Definition:Metric Space
Definition
A metric space $M = \struct {A, d}$ is an ordered pair consisting of:
together with:
- $(2): \quad$ a real-valued function $d: A \times A \to \R$ which acts on $A$, satisfying the metric space axioms:
| \((\text M 1)\) | $:$ | \(\ds \forall x \in A:\) | \(\ds \map d {x, x} = 0 \) | ||||||
| \((\text M 2)\) | $:$ | Triangle Inequality: | \(\ds \forall x, y, z \in A:\) | \(\ds \map d {x, y} + \map d {y, z} \ge \map d {x, z} \) | |||||
| \((\text M 3)\) | $:$ | \(\ds \forall x, y \in A:\) | \(\ds \map d {x, y} = \map d {y, x} \) | ||||||
| \((\text M 4)\) | $:$ | \(\ds \forall x, y \in A:\) | \(\ds x \ne y \implies \map d {x, y} > 0 \) |
Points of Metric Space
The elements of $A$ are called the points of the space.
Distance Function
Let $\struct {A, d}$ be a metric space.
The mapping $d: A \times A \to \R$ is referred to as a distance function on $A$.
Triangle Inequality
Axiom $\text M 2$ is referred to as the triangle inequality, as it is a generalization of the Triangle Inequality which holds on the real number line and complex plane.
Notation
Some authors use the suboptimal $M = \set {A, d}$, which leaves it conceptually unclear as to which is the set and which the metric.
This adds unnecessary complexity to the underlying axiomatic justification for the existence of the very object that is being defined.
The notation $M = \eqclass {A, \rho} {}$ can also be found.
Also see
- Pseudometric, which is the same as a metric but does not include the condition $(\text M 4)$.
- Quasimetric, which is the same as a metric but does not include the condition $(\text M 3)$.
- Results about metric spaces can be found here.
In Relation to Norms
- Metric Defines Norm iff it Preserves Linear Structure, where a homogeneous and translation invariant metric $d$ can be used to define a norm on a vector space.
- Metric Induced by Norm is Metric, where it is shown that any vector space norm can be used to define a metric:
- $\map d {x, y} = \norm {x - y}$
- Metric Induced by Norm on Normed Division Ring is Metric, where it is shown that any division ring norm can be used to define a metric:
- $\map d {x, y} = \norm {x - y}$
In Relation to Topological Spaces
- For a metric space $\struct {A, d}$, one can define the topology $\tau$ on $A$ induced by the metric $d$, thus making $\struct {A, \tau}$ a topological space. Thus topological notions carry over to metric spaces.
Sources
- 1967: George McCarty: Topology: An Introduction with Application to Topological Groups ... (previous) ... (next): Chapter $\text{III}$: Metric Spaces: The Definition
- 1975: Bert Mendelson: Introduction to Topology (3rd ed.) ... (previous) ... (next): Chapter $2$: Metric Spaces: $\S 2$: Metric Spaces: Definition $2.1$
- 1975: W.A. Sutherland: Introduction to Metric and Topological Spaces ... (previous) ... (next): $2$: Continuity generalized: metric spaces: $2.1$: Motivation: Definition $2.1.2$
- 1978: Lynn Arthur Steen and J. Arthur Seebach, Jr.: Counterexamples in Topology (2nd ed.) ... (previous) ... (next): Part $\text I$: Basic Definitions: Section $5$: Metric Spaces
- 1998: David Nelson: The Penguin Dictionary of Mathematics (2nd ed.) ... (previous) ... (next): metric space
- 1999: Theodore W. Gamelin and Robert Everist Greene: Introduction to Topology (2nd ed.) ... (previous) ... (next): One: Metric Spaces: $1$: Open and Closed Sets
- 2008: David Nelson: The Penguin Dictionary of Mathematics (4th ed.) ... (previous) ... (next): metric space
- 2014: Christopher Clapham and James Nicholson: The Concise Oxford Dictionary of Mathematics (5th ed.) ... (previous) ... (next): metric space
- 2017: Amol Sasane: A Friendly Approach to Functional Analysis ... (previous) ... (next): $\S 1.2$: Normed and Banach spaces. Normed spaces