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4.4.Change of basis: Linear transformations.

We mentioned above that a linear map is more fundamental than the matrix representing it relative to a chosen basis, for the matrix changes when we change the basis but the linear map remains unchanged. In this Section we will explore how the matrix of a linear map changes as we change the basis. We will first consider linear transformations (or endomorphisms), that is, linear maps T : V → V  .

As before we let V  be an n  -dimensional vector space with basis ℬ = (ei)  , and let T : V → V  be a linear transformation whose matrix relative to ℬ  has entries Tji  defined by

       ∑n
T (ei) =   Tjiej .
       j=1

Now let ℬ ′ = (e′)
       i  be another basis. Relative to this basis, T  will have a matrix with entries T ′
 ji  defined by

        n
T (e′) = ∑ T ′e′.
   i   j=1  ji j

(15)

The obvious question is: How are the two matrices [Tbji]  and [T ′bji]  related?

We can answer this question as follows. As we did in Section 2.3, we introduce the transition matrix [S ]
  ij  relating the basis ℬ  to the basis ℬ ′ :

     ∑n
e ′i =   Sjiej .
     j=1

(16)

We can then compute both sides of equation (15) separately and compare. The right-hand side gives

On the other hand, the left-hand side gives

Comparing the two sides, we see that

∑n         ∑n
   TkjSji =   SkjT′ji ,
j=1        j=1

(17)

or if we let T  , T′ and S  denote the corresponding matrices

       ′
TS = ST .

(18)

As we saw in Section 2.3, S  is invertible, with inverse S′ whose entries are defined by

     ∑n
ei =    S′jie′j .
     j=1

(19)

Let’s change the notation and denote by S-1  the matrix corresponding to S-1  . Multiplying both sides of equation (>18) by S-1  on the left, we obtain

T′ = S-1TS ,

(20)

or more explicitly

       n
T ′=  ∑   S-1T  S  .
  ij  k,l=1  ik  kl lj

(21)