Euclidean space is the fundamental space of classical geometry
. Originally it was the three-dimensional space
of Euclidean geometry
, but in modern mathematics
there are Euclidean spaces of any nonnegative integer dimension
, including the three-dimensional space and the ''Euclidean plane'' (dimension two). It was introduced by the Ancient Greek
mathematician Euclid of Alexandria
, and the qualifier ''Euclidean'' is used to distinguish it from other spaces that were later discovered in physics
and modern mathematics.
Ancient Greek geometers
introduced Euclidean space for modeling the physical universe
. Their great innovation was to ''prove
'' all properties of the space as theorem
s by starting from a few fundamental properties, called ''postulate
s'', which either were considered as evident (for example, there is exactly one straight line
passing through two points), or seemed impossible to prove (parallel postulate
After the introduction at the end of 19th century of non-Euclidean geometries
, the old postulates were re-formalized to define Euclidean spaces through axiomatic theory
. Another definition of Euclidean spaces by means of vector space
s and linear algebra
has been shown to be equivalent to the axiomatic definition. It is this definition that is more commonly used in modern mathematics, and detailed in this article.
In all definitions, Euclidean spaces consist of points, which are defined only by the properties that they must have for forming a Euclidean space.
There is essentially only one Euclidean space of each dimension; that is, all Euclidean spaces of a given dimension are isomorphic
. Therefore, in many cases, it is possible to work with a specific Euclidean space, which is generally the real -space
equipped with the dot product
. An isomorphism from a Euclidean space to
associates with each point an -tuple
of real number
s which locate that point in the Euclidean space and are called the ''Cartesian coordinates
'' of that point.
History of the definition
Euclidean space was introduced by ancient Greeks
as an abstraction of our physical space. Their great innovation, appearing in Euclid's ''Elements''
was to build and ''prove
'' all geometry by starting from a few very basic properties, which are abstracted from the physical world, and cannot be mathematically proved because of the lack of more basic tools. These properties are called postulate
s, or axiom
s in modern language. This way of defining Euclidean space is still in use under the name of synthetic geometry
In 1637, René Descartes
introduced Cartesian coordinates
and showed that this allows reducing geometric problems to algebraic computations with numbers. This reduction of geometry to algebra
was a major change of point of view, as, until then, the real number
s—that is, rational number
s and non-rational numbers together–were defined in terms of geometry, as lengths and distance.
Euclidean geometry was not applied in spaces of more than three dimensions until the 19th century. Ludwig Schläfli
generalized Euclidean geometry to spaces of ''n'' dimensions using both synthetic and algebraic methods, and discovered all of the regular polytope
s (higher-dimensional analogues of the Platonic solid
s) that exist in Euclidean spaces of any number of dimensions.
Despite the wide use of Descartes' approach, which was called analytic geometry
, the definition of Euclidean space remained unchanged until the end of 19th century. The introduction of abstract vector space
s allowed their use in defining Euclidean spaces with a purely algebraic definition. This new definition has been shown to be equivalent to the classical definition in terms of geometric axioms. It is this algebraic definition that is now most often used for introducing Euclidean spaces.
Motivation of the modern definition
One way to think of the Euclidean plane is as a set
s satisfying certain relationships, expressible in terms of distance and angles. For example, there are two fundamental operations (referred to as motions
) on the plane. One is translation
, which means a shifting of the plane so that every point is shifted in the same direction and by the same distance. The other is rotation
around a fixed point in the plane, in which all points in the plane turn around that fixed point through the same angle. One of the basic tenets of Euclidean geometry is that two figures (usually considered as subset
s) of the plane should be considered equivalent (congruent
) if one can be transformed into the other by some sequence of translations, rotations and reflection
s (see below
In order to make all of this mathematically precise, the theory must clearly define what is a Euclidean space, and the related notions of distance, angle, translation, and rotation. Even when used in physical
theories, Euclidean space is an abstraction
detached from actual physical locations, specific reference frames
, measurement instruments, and so on. A purely mathematical definition of Euclidean space also ignores questions of units of length
and other physical dimensions
: the distance in a "mathematical" space is a number
, not something expressed in inches or metres.
The standard way to mathematically define a Euclidean space, as carried out in the remainder of this article, is to define a Euclidean space as a set of points on which acts
a real vector space
, the ''space of translations'' which is equipped with an inner product
. The action of translations makes the space an affine space
, and this allows defining lines, planes, subspaces, dimension, and parallelism
. The inner product allows defining distance and angles.
of -tuples of real numbers equipped with the dot product
is a Euclidean space of dimension . Conversely, the choice of a point called the ''origin'' and an orthonormal basis
of the space of translations is equivalent with defining an isomorphism
between a Euclidean space of dimension and
viewed as a Euclidean space.
It follows that everything that can be said about a Euclidean space can also be said about
Therefore, many authors, specially at elementary level, call
the ''standard Euclidean space'' of dimension , or simply ''the'' Euclidean space of dimension .
A reason for introducing such an abstract definition of Euclidean spaces, and for working with it instead of
is that it is often preferable to work in a ''coordinate-free'' and ''origin-free'' manner (that is, without choosing a preferred basis and a preferred origin). Another reason is that there is no origin nor any basis in the physical world.
A is a finite-dimensional inner product space
over the real number
A Euclidean space is an affine space
over the reals
such that the associated vector space is a Euclidean vector space. Euclidean spaces are sometimes called ''Euclidean affine spaces'' for distinguishing them from Euclidean vector spaces.
If is a Euclidean space, its associated vector space is often denoted
The ''dimension'' of a Euclidean space is the dimension
of its associated vector space.
The elements of are called ''points'' and are commonly denoted by capital letters. The elements of
are called ''Euclidean vector
s'' or ''free vector
s''. They are also called ''translations'', although, properly speaking, a translation
is the geometric transformation
resulting of the action
of a Euclidean vector on the Euclidean space.
The action of a translation on a point provides a point that is denoted . This action satisfies
(The second in the left-hand side is a vector addition; all other denote an action of a vector on a point. This notation is not ambiguous, as, for distinguishing between the two meanings of , it suffices to look on the nature of its left argument.)
The fact that the action is free and transitive means that for every pair of points there is exactly one vector such that . This vector is denoted or
As previously explained, some of the basic properties of Euclidean spaces result of the structure of affine space. They are described in and its subsections. The properties resulting from the inner product are explained in and its subsections.
For any vector space, the addition acts freely and transitively on the vector space itself. Thus a Euclidean vector space can be viewed as a Euclidean space that has itself as associated vector space.
A typical case of Euclidean vector space is
viewed as a vector space equipped with the dot product
as an inner product
. The importance of this particular example of Euclidean space lies in the fact that every Euclidean space is isomorphic
to it. More precisely, given a Euclidean space of dimension , the choice of a point, called an ''origin'' and an orthonormal basis
defines an isomorphism of Euclidean spaces from to
As every Euclidean space of dimension is isomorphic to it, the Euclidean space
is sometimes called the ''standard Euclidean space'' of dimension .
Some basic properties of Euclidean spaces depend only of the fact that a Euclidean space is an affine space
. They are called affine properties
and include the concepts of lines, subspaces, and parallelism, which are detailed in next subsections.
Let be a Euclidean space and
its associated vector space.
A ''flat'', ''Euclidean subspace'' or ''affine subspace'' of is a subset of such that
is a linear subspace
A Euclidean subspace is a Euclidean space with
as associated vector space. This linear subspace
is called the ''direction'' of .
If is a point of then
Conversely, if is a point of and is a linear subspace
is a Euclidean subspace of direction .
A Euclidean vector space (that is, a Euclidean space such that
) has two sorts of subspaces: its Euclidean subspaces and its linear subspaces. Linear subspaces are Euclidean subspaces and a Euclidean subspace is a linear subspace if and only if it contains the zero vector.
Lines and segments
In a Euclidean space, a ''line'' is a Euclidean subspace of dimension one. Since a vector space of dimension one is spanned by any nonzero vector a line is a set of the form
where and are two distinct points.
It follows that ''there is exactly one line that passes through (contains) two distinct points.'' This implies that two distinct lines intersect in at most one point.
A more symmetric representation of the line passing through and is
where is an arbitrary point (not necessary on the line).
In a Euclidean vector space, the zero vector is usually chosen for ; this allows simplifying the preceding formula into
A standard convention allows using this formula in every Euclidean space, see .
The ''line segment
'', or simply ''segment'', joining the points and is the subset of the points such that in the preceding formulas. It is denoted or ; that is
Two subspaces and of the same dimension in a Euclidean space are ''parallel'' if they have the same direction. Equivalently, they are parallel, if there is a translation vector that maps one to the other:
Given a point and a subspace , there exists exactly one subspace that contains and is parallel to , which is
In the case where is a line (subspace of dimension one), this property is Playfair's axiom
It follows that in a Euclidean plane, two lines either meet in one point or are parallel.
The concept of parallel subspaces has been extended to subspaces of different dimensions: two subspaces are parallel if the direction of one of them is contained in the direction to the other.
The vector space
associated to a Euclidean space is an inner product space
. This implies a symmetric bilinear form
that is positive definite
is always positive for ).
The inner product of a Euclidean space is often called ''dot product'' and denoted . This is specially the case when a Cartesian coordinate system
has been chosen, as, in this case, the inner product of two vectors is the dot product
of their coordinate vector
s. For this reason, and for historical reasons, the dot notation is more commonly used than the bracket notation for the inner product of Euclidean spaces. This article will follow this usage; that is
will be denoted in the remainder of this article.
The Euclidean norm of a vector is
The inner product and the norm allows expressing and proving all metric
properties of Euclidean geometry
. The next subsection describe the most fundamental ones. ''In these subsections,'' ''denotes an arbitrary Euclidean space, and
denotes its vector space of translations.''
Distance and length
The ''distance'' (more precisely the ''Euclidean distance'') between two points of a Euclidean space is the norm of the translation vector that maps one point to the other; that is
The ''length'' of a segment is the distance between its endpoints. It is often denoted
The distance is a metric
, as it is positive definite, symmetric, and satisfies the triangle inequality
Moreover, the equality is true if and only if belongs to the segment .
This inequality means that the length of any edge of a triangle
is smaller than the sum of the lengths of the other edges. This is the origin of the term ''triangle inequality''.
With the Euclidean distance, every Euclidean space is a complete metric space
Two nonzero vectors and of
are ''perpendicular'' or ''orthogonal'' if their inner product is zero:
Two linear subspaces of
are orthogonal if every nonzero vector of the first one is perpendicular to every nonzero vector of the second one. This implies that the intersection of the linear subspace is reduced to the zero vector.
Two lines, and more generally two Euclidean subspaces are orthogonal if their direction are orthogonal. Two orthogonal lines that intersect are said ''perpendicular''.
Two segments and that share a common endpoint are ''perpendicular'' or ''form a right angle
'' if the vectors
If and form a right angle, one has
This is the Pythagorean theorem
. Its proof is easy in this context, as, expressing this in terms of the inner product, one has, using bilinearity and symmetry of the inner product:
The (non-oriented) ''angle'' between two nonzero vectors and in
where is the principal value
of the arccosine
function. By Cauchy–Schwarz inequality
, the argument of the arccosine is in the interval . Therefore is real, and (or } if angles are measured in degrees).
Angles are not useful in a Euclidean line, as they can be only 0 or '.
In an oriented
Euclidean plane, one can define the ''oriented angle'' of two vectors. The oriented angle of two vectors and is then the opposite of the oriented angle of and . In this case, the angle of two vectors can have any value modulo
an integer multiple of . In particular, a reflex angle
equals the negative angle .
The angle of two vectors does not change if they are multiplied
by positive numbers. More precisely, if and are two vectors, and and are real numbers, then
If and are three points in a Euclidean space, the angle of the segments and is the angle of the vectors
As the multiplication of vectors by positive numbers do not change the angle, the angle of two half-line
s with initial point can be defined: it is the angle of the segments and , where and are arbitrary points, one on each half-line. Although this is less used, one can define similarly the angle of segments or half-lines that do not share an initial points.
The angle of two lines is defined as follows. If is the angle of two segments, one on each line, the angle of any two other segments, one on each line, is either or . One of these angles is in the interval
, and the other being in . The ''non-oriented angle'' of the two lines is the one in the interval . In an oriented Euclidean plane, the ''oriented angle'' of two lines belongs to the interval .
Every Euclidean vector space has an orthonormal basis
(in fact, infinitely many in dimension higher than one, and two in dimension one), that is a basis
of unit vector
) that are pairwise orthogonal (
for ). More precisely, given any basis
the Gram–Schmidt process
computes an orthonormal basis such that, for every , the linear span
Given a Euclidean space , a ''Cartesian frame'' is a set of data consisting of an orthonormal basis of
and a point of , called the ''origin'' and often denoted . A Cartesian frame
allows defining Cartesian coordinates for both and
in the following way.
The Cartesian coordinates of a vector are the coefficients of on the basis
As the basis is orthonormal, the th coefficient is the dot product
The Cartesian coordinates of a point of are the Cartesian coordinates of the vector
192px|3-dimensional skew coordinates
As a Euclidean space is an affine space
, one can consider an affine frame
on it, which is the same as a Euclidean frame, except that the basis is not required to be orthonormal. This define affine coordinates
, sometimes called ''skew coordinates'' for emphasizing that the basis vectors are not pairwise orthogonal.
An affine basis
of a Euclidean space of dimension is a set of points that are not contained in a hyperplane. An affine basis define barycentric coordinates
for every point.
Many other coordinates systems can be defined on a Euclidean space of dimension , in the following way. Let be a homeomorphism
(or, more often, a diffeomorphism
) from a dense open subset
of to an open subset of
The ''coordinates'' of a point of are the components of . The polar coordinate system
(dimension 2) and the spherical
coordinate systems (dimension 3) are defined this way.
For points that are outside the domain of , coordinates may sometimes be defined as the limit of coordinates of neighbour points, but these coordinates may be not uniquely defined, and may be not continuous in the neighborhood of the point. For example, for the spherical coordinate system, the longitude is not defined at the pole, and on the antimeridian
, the longitude passes discontinuously from –180° to +180°.
This way of defining coordinates extends easily to other mathematical structures, and in particular to manifold
between two metric space
s is a bijection preserving the distance, that is
In the case of a Euclidean vector space, an isometry that maps the origin to the origin preserves the norm
since the norm of a vector is its distance from the zero vector. It preserves also the inner product
An isometry of Euclidean vector spaces is a linear isomorphism
of Euclidean spaces defines an isometry
of the associated Euclidean vector spaces. This implies that two isometric Euclidean spaces have the same dimension. Conversely, if and are Euclidean spaces, , , and
is an isometry, then the map
is an isometry of Euclidean spaces.
It follows from the preceding results that an isometry of Euclidean spaces maps lines to lines, and, more generally Euclidean subspaces to Euclidean subspaces of the same dimension, and that the restriction of the isometry on these subspaces are isometries of these subspaces.
Isometry with prototypical examples
If is a Euclidean space, its associated vector space
can be considered as a Euclidean space. Every point defines an isometry of Euclidean spaces
which maps to the zero vector and has the identity as associated linear map. The inverse isometry is the map
A Euclidean frame allows defining the map
which is an isometry of Euclidean spaces. The inverse isometry is
''This means that, up to an isomorphism, there is exactly one Euclidean space of a given dimension.''
This justifies that many authors talk of
as ''the'' Euclidean space of dimension .
An isometry from a Euclidean space onto itself is called ''Euclidean isometry'', ''Euclidean transformation'' or ''rigid transformation''. The rigid transformations of a Euclidean space form a group (under composition
), called the ''Euclidean group'' and often denoted of .
The simplest Euclidean transformations are translations
They are in bijective correspondence with vectors. This is a reason for calling ''space of translations'' the vector space associated to a Euclidean space. The translations form a normal subgroup
of the Euclidean group.
A Euclidean isometry of a Euclidean space defines a linear isometry
of the associated vector space (by ''linear isometry'', it is meant an isometry that is also a linear map
) in the following way: denoting by the vector
, if is an arbitrary point of , one has
It is straightforward to prove that this is a linear map that does not depend from the choice of
is a group homomorphism
from the Euclidean group onto the group of linear isometries, called the orthogonal group
. The kernel of this homomorphism is the translation group, showing that it is a normal subgroup of the Euclidean group.
The isometries that fix a given point form the stabilizer subgroup
of the Euclidean group with respect to . The restriction to this stabilizer of above group homomorphism is an isomorphism. So the isometries that fix a given point form a group isomorphic to the orthogonal group.
Let be a point, an isometry, and the translation that maps to . The isometry
fixes . So
and ''the Euclidean group is the semidirect product
of the translation group and the orthogonal group.''
The special orthogonal group
is the normal subgroup of the orthogonal group that preserves handedness
. It is a subgroup of index
two of the orthogonal group. Its inverse image by the group homomorphism
is a normal subgroup of index two of the Euclidean group, which is called the ''special Euclidean group'' or the ''displacement group''. Its elements are called ''rigid motions'' or ''displacements''.
Rigid motions include the identity
, translations, rotation
s (the rigid motions that fix at least a point), and also screw motions
Typical examples of rigid transformations that are not rigid motions are reflection
s, which are rigid transformations that fix a hyperplane and are not the identity. They are also the transformations consisting in changing the sign of one coordinate over some Euclidean frame.
As the special Euclidean group is a subgroup of index two of the Euclidean group, given a reflection , every rigid transformation that is not a rigid motion is the product of and a rigid motion. A glide reflection
is an example of a rigid transformation that is not a rigid motion or a reflection.
All groups that have been considered in this section are Lie group
s and algebraic group
The Euclidean distance makes a Euclidean space a metric space
, and thus a topological space
. This topology is called the Euclidean topology
. In the case of
this topology is also the product topology
The open set
s are the subsets that contains an open ball
around each of their points. In other words, open balls form a base of the topology
The topological dimension
of a Euclidean space equals its dimension. This implies that Euclidean spaces of different dimensions are not homeomorphic
. Moreover, the theorem of invariance of domain
asserts that a subset of a Euclidean space is open (for the subspace topology
) if and only if it is homeomorphic to an open subset of a Euclidean space of the same dimension.
Euclidean spaces are complete
and locally compact
. That is, a closed subset of a Euclidean space is compact if it is bounded
(that is, contained in a ball). In particular, closed balls are compact.
The definition of Euclidean spaces that has been described in this article differs fundamentally of Euclid
's one. In reality, Euclid did not define formally the space, because it was thought as a description of the physical world that exists independently of human mind. The need of a formal definition appeared only at the end of 19th century, with the introduction of non-Euclidean geometries
Two different approaches have been used. Felix Klein
suggested to define geometries through their symmetries
. The presentation of Euclidean spaces given in this article, is essentially issued from his Erlangen program
, with the emphasis given on the groups of translations and isometries.
On the other hand, David Hilbert
proposed a set of axioms
, inspired by Euclid's postulates
. They belong to synthetic geometry
, as they do not involve any definition of real number
s. Later G. D. Birkhoff
and Alfred Tarski
proposed simpler sets of axioms, which use real number
s (see Birkhoff's axioms
and Tarski's axioms
In ''Geometric Algebra
'', Emil Artin
has proved that all these definitions of a Euclidean space are equivalent. It is rather easy to prove that all definitions of Euclidean spaces satisfy Hilbert's axioms, and that those involving real numbers (including the above given definition) are equivalent. The difficult part of Artin's proof is the following. In Hilbert's axioms, congruence
is an equivalence relation
on segments. One can thus define the ''length'' of a segment as its equivalence class. One must thus prove that this length satisfies properties that characterize nonnegative real numbers. It is what did Artin, with axioms that are not Hilbert's ones, but are equivalent.
Since ancient Greeks
, Euclidean space is used for modeling shape
s in the physical world. It is thus used in many science
s such as physics
, and astronomy
. It is also widely used in all technical areas that are concerned with shapes, figure, location and position, such as architecture
, industrial design
, or technical drawing
Space of dimensions higher than three occurs in several modern theories of physics; see Higher dimension
. They occur also in configuration space
s of physical system
Beside Euclidean geometry
, Euclidean spaces are also widely used in other areas of mathematics. Tangent space
s of differentiable manifold
s are Euclidean vector spaces. More generally, a manifold
is a space that is locally approximated by Euclidean spaces. Most non-Euclidean geometries
can be modeled by a manifold, and embedded
in a Euclidean space of higher dimension. For example, an elliptic space
can be modeled by an ellipsoid
. It is common to represent in a Euclidean space mathematics objects that are ''a priori'' not of a geometrical nature. An example among many is the usual representation of graphs
Other geometric spaces
Since the introduction, at the end of 19th century, of Non-Euclidean geometries
, many sorts of spaces have been considered, about which one can do geometric reasoning in the same way as with Euclidean spaces. In general, they share some properties with Euclidean spaces, but may also have properties that could appear as rather strange. Some of these spaces use Euclidean geometry for their definition, or can be modeled as subspaces of a Euclidean space of higher dimension. When such a space is defined by geometrical axiom
the space in a Euclidean space is a standard way for proving consistency
of its definition, or, more precisely for proving that its theory is consistent, if Euclidean geometry
is consistent (which cannot be proved).
A Euclidean space is an affine space equipped with a metric
. Affine spaces have many other uses in mathematics. In particular, as they are defined over any field
, they allow doing geometry in other contexts.
As soon as non-linear questions are considered, it is generally useful to consider affine spaces over the complex number
s as an extension of Euclidean spaces. For example, a circle
and a line
have always two intersection points (possibly not distinct) in the complex affine space. Therefore, most of algebraic geometry
is built in complex affine spaces and affine spaces over algebraically closed field
s. The shapes that are studied in algebraic geometry in these affine spaces are therefore called affine algebraic varieties
Affine spaces over the rational number
s and more generally over algebraic number field
s provide a link between (algebraic) geometry and number theory
. For example, the Fermat's Last Theorem
can be stated "a Fermat curve
of degree higher than two has no point in the affine plane over the rationals."
Geometry in affine spaces over a finite fields
has also been widely studied. For example, elliptic curve
s over finite fields are widely used in cryptography
Originally, projective spaces have been introduced by adding "points at infinity
" to Euclidean spaces, and, more generally to affine spaces, in order to make true the assertion "two coplanar
lines meet in exactly one point". Projective space share with Euclidean and affine spaces the property of being isotropic
, that is, there is no property of the space that allows distinguishing between two points or two lines. Therefore, a more isotropic definition is commonly used, which consists as defining a projective space as the set of the vector line
s in a vector space
of dimension one more.
As for affine spaces, projective spaces are defined over any field
, and are fundamental spaces of algebraic geometry
''Non-Euclidean geometry'' refers usually to geometrical spaces where the parallel postulate
is false. They include elliptic geometry
, where the sum of the angles of a triangle is more than 180°, and hyperbolic geometry
, where this sum is less than 180°. Their introduction in the second half of 19th century, and the proof that their theory is consistent
(if Euclidean geometry is not contradictory) is one of the paradoxes that are at the origin of the foundational crisis in mathematics
of the beginning of 20th century, and motivated the systematization of axiomatic theories
is a space that in the neighborhood of each point resembles a Euclidean space. In technical terms, a manifold is a topological space
, such that each point has a neighborhood
that is homeomorphic
to an open subset
of a Euclidean space. Manifold can be classified by increasing degree of this "resemblance" into topological manifold
s, differentiable manifold
s, smooth manifold
s, and analytic manifold
s. However, none of these types of "resemblance" respect distances and angles, even approximately.
Distances and angles can be defined on a smooth manifold by providing a smoothly varying
Euclidean metric on the tangent space
s at the points of the manifold (these tangent are thus Euclidean vector spaces). This results in a Riemannian manifold
. Generally, straight line
s do not exist in a Riemannian manifold, but their role is played by geodesic
s, which are the "shortest paths" between two points. This allows defining distances, which are measured along geodesics, and angles between geodesics, which are the angle of their tangents in the tangent space at their intersection. So, Riemannian manifolds behave locally like a Euclidean that has been bended.
Euclidean spaces are trivially Riemannian manifolds. An example illustrating this well is the surface of a sphere
. In this case, geodesics are arcs of great circle
, which are called orthodrome
s in the context of navigation
. More generally, the spaces of non-Euclidean geometries
can be realized as Riemannian manifolds.
The inner product
that is defined to define Euclidean spaces is a positive definite bilinear form
. If it is replaced by an indefinite quadratic form
which is non-degenerate
, one gets a pseudo-Euclidean space
A fundamental example of such a space is the Minkowski space
, which is the space-time
's special relativity
. It is a four-dimensional space, where the metric is defined by the quadratic form
where the last coordinate (''t'') is temporal, and the other three (''x'', ''y'', ''z'') are spatial.
To take gravity
into account, general relativity
uses a pseudo-Riemannian manifold
that has Minkowski spaces as tangent space
s. The curvature
of this manifold at a point is a function of the value of the gravitational field
at this point.
* Hilbert space
, a generalization to infinite dimension, used in functional analysis