MATRICES AND VECTOR SPACES
|expA|. Moreover, by choosing the similarity transformation so that it diagonalisesA,we
haveA′=diag(λ 1 ,λ 2 ,...,λN), and so
|expA|=|expA′|=|exp[diag(λ 1 ,λ 2 ,...,λN)]|=|diag(expλ 1 ,expλ 2 ,...,expλN)|=
∏N
i=1
expλi.
Rewriting the final product of exponentials of the eigenvalues as the exponential of the
sum of the eigenvalues, we find
|expA|=
∏N
i=1
expλi=exp
(N
∑
i=1
λi
)
=exp(TrA),
which gives the trace formula (8.104).
8.17 Quadratic and Hermitian forms
Let us now introduce the concept of quadratic forms (and their complex ana-
logues, Hermitian forms). A quadratic formQis a scalar function of a real vector
xgiven by
Q(x)=〈x|Ax〉, (8.105)
for some real linear operatorA. In any given basis (coordinate system) we can
write (8.105) in matrix form as
Q(x)=xTAx, (8.106)
whereAis a real matrix. In fact, as will be explained below, we need only consider
the case whereAis symmetric, i.e.A=AT. As an example in a three-dimensional
space,
Q=xTAx=
(
x 1 x 2 x 3
)
11 3
11 − 3
3 − 3 − 3
x 1
x 2
x 3
=x^21 +x^22 − 3 x^23 +2x 1 x 2 +6x 1 x 3 − 6 x 2 x 3. (8.107)
It is reasonable to ask whether a quadratic formQ=xTMx,whereMis any
(possibly non-symmetric) real square matrix, is a more general definition. That
this is not the case may be seen by expressingMin terms of a symmetric matrix
A=^12 (M+MT) and an antisymmetric matrixB=^12 (M−MT) such thatM=A+B.
We then have
Q=xTMx=xTAx+xTBx. (8.108)
However,Qis a scalar quantity and so
Q=QT=(xTAx)T+(xTBx)T=xTATx+xTBTx=xTAx−xTBx.
(8.109)
Comparing (8.108) and (8.109) shows thatxTBx= 0, and hencexTMx=xTAx,