Maths - Continuity

Continuity Between Metric Spaces

Even if we are mostly interested in continuity between non-metric spaces I think it helps intuition if we look at metric spaces first.

The diagram shows a function from X with a metric δ to Y with a metric ξ.

We have an open set which is a ball around x and an open set which is a ball around f(x).

For continuity, as the ball around x gets smaller we want the ball around f(x) to get smaller.

To visualise this as a function better lets draw these balls in two dimensions only: diagram
As an example of a function that is not continuous lets take a function that has value 1 when x<3 and has value 4 when x<=3. diagram

Here we can see that there is a smaller ball (open set) in Y but it doesn't have a corresponding ball (open set) in X.

So we can start to see that there is a requirement, for continuity, that open sets in Y map through f-1 to open sets in X.


Continuous Maps

A function is continuous if it doesn't jump, that is, when two inputs of the function get close to each other then the corresponding outputs of the function get close to each other.

Here we discuss the most general form of continuous map which also applies to non-metric topological spaces.

A continuous mapping implies a limited kind of reversibility, at least locally.

Definition 1

Here is one definition of continuity, based on open sets:

Let X and Y be topological spaces. A function f : X->Y is continuous if f-1(V) is open for every open set V in Y. diagram

Definition 2

Another definition of continuity, based on neighbourhoods, is equivalent to the above definition.

Let X and Y be topological spaces. A function f : X->Y is continuous if for every x∈X and every open set U containing f(x), there exists a neighbourhood V of x such that f(V)containsU. continuity diagram

More detail about continuity on page here.

Continuous Surjective Maps


Here is an extreme case of a Surjective Map which maps to a single point.

This seems to meet the requirements as there is an open set round the whole preimage. We can think of surjections which meet these requirements as 'nice surjections'.

See fibrations

Continuous Injective Maps


Here is an extreme case of a Injective Map which maps from a single point.

In this case all the open sets in the codomain need to map back to a single open set in the domain. This meets the requirements so it is a 'nice injection'.

See cofibrations

Continuity as Pullback

This diagram shows a set of points being mapped to another set of points (in red).

For that map to be continuous the pre-image of every open set must be an open set (shown as blue map in the reverse direction).


Continuity of Maps between Lattice Structures

So far we have drawn diagrams with intersections and unions (Venn diagrams) but we could also draw these in terms of logic. diagram


In this diagram the points stay within their open sets. This is a continuous map, the preimage of every open set is an open set. The intersections and unions of open sets play nicely together. diagram
This next example is not a continuous map because the preimage of A is not an open set because it includes A and A/\B but not B. We could think of this as a tear. diagram
Again this example is not a continuous map because the preimage of A is not an open set. diagram
In this example the whole space is shrunk to a point. This is a valid continuous map because the preimage A\/B is an open set. diagram


A homotopy is a function between functions with certain properties.

Let X and Y be topological spaces and f,g : X->Y be two continuous maps. Then f is said to be homotopic to g (written f~g) if there exists a map F : X×power set-> Y, called a homotopy such that F(x,0) = f(x) and F(x,1) = g(x) .


  • f~g f is said to be homotopic to g
  • power setrepresents the unit interval [0,1]
  • continuity, in this context, is defined on page here


Homotopy Lifting Property


from here
transport : Path U A B -> A -> B

That is, if we have a path from A to B and A, then B.

Composition of Paths

We want to compose these two paths:

  • p : Path A a b
  • q : Path A b c

from here

compPath (A : U) (a b c : A) (p : Path A a b) (q : Path A b c) : Path A a c =
   comp (<_> A) (p @ i)
                   [ (i = 0) ->  a
                   , (i = 1) -> q ]

Where 'comp' is a keyword with the following parameters:

  • a path in the universe.
  • the bottom of the cube we are computing.
  • a list of the sides of the cube



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see also:

Michael Robinson - Youtube from two-day short course on Applied Sheaf Theory:

  1. Lecture 1
  2. Lecture 2
  3. Lecture 3
  4. Lecture 4
  5. Lecture 5
  6. Lecture 6
  7. Lecture 7
  8. Lecture 8
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