Neighbourhood (mathematics)
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- See also the concepts of neighbour and neighbourhood in graph theory.
This concept is closely related to the concepts of open set and interior.
Definition
If X is a topological space and p is a point in X, a neighbourhood of p is a set V, which contains an open set U containing p.
- [p \in U \subseteq V]
If S is a subset of X, a neighbourhood of S is a set V, which contains an open set U containing S. It follows that a set V is a neighbourhood of S, if and only if, it is a neighbourhood of all the points in S.
The collection of all neighbourhoods of a point is called the neighbourhood system at the point.
In a metric space
In a metric space M = (X,d), a set V is a neighbourhood of a point p if there exists an open ball with center p and radius r,
- [B_r(p) = B(p;r) = \]
V is called uniform neighbourhood of a set S if there exists a positive number r such that for all elements p of S,
- [B_r(p) = \]
Examples
Given the set of real numbers R with the usual Euclidean metric and a subset V defined as
- [V:=\bigcup_} B\big(n\,;\,\frac\big),]
Topology from neighbourhoods
The above definition is useful if the notion of open set is already defined. There is an alternative way to define a topology, by first defining the neighbourhood system, and then open sets as those sets containing a neighbourhood of each of their points.
A neighborhood system on X is the assignment of a filter N(x) (on the set X) to each x in X, such that
- the point x is an element of each U in N(x)
- each U in N(x) contains some V in N(x) such that for each y in V, U is in N(y).
Uniform neighbourhoods
In a uniform space S:=(X, δ) V is called a uniform neighbourhood of P if P is not close to X \ V, that is there exists no entourage containing P and X \ V.
Significance of neighbourhoods in analysis of real functions
Neighbourhoods in more than one dimension are generally chosen equivalent to Euclidean metrics for their symmetry and readability. But for the analysis of functions, this choice is wholly arbitrary. Other notions of distance will (as they ought to) lead to the same results in analysis, if they are properly formulated. Consider, for instance, the following notion of distance in two dimensions: let [(x,y)] be in the [\delta]-neighbourhood of [(x_0,y_0)] if and only if
- [|x - x_0| + |y - y_0| < \delta,\,]
The conclusion is that there is nothing special about the shape we assign to a neighbourhood in multiple dimensions. The important (distinguishing) requirement for neighbourhoods in analysis is much looser. See metric (mathematics) for a more thorough discussion.
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