
21-25 емтихан сурактары
.docx21. Quadratic forms. Reducing a quadratic form to a canonical type.
A
QF of real variables x1,x1,…,xn
is a polynomial of the 2nd
degree according to these variables which doesn’t contain a free
term and terms of the 1st
degree. If n=2, then f(x1,x2)=a11x2+2a12x1x2+a22x2.
A matrix
at which
is called matrix
of quadratic form
and the corresponding determinant – determinant
of this quadratic
form.
Since A
is a symmetric matrix then the roots
and
of the characteristic equation are real numbers.
Let
be
normalized eigenvectors corresponding to characteristic numbers
in an orthonormal basis
The vectors
form an orthonormal basis.
The
matrix
is the transition matrix from the basis
to
the basis
Formulas of transformation of coordinates at transition to the new orthonormal basis have the following form:
Transforming
by these formulas the quadratic form
we
obtain the following quadratic form:
It
does not contain terms with
We
say that a quadratic form
has
been reduced to the canonical
type
by an orthogonal transformation B.
22. Definite quadratic forms. Criterion of Sylvester.
A
quadratic form
is called positive
definite
(negative
definite)
if for all values
the condition
(
)
holds and
only for
For
example,
is positive definite;
is negative definite. Positive definite and negative definite
quadratic forms are called definite.
A
quadratic form
is called quasi-definite
(either non-negative
or
non-positive)
if it takes either only non-negative values or non-positive values,
but it takes 0 not only for
The determinants
are
called angular
minors of
a matrix
1. A quadratic form is positive definite if and only if all the angular minors of its matrix are positive.
2.
A quadratic form is negative definite if and only if the signs of
angular minors alternate as follows:
23. Reducing an equation of curve of the second order to a canonical type.
Let
an equation of a curve of the second order in rectangular system of
coordinates
be given:
Consider
the quadratic form connected with the equation (1):
.Reduce
the quadratic form to canonic type
by an orthogonal transformation of variables:
are eigen-values of the matrix
,
and the columns of the matrix
are orthogonal normalized eigen-vectors (columns) of the matrix
.
The matrix
by properties of orthogonal matrices has the following type:
Using
the formulas (2), express the linear terms
of the equation (1) by the coordinates
.
In result in the system
the equation of the curve takes the following type:
.
Further, extracting complete squares on both variables by parallel
transfer of axes of coordinates of the system
pass to the system
in which the equation of the curve has canonic type. An equation of a
surface of the second order can be reduced to canonic type by analogy
24. Unitary space. Gram matrix, Hermitian matrix, unitary matrix.
A complex linear space where the following conditions hold:
1)
;
2)
A complex number z is real iff
;
3)
The number
is always real and nonnegative;
4)
,
.
is called unitary iff every ordered pair of elements x and y is put in correspondence a complex number (x,y) called their scalar product so that the following conditions hold:
(1)
;
(2)
for every complex number
;
(3)
;
(4)
is a real nonnegative number, and
.
Let
in
a basis
be given. The scalar product of elements
and
is presented as
,
where
are components of the matrix
named the basis
matrix of Gram.
A
matrix
satisfying the property
is called Hermitian.
A matrix
satisfying the properties
and
is called unitary.
25. Linear operators in a unitary space.
A
linear operator
acting in a unitary space
is called Hermitian
conjugate
to a linear operator
if for all
the following holds:
.
Theorem
1.
For linear operators
and
acting in a unitary space
the following holds:
and
Proof:
Prove the first assertion. We have
for all
,
and consequently
.
Similarly,
for all
and every complex number
.
Theorem
2.
The matrix of an operator
that is Hermitian conjugate to an operator
in
in a basis
is
defined by the following equality:
.
A
linear operator
acting in a unitary space
is called Hermitian
self-conjugate
(or just Hermitian)
if
.
Properties of Hermitian operators:
1. Eigen-values of a Hermitian operator are real numbers.
2. Eigen-vectors corresponding to distinct eigen-values of a Hermitian operator are orthogonal.
3. For every Hermitian operator there exists an orthonormal basis consisting of its eigen-vectors.
4.
In an orthonormal basis of a unitary space
a Hermitian operator has a Hermitian matrix.
An
eigen-value
of a linear operator
is called degenerate
if an invariant eigen-subspace corresponding to it has the dimension
greater than 1.
A
linear operator
acting in a unitary space
is called unitary
(or isometric)
if for all
the following holds:
.
Properties of unitary operators:
1.
.
2.
If
is a unitary operator then there exists the inverse operator
that is also unitary and
.
3.
A unitary operator transfers an orthonormal basis in an orthonormal
basis, and conversely if a linear operator
transfers an orthonormal basis to an orthonormal basis then
is unitary.
4.
If
is an eigen-value of a unitary operator then
.