f*″, …,

*f*

^{((k)}exist and are continuous (continuity is implied by differentiability for all derivatives with the exception of

*f*

^{((k)}). The function

*f*it is said that

**infinitely differentiable**,

**smooth**, Or from

**class**if it has derivatives of all orders.

*C.*^{∞}^{[5]}The function

*f*should be from

**class**, or

*C.*^{ω}**analytically**, if

*f*is smooth

*and*if its Taylor series expansion around a point in its domain converges to the function in a neighborhood of the point.

*C.*

^{ω}is therefore strictly included in

*C.*

^{∞}. Bump functions are examples of functions in

*C.*

^{∞}but

*Not*in the

*C.*

^{ω}.

In other words, the class *C.*^{0} consists of all continuous functions. The class *C.*^{1} consists of all differentiable functions whose derivative is continuous; such functions are called **continuously differentiable**. Thus a *C.*^{1} Function is exactly one function whose derivative exists and is of class *C.*^{0}. In general, the classes are *C. ^{k}* can be defined recursively by declaration

*C.*

^{0}be and declare the set of all continuous functions

*C.*for any positive integer

^{k}*k*be the set of all differentiable functions whose derivative is in

*C.*

^{k−1}. Specifically,

*C.*is included in

^{k}*C.*

^{k−1}for each

*k*> 0, and there are examples showing that this containment is strict (

*C.*⊊

^{k}*C.*

^{k−1}). The class

*C.*

^{∞}of infinitely differentiable functions is the intersection of the classes

*C.*how

^{k}*k*varies over the non-negative integers.

### Examples [edit]

*C.*

^{0}Function f ((x) = x for x ≥ 0 and otherwise 0.

^{2}Sin (1 / x) for x> 0.

The function

is continuous but not differentiable at x = 0, it is of class *C.*^{0}, but not of class *C.*^{1}.

The function

is differentiable, with derivative

because

oscillates as x → 0,

is not continuous at zero. Therefore,

is differentiable but not of class *C.*^{1}. Besides, if you take

((x ≠ 0) In this example it can be shown that the derivative function of a differentiable function for a compact set can be unlimited and therefore a differentiable function for a compact set may not be locally Lipschitz continuous.

The functions

where k is even, x are continuous and k times are differentiable at all. But at x = 0 they are not ((k + 1) times differentiable, so they are great *C.*^{k}, but not of class *C.*^{j} where j> k.

The exponential function is analytical and therefore falls into the class *C.*^{ω}. The trigonometric functions are also analytical wherever they are defined.

The push function

is smooth, so great *C.*^{∞}, but it is not analytical at x = ± 1 and is therefore not of class *C.*^{ω}. The function f is an example of a smooth function with compact support.

### Multivariate differentiability classes [edit]

One function

defined on an open sentence

of

I said^{[6]} be of class

on

for a positive integer

if all partial derivatives

exist and are continuous for everyone

not negative integers such that

, And everybody

. Likewise

is great

on

if the

-th order Fréchet derivative of

exists and is continuous at every point of

. The function

should be of class

or

when it's continuous

.

One function

, defined on an open sentence

of

should be great

on

for a positive integer

when all of its components

are great

, Where

are the natural projections

defined by

. It should be classy

or

if it is continuous or equivalent if all components

are continuous, on

.

### The space of *C.*^{k} Functions [edit]

To let *D.* be an open subset of the real line. The set of all *C. ^{k}* real functions defined on

*D.*is a Fréchet vector space with the countable family of Seminorms

Where *K.* varies over an increasing sequence of compact sets whose union is *D.*, and *m* = 0, 1, …, *k*.

The set of *C.*^{∞} Functions over *D.* also forms a Fréchet room. The same seminorms are used as above, except that *m* may extend over all non-negative integer values.

The above blanks appear of course in applications where functions with derivatives of certain orders are required; However, especially when examining partial differential equations, it can sometimes be more fruitful to work with the Sobolev spaces instead.

### Parametric continuity [edit]

The conditions *parametric continuity* and *geometric continuity* ((*G ^{n}*) were introduced by Brian Barsky to show that the smoothness of a curve can be measured by removing restrictions on the speed at which the parameter traces the curve.

^{[7]}

^{[8]}

^{[9]}

**Parametric continuity** is a concept applied to parametric curves that describes the smoothness of the parameter value with distance along the curve.

### Definition [edit]

A (parametric) curve

should be of class *C.*^{k}, if

exists and is continuously on

where leads at the endpoints

are considered to be unilateral derivatives (i.e. at

from right and at

from the left).

As a practical application of this concept, there must be a curve that describes the movement of an object with a time parameter *C.*^{1} Continuity - so that the object has a finite acceleration. For a smoother movement, such as For example, the way a camera takes in making a movie, higher orders of parametric continuity are required.

### Order of continuity [edit]

^{1}continuously

The different orders of parametric continuity can be described as follows:^{[10]}

*C.*^{0}: Curves are continuous*C.*^{1}: First derivatives are continuous*C.*^{2}: First and second derivatives are continuous*C.*: First through^{n}*n*The derivatives are continuous

### Geometric continuity [edit]

*G*

^{1}-Contact (circles, line)

The concept of **geometric** or **geometric continuity** was mainly applied to the conic sections (and related shapes) by mathematicians such as Leibniz, Kepler, and Poncelet. The concept was an early attempt to describe the concept of continuity, expressed by a parametric function, in terms of geometry rather than algebra.^{[11]}

The basic idea behind the geometric continuity was that the five conic sections were actually five different versions of the same shape. An ellipse tends to be a circle as the eccentricity approaches zero or a parabola as it approaches one. and a hyperbola tends to parabola when the eccentricity drops to one; it can also tend to cut lines. So there was *continuity* between the conic sections. These ideas led to other concepts of continuity. For example, if a circle and a straight line were two expressions of the same shape, perhaps a line could be thought of as a circle of infinite radius. For this to be the case, one would have to close the line by allowing the point

be a point on the circle and for

and

be identical. Such ideas were useful to the modern, algebraically defined idea of the continuity of a function and of

(For more information, see Projective Extended Real Line).^{[11]}

### Smoothness of curves and surfaces [edit]

A curve or surface can be described as having *G ^{n}* Continuity with

*n*be the increasing measure of smoothness. Consider the segments on either side of a point on a curve:

*G*^{0}: The curves touch at the connection point.*G*^{1}: The curves also have a common tangent direction at the connection point.*G*^{2}: The curves also have a common center of curvature at the connection point.

In general, *G ^{n}* There is continuity if the curves can be re-parameterized

*C.*

^{n}(parametric) continuity.

^{[12]}

^{[13]}A new parameterization of the curve is geometrically identical to the original; Only the parameter is affected.

Correspondingly two vector functions *f*((*t*) and *G*((*t*) to have *G ^{n}* Continuity if

*f*

^{((n)}((

*t*) ≠ 0 and

*f*

^{((n)}((

*t*) ≡

*kg*

^{((n)}((

*t*) for a scalar

*k*> 0 (ie if the direction, but not necessarily the size of the two vectors is the same).

While it may be obvious that a curve would require *G*^{1} Continuity in order to appear smooth, for good aesthetics, such as is sought after in architecture and sports car design, a higher degree of geometric continuity is required. For example, reflections in a body only appear smooth if the body has done so *G*^{2} Continuity.

A *Rectangle with rounded corners* (with 90 degree arcs at the four corners) *G*^{1} Continuity, but not *G*^{2} Continuity. The same applies to a *rounded cube*with octants of a sphere at the corners and quarter cylinders at the edges. If you have an editable curve with *G*^{2} Continuity is required, then cubic splines are typically chosen; These curves are often used in industrial design.

### Smoothness of piece-wise defined curves and surfaces [edit]

This department needs expansion with: Linking curve set. You can help by adding it.((August 2014) |

### Other concepts [edit]

### Relationship to analyticity [edit]

While all analytic functions are "smooth" (i.e. all derivatives are continuous) on the set on which they are analytic, examples such as bump functions (mentioned above) show that the opposite is not true for functions on the reals: there are smooth ones Real functions that are not analytical. Simple examples of functions that are smooth but never analytical can be constructed using Fourier series. Another example is the Fabius function. Although it may seem that such functions are the exception rather than the rule, it turns out that the analytic functions are very thinly distributed on the smooth ones. more strictly, the analytic functions form a meager subset of the smooth functions. In addition, for each open subset *A* The real line has smooth functions that are analytical *A* and nowhere else.

It is useful to compare the situation with the ubiquity of transcendental numbers on the real line. Both on the real line and on the set of smooth functions, the examples we have at first sight (algebraic / rational numbers and analytic functions) behave far better than most cases: the transcendental numbers and nowhere have analytic functions the full measure (your supplements are scant).

The situation described in this way stands in clear contrast to complex differentiable functions. If a complex function is differentiable only once in an open set, it is both infinitely differentiable and analytical in this set.

### Smooth partitions of the unit [edit]

In the construction of, smooth functions with given closed support are used **smooth partitions of the unit** (see *Division of the unit* and topology glossary); These are essential for the investigation of smooth manifolds, for example to show that Riemannian metrics can be defined globally based on their local existence. A simple case is that of a **Push function** on the real line, that is, a smooth function *f* that takes the value 0 outside an interval [*a*,*b*] and so that

Given a number of overlapping intervals on the line, collision functions can be constructed for each of them and for semi-infinite intervals (−∞, *c*]] and [*d*, + ∞) to cover the whole line, such that the sum of the functions is always 1.

From what has just been said, partitions of unity don’t apply to holomorphic functions; their different behavior relative to existence and analytic continuation is one of the roots of sheaf theory. In contrast, sheaves of smooth functions tend not to carry much topological information.

### Smooth functions on and between manifolds [edit]

Given a smooth manifold

, Dimensions *m*with atlas

, then a card

is **smooth** on *M.* if for all

There is a diagram

so that the withdrawal from

by

designated

is smooth as a function of

to

in a neighborhood of

(All partial derivatives up to a certain order are continuous). Note that smoothness can be checked against any preferred graph *p* in the atlas, since the smoothing requirements for the transition functions between diagrams ensure that if

is smooth around p on a graph, it will be smooth around *p* in every other table in the atlas. If instead

is a card of

to a *n*-dimensional manifold

, then *F.* is smooth if for everyone *p* ∈ *M.*there is a diagram

over *p* in the

, and a diagram

over

in the

With

, so that

is smooth as a function of **R.**^{m} to **R.**^{n}.

Smooth maps between manifolds induce linear maps between tangent spaces: e.g.

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