Three dimensions in 3D. The
position vector r is parameterized by a scalar
t. At
r =
a the red line is the tangent to the curve, and the blue plane is normal to the curve. In
three dimensions, any set of three-dimensional coordinates and their corresponding basis vectors can be used to define the location of a point in space—whichever is the simplest for the task at hand may be used. Commonly, one uses the familiar
Cartesian coordinate system, or sometimes
spherical polar coordinates, or
cylindrical coordinates: : \begin{align} \mathbf{r}(t) & \equiv \mathbf{r}(x,y,z) \equiv x(t)\mathbf{\hat{e}}_x + y(t)\mathbf{\hat{e}}_y + z(t)\mathbf{\hat{e}}_z \\ & \equiv \mathbf{r}(r,\theta,\phi) \equiv r(t)\mathbf{\hat{e}}_r\big(\theta(t), \phi(t)\big) \\ & \equiv \mathbf{r}(r,\phi,z) \equiv r(t)\mathbf{\hat{e}}_r\big(\phi(t)\big) + z(t)\mathbf{\hat{e}}_z, \\ \end{align} where
t is a
parameter, owing to their rectangular or circular symmetry. These different coordinates and corresponding basis vectors represent the same position vector. More general
curvilinear coordinates could be used instead and are in contexts like
continuum mechanics and
general relativity (in the latter case one needs an additional time coordinate).
n dimensions Linear algebra allows for the abstraction of an
n-dimensional position vector. A position vector can be expressed as a linear combination of
basis vectors: :\mathbf{r} = \sum_{i=1}^n x_i \mathbf{e}_i = x_1 \mathbf{e}_1 + x_2 \mathbf{e}_2 + \dotsb + x_n \mathbf{e}_n. The
set of all position vectors forms
position space (a
vector space whose elements are the position vectors), since positions can be added (
vector addition) and scaled in length (
scalar multiplication) to obtain another position vector in the space. The notion of "space" is intuitive, since each
xi (
i = 1, 2, …,
n) can have any value, the collection of values defines a point in space. The
dimension of the position space is
n (also denoted dim(
R) =
n). The
coordinates of the vector
r with respect to the basis vectors
ei are
xi. The vector of coordinates forms the
coordinate vector or
n-
tuple (
x1,
x2, …,
xn). Each coordinate
xi may be parameterized a number of
parameters
t. One parameter
xi(
t) would describe a curved 1D path, two parameters
xi(
t1,
t2) describes a curved 2D surface, three
xi(
t1,
t2,
t3) describes a curved 3D volume of space, and so on. The
linear span of a basis set
B = {
e1,
e2, …,
en} equals the position space
R, denoted span(
B) =
R. ==Applications==