Coordinates vector is a very important concept in Linear algebra and representation theory.
Definition
Let V be a linear space with dim V = n and let
be a linear basis for V.
Therefore for every
there is a linear combination (which is unique to v) of the basis vectors such as
The α-s are determined uniquely by v and B (the theorem of basis guarantees this) and therefore we can say that the following is a Representation of v in the B basis.
Now, we define the coordinates vector of v according to B (also called B representation of v) by:
and the α-s are called the coordinates of v.
The mapping which matches each vector v from V to its coordinate vector [v]B is an isomorphism: a linear transformation which is a one-to-one correspondence and onto. This means that every finite-dimensional linear space can be treated as a "columns and squares" space Fn where n is the dimension of V and F is the field on which V is defined.
Coordinates vector is a very important concept in Linear algebra and representation theory, since it allows every calculation with abstract objects to be transformed into a calculation with blocks of numbers (matrices, column vectors) which we know how to do explicitly.
Example 1
Let P3 be the space of all the algebraic polynomials in degree less than 4 (i.e. the highest exponent of x can be 3). This space is linear and spanned by the following polynomials:
- BP = {1,x,x2,x3}
matching
then the corresponding coordinate vector to the polynomial
is
.
According to that representation, the differentiation operator d/dx which we shall mark D will be represented by the following matrix:
Using that method it is easy to explore the properties of the operator: such as invertability, hermitian or anti-hermitian or none, spectrum and eigenvalues and more.
Example 2
The Pauli matrices which represent the spin operator when transforming the spin eigenstates into vector coordinates.
Basis transformation matrix
Let's mark with [M]B the matrix which has columns consisting of b1, b2, ..., bn . Then,
- v = [M]B[v]B.
This formalism can be generalized for transforming v from B representation to a C representation (where C is another basis).
Defining basis transformation matrix from B to C as the following matrix:
we receive the following theorem:
Corollary:
This matrix is Invertible matrix and M-1 is the basis transformation matrix from C to B. In other words,
Remarks:
- The basis transformation matrix can be regarded as an automorphism over V.
-
where E is the standard basis.
- In order to easily remember the theorem
-
- notice that the M's sup-index and v's sub-index are "canceling" each other and the M's sub-index is what remains and become v's new sub-index. The "canceling" of index is not a real canceling but rather a manipulation of symbols which serves us for purposes of convenience.