analysis (differential/integral calculus, functional analysis, topology)
metric space, normed vector space
open ball, open subset, neighbourhood
convergence, limit of a sequence
compactness, sequential compactness
continuous metric space valued function on compact metric space is uniformly continuous
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higher geometry / derived geometry
geometric little (∞,1)-toposes
geometric big (∞,1)-toposes
derived smooth geometry
The concept of Euclidean space in analysis, topology and differential geometry and specifically Euclidean geometry is a fomalization in modern terms of the spaces studied in Euclid 300BBC, equipped with the structures that Euclid recognised his spaces as having.
In the strict sense of the word, Euclidean space $E^n$ of dimension $n$ is, up to isometry, the metric space whose underlying set is the Cartesian space $\mathbb{R}^n$ and whose distance function $d$ is given by the Euclidean norm:
(In Euclid 300BC this is considered for $n = 3$.)
This means that in a Euclidean space one may construct for instance the unit sphere around any point, or the shortest curve connecting any two points. These are the operations studied in (Euclid 300BC), see at Euclidean geometry.
Of course these operations may be considered in every (other) metric space, too, see at non-Euclidean geometry. Euclidean geometry is distinguished notably from elliptic geometry or hyperbolic geometry by the fact that it satisfies the parallel postulate.
In regarding $E^n = (\mathbb{R}^n, d_{Eucl})$ (only) as a metric space, some extra structure still carried by $\mathbb{R}^n$ is disrgarded, such as its vector space structure, hence its affine structure? and its canonical inner product space structure. Sometimes “Euclidean space” is used to refer to $E^n$ with that further extra structure remembered.
Retaining the inner product on top of the metric space structure means that on top of distances one may also speak of angles in a Euclidean space.
Then of course $\mathbb{R}^n$ carries also non-canonical inner product space strctures, not corresponding to the Euclidean norm. Regarding $E^n$ as equipped with these one says that it is a pseudo-Euclidean space. These are now, again in the sense of Cartan geometry, the local model spaces for pseudo-Riemannian geometry.
Finally one could generalize and allow the dimension to be countably infinite, and regard seperable Hilbert spaces as generalized Eclidean spaces.
Arguably, the spaces studied by Euclid were not really modelled on inner product spaces, as the distances were lengths, not real numbers (which, if non-negative, are ratios of lengths). So we should say that $V$ has an inner product valued in some oriented line $L$ (or rather, in $L^2$). Of course, Euclid did not use the inner product (which takes negative values) directly, but today we can recover it from what Euclid did discuss: lengths (valued in $L$) and angles (dimensionless).
Since the days of René Descartes, it is common to identify a Euclidean space with a Cartesian space, that is $\mathbb{R}^n$ for $n$ the dimension. But Euclid's spaces had no coordinates; and in any case, what we do with them is still coordinate-independent.
Given two points $x$ and $y$ of a Euclidean space $E$, their difference $x - y$ belongs to the vector space $V$, where it has a norm
This real number (or properly, element of the line $L$) is the distance between $x$ and $y$, or the length of the line segment $\overline{x y}$. This distance function makes $E$ into an ($L$-valued) metric space.
Given three points $x, y, z$, with $x, y \ne z$ (so that ${\|x - z\|}, {\|y - z\|} \ne 0$), we can form the ratio
which is a (dimensionless) real number. By the Cauchy–Schwartz inequality, this number lies between $-1$ and $1$, so it's the cosine? of a unique angle measure between $0$ and $\pi$ radians. This is the measure of the angle $\angle x z y$. In a $2$-dimensional Euclidean space, we can interpret $\angle x z y$ as a signed angle (so taking values anywhere on the unit circle) if we fix an orientation of $E$.
Conversely, knowing angles and lengths, we may recover the inner product on $V$;
and other inner products are recovered by linearity. (We must then use the axioms of Euclidean geometry to prove that this is well defined and actually an inner product.) It’s actually possible to recover the inner product and angles from lengths alone; this is discussed at Hilbert space.