The best known example of one manifold covering another manifold is provided by the earth’s daily rotation over a clock whose hour hand rotates twice over the circle in that period, or whose minute hand rotation is covered 24 times over the same, etc., so that every point of the latter, with a non-vanishing neighborhood, is mapped on two or 24 points on the former. Thus the question arises whether a manifold less trivial than a circle, can also cover another similar manifold more than once.
  2.1. Unitary Matrices Cover Orthogonal Matrices
To see and prove the cover provided by spin over rotations, it is sufficient to provide a map between a subset of complex 
 and a subset of 
 orthogonal matrices:
Upon writing out the complex numbers 
 and 
, we see that 
 is a 3-sphere or, if we write 
, we recognize it as the boundary (for 
), and twice the center (for 
) and the interior (for 
) of a 2-sphere. The 2:1 map (
3) is quadratic and covers twice that set of real 
 matrices. The former is the set of all 
 unitary matrices of unit determinant: 
, that form the group of 
special (
) 
unitary matrices denoted 
, covering 2:1 the group of 
special (
) 
orthogonal matrices 
, denoted 
. (We indicate complex conjugation by 
, matrix transposition by 
, and matrix adjunction by 
.) These matrices will apply to and rotate 3-vectors 
 respecting their magnitude 
.
Most importantly, the map (
3) preserves the group properties between the 
 and 
 matrices:
        while the unit is 
, all inverses 
 exist, and associativity holds as it does for all matrices.
The  manifold is a 3-sphere which is simply connected, as all spheres are; this means that any closed path in the manifold can be contracted to a point. The  manifold on the other hand can be visualized as the interior of a 2-sphere corresponding to all rotation axes  with radii given by the rotation angles . However since a rotation by  around  is the same as a rotation by  around the antipodal  point on the surface of that sphere, the two transformations are identified as the same group element. This manifold is thus doubly connected: Trajectories which cross the sphere ‘surface’ an even number of times can be contracted to a point; those that cross it an odd number can contract only to a single-crossing trajectory.
  2.2. Pseudo-Unitary Cover Pseudo-Orthogonal Matrices
Closely related to the cover afforded by 
 over 
 in (
3), is the cover given by:
The ’s form a group of matrices that satisfy , with , thus called special () pseudo-unitary and denoted (), while the ’s also form a group of real matrices that satisfy , where  characterizes the ‘’ special pseudo-orthogonal or Lorentz group of three-dimensional relativity, denoted . In this case, the  matrices apply to 3-vectors , and respect the ‘space-time’ magnitude .
To examine their manifolds, we again write the entries of 
 with 
 and 
, so that now the determinant is 
. Written as 
 in three-dimensional space, this is the surface (for 
) and twice the exterior (for 
) of a one-sheeted hyperboloid. We have thus an 
 manifold with a hyperbolic ‘hole’, which is 
multiply connected: Trajectories that wind a different number of loops around the hole are distinct, and cannot be deformed one onto another. The map (
5) is 2:1, but leaves the 
 group to cover further manifolds where an angular coordinate around the hyperboloid axis can be counted any times 
 before returning to the initial value.
While the 
 matrices do not have a real form alternative to the complex (
3), we note that the complex 
 matrices 
V in (
5) are equivalent to the set of real 
 matrices 
 of unit determinant 
, denoted 
. Indeed, with the unitary matrix 
, we have: 
This brings in the realization that finding coverings is related to finding coordinates appropriate to the task. The real coordinates of 
 hide the clear description of the 
 manifold as a 3-space with a ‘hole’. The real parameters of 
 in (
5) are better in showing that when the matrix acts on column 3-vectors 
, it contains trigonometric rotations in the 
x–
y plane, and hyperbolic accelerations (‘boosts’) in the 
x–
t and 
y–
t planes. Before addressing in the next section the question of the group covers afforded by these representation matrices, we shall mention one more group that is also realized by 
 real matrices.
  2.3. Real ( and Symplectic  Matrices
Real 
symplectic matrices 
 are even-dimensional and defined in a manner similar to that defining unitary and orthogonal matrices, but with a distinct skew-symmetric metric [
10],
        
        where 
 and 
 are 
 null and unit submatrices. The Greek root of the peculiar name ‘symplectic’ means interwoven, imbricate, and is rarely used outside Hamiltonian mechanics and mathematics.
In the  case () all matrices of unit determinant are also symplectic, , i.e., . This is an accident among low-dimensional groups.
Symplectic matrices are indispensable for Hamiltonian mechanics and geometric optics because they embody linear phase space evolution. Positions 
 and momenta 
 in a system ruled by a Hamiltonian 
 obey the 
 Hamilton equations, written as a single vector equation with the symplectic metric matrix as:
        where the evolution parameter 
z is time in the case of mechanics or, in optics, distance along the setup axis. Let the phase space 
-vectors be written as 
 and the phase space gradient as 
. A permissible linear transformation of phase space by a matrix 
 acting as 
, is such that it conserves the Hamilton Equation (
9). Since the phase space gradient transforms as 
, this conservation condition is evinced multiplying (
9) by 
 from the left and introducing 
 between 
 and 
 to write:
        provided that the matrix 
 satisfies (
8), i.e., is symplectic. Transformations of phase space (linear and also nonlinear) that preserve the Hamilton equations of motion are called 
canonical. Basically equivalent definitions of canonicity are provided by transformations that keep invariant the volume and orientation of phase space elements, and those that keep invariant the Poisson brackets between the phase space coordinates [
11] [Ch. 3]. All linear canonical transformations are produced through this action of real symplectic matrices. The outcome of the last two subsections leads us to write 
. In fact, there is one more repetition of this relation in one higher dimension 
: 
. This applies for two-dimensional mechanical systems with correspondingly two-dimensional momenta, or to three-dimensional optics with two-dimensional screens, where the group of 
 symplectic matrices covers the group of 
 pseudo-orthogonal matrices with metric 
 [
11] [Ch. 12]. These two homomorphisms are accidental; there are no more systematic cover relations between higher symplectic and pseudo-orthogonal groups.
  2.4. Matrices in Paraxial Geometric Optics
Geometric optics uses symplectic matrices to keep track of linear transformations between ray positions, registered as the points  where the ray crosses the standard plane screen , and the ray momentum, which is the projection  on the screen plane of a vector  along the ray, whose magnitude is the refraction index  ( in vacuum).
In plane optics 
, these are coordinates 
 and 
, where 
 is the angle between the ray 
 and the normal to the screen. The coordinates 
 are said to be 
canonically conjugate; they enter the Hamilton Equation (
9) with a Hamiltonian 
, where we note that 
 lies on the so-called 
Descartes sphere (for 
 a circle). We thus interpret 
h as the component of the ray vector that is normal to the screen, in the same sense that 
z is the coordinate normal to it and becomes the evolution parameter of the ray 
 through a setup of free spaces and lenses.
Symplectic matrices are used to describe linear canonical transformations of phase space in a model of geometric optics, called 
paraxial, where the angle 
 is assumed to be conveniently 
small, so that 
 and 
, but extending 
. For 
, paraxial optical systems have thus phase space coordinates in a plane 
 that can be subject to linear transformations. A basis for all linear transformations in this paraxial model are ‘free’ spaces for displacements by 
, and ‘flat’ lenses of Gaussian power 
G (i.e., focal distance 
), which are represented through the following matrices and their actions,
        
To corroborate these identifications: Displacement skews phase space, translating the point on the screen q to  by , and leaving the ray direction  invariant. A lens of power  is convex and convergent by redirecting rays of inclination p to  towards the optical axis by angles  to concentrate them at the focal distance , while if , the lens is concave and divergent.
Representing the optical elements of the paraxial model by matrices allows us to design compound systems with little effort [
12,
13]. As we picture light rays advancing from left to right, one lens 
G between a free space 
 at its left, and another 
 to its right, three-element setups are represented:
The order is important because the matrices act on , the phase space vector to their right: First the light ray is acted by the  flight, then by the lens, and last by the  flight.
When the 1–2 element of the product matrix (
13) is zero, the image 
 is independent of the incoming ray direction, so the system satisfies the focal condition: 
 (i.e., 
), and is an 
imager with magnification 
; being negative, the image will be inverted. On the other and, when 
 and 
, the matrix (
13) becomes 
, namely a 
rotation of phase space 
 by 
, which is a fractional Fourier transform of power 
; for 
 this is the standard Fourier transform [
14,
15],
        
        and the inverse is 
. Fractional Fourier transformers (for 
a integer or non-integer) can be concatenated with products within the set; so 
 and 
 brings us back to an ‘identity’ geometric optical system (there will be more on this in the next section). With a Fourier transformer piece, its inverse, and one lens, we can build:
When the lens is divergent (concave, 
), this is negative free flight. An even better setup for negative free flight is:
        because its total length is only 
; it is also back-forth-symmetric so it minimizes aberrations.
In (
14) we saw that four concatenated geometrical Fourier transformers bring us back to the identity transformation, while the setup (
15) cannot reach back to 
. A third setup to produce the identity can be ‘built’ with repeated blocks of one lens and a displacement,
        
Hence, the geometric optical transformation of inversion  can be obtained with , , or  setups, while the identity  of linear transformations is built with , or  setups. This will be contrasted below with the inversion and unit integral canonical transformations in the linear wave model.
It is finally a natural question whether any 
 matrix 
 of unit determinant can be ‘represented’ by a (paraxial) optical system. Part of the difficulty in proving this, is that the decomposition of generic matrices into left- and right-triangular ones is seldom used, compared with other decompositions such as the Euler angle, polar rotation, Iwasawa, or Bargmann, which are mathematically richer. Yet, the answer is in the affirmative: It requires up to three lenses separated by two free flights to realize all 
 symplectic matrices, except that we only miss a subset of zero measure as seen in (
16), which can be bridged by just allowing one last displacement at either end; see [
11] (Sect. 10.5) and [
16]. The case 
 of three-dimensional setups with generally cylindrical lenses is addressed in Ref. [
11] (Chs. 10 and 12), although the matter of minimal arrangements has been eschewed—as far as we know.