Difference between revisions of "Euclidean space"

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The '''Euclidean space''' of dimension <math>n</math> refers to the set of points <math>(x_1, x_2, \ldots, x_n)</math>, where each <math>x_i</math> is a real number. The two-dimensional Euclidean space is the [[Cartesian plane]], and so forth. See also [[coordinate geometry]].  
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The '''Euclidean space''' of dimension <math>n</math> refers to the [[set]] of points <math>(x_1, x_2, \ldots, x_n)</math>, where each <math>x_i</math> is a [[real number]]. The two-dimensional Euclidean space is the [[Cartesian plane]], and so forth. In this representation, the study of Euclidean space is called [[coordinate geometry]].  
  
It is a [[metric space]] with respect to the [[usual distance formula|distance]] [[metric]], <math>d(\bold{x},\bold{y}) = \sqrt{(x_1-y_1)^2 + \cdots + (x_n - y_n)^2}</math>.  
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Euclidean space can also be viewed as an example of one of several more general mathematical objects.  For example, Euclidean space is a [[metric space]] with respect to the [[distance formula|distance]] [[metric]], <math>d(\bold{x},\bold{y}) = \sqrt{(x_1-y_1)^2 + \cdots + (x_n - y_n)^2}</math>.  Similarly, the Euclidean space of dimension <math>n</math> is the unique (up to [[isomorphism]]) [[vector space]] of dimension <math>n</math> over <math>\mathbb{R}</math> (under [[pointwise addition]] and the "usual" scalar multiplication <math>c \cdot (x_1, \ldots, x_n) = (c x_1, \ldots, c x_n)</math> for <math>c, x_i \in \mathbb{R}</math>).
  
 
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[[Category:Geometry]]
 
[[Category:Geometry]]

Latest revision as of 11:46, 13 March 2010

The Euclidean space of dimension $n$ refers to the set of points $(x_1, x_2, \ldots, x_n)$, where each $x_i$ is a real number. The two-dimensional Euclidean space is the Cartesian plane, and so forth. In this representation, the study of Euclidean space is called coordinate geometry.

Euclidean space can also be viewed as an example of one of several more general mathematical objects. For example, Euclidean space is a metric space with respect to the distance metric, $d(\bold{x},\bold{y}) = \sqrt{(x_1-y_1)^2 + \cdots + (x_n - y_n)^2}$. Similarly, the Euclidean space of dimension $n$ is the unique (up to isomorphism) vector space of dimension $n$ over $\mathbb{R}$ (under pointwise addition and the "usual" scalar multiplication $c \cdot (x_1, \ldots, x_n) = (c x_1, \ldots, c x_n)$ for $c, x_i \in \mathbb{R}$).

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