| Topic: |
Science > Physics |
| User: |
"Kevin Roberge" |
| Date: |
15 Jun 2004 01:06:17 PM |
| Object: |
simultaneous diagonalization |
given two matrices A and B, what are the neccessary and sufficient
conditions that they can be simultaneously diagonalized?
Thanks,
Kevin
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| User: "John T Lowry" |
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| Title: Re: simultaneous diagonalization |
15 Jun 2004 02:59:20 PM |
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It means there is some basis consisting of eigenvectors of both A and B.
Using that basis, both A and B are represented by diagonal matrices.
"Kevin Roberge" <kevin.roberge@umit.maine.edu> wrote in message
news:d2c23ee6.0406151006.762de2e7@posting.google.com...
given two matrices A and B, what are the neccessary and sufficient
conditions that they can be simultaneously diagonalized?
Thanks,
Kevin
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| User: "Creighton Hogg" |
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| Title: Re: simultaneous diagonalization |
15 Jun 2004 01:18:26 PM |
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On 15 Jun 2004, Kevin Roberge wrote:
given two matrices A and B, what are the neccessary and sufficient
conditions that they can be simultaneously diagonalized?
This sounds like a homework problem. Anyway, if I remember correctly two
diagonalizable matrices A and B can be simultaneously diagnonalized if and
only if they commute.
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| User: "Kevin Roberge" |
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| Title: Re: simultaneous diagonalization |
18 Jun 2004 07:24:02 AM |
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Creighton Hogg <wchogg@hep.wisc.edu> wrote in message
This sounds like a homework problem. Anyway, if I remember correctly two
diagonalizable matrices A and B can be simultaneously diagnonalized if and
only if they commute.
Thanks for your response, here is my concern however. Consider the
following problem of a double pendulum that has two identical masses
both on rods of length l. Suppose we use the usual general
coordinates: theta (for the upper rod) and phi (for the lower rod).
Then we have a kinetic energy matrix:
|2 1| |2 0|
M = m(l^2)| | and a potential energy matrix K = mgl| |
|1 1| |0 1|
The normal mode vectors are |1>=(1, root(2)) and |2>=(-1, root(2)).
I've used ket notation since vectors are hard to represent in text and
the vectors are intended to be columns as well.
Now we can form the modal matrix
A=(|1> |2>) we haven't yet normalize the normal modes, but this
doesn't change the diagonalization in this problem just what the
resulting diagonal entries are.
Now the kinetic energy matrix M can be diagonalized by
Transpose(A)*M*A and the potential energy matrix can be diagonalized
as well
by Transpose(A)*K*A. (if the modal matrix contained normalized
(relative to M) eigenvectors then M would be diagonalized to the
identity).
But, consider the following products
|2 1| * |2 0| |4 1| versus |2 0| * |2 1| |4 2|
|1 1| |0 1| = |2 1| |0 1| |1 1| = |1 1|
So the matrices clearly don't commute, but we have just simultaneously
diagonalized them. I buy the fact the if two hermitian operators
commute then they can be simultaneously diagonalized (seen the proof).
But I would like to know what simultaneous diagonalization implies
(since it doesn't seem to imply commutation).
Any thoughts?
Kevin
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| User: "Mel Lep" |
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| Title: Re: simultaneous diagonalization |
18 Jun 2004 06:26:58 PM |
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(Kevin Roberge) wrote:
Creighton Hogg <wchogg@hep.wisc.edu> wrote in message
This sounds like a homework problem. Anyway, if I remember correctly two
diagonalizable matrices A and B can be simultaneously diagnonalized if and
only if they commute.
Thanks for your response, here is my concern however. Consider the
following problem of a double pendulum that has two identical masses
both on rods of length l. Suppose we use the usual general
coordinates: theta (for the upper rod) and phi (for the lower rod).
Then we have a kinetic energy matrix:
|2 1| |2 0|
M = m(l^2)| | and a potential energy matrix K = mgl| |
|1 1| |0 1|
The normal mode vectors are |1>=(1, root(2)) and |2>=(-1, root(2)).
I've used ket notation since vectors are hard to represent in text and
the vectors are intended to be columns as well.
Now we can form the modal matrix
A=(|1> |2>) we haven't yet normalize the normal modes, but this
doesn't change the diagonalization in this problem just what the
resulting diagonal entries are.
Now the kinetic energy matrix M can be diagonalized by
Transpose(A)*M*A and the potential energy matrix can be diagonalized
as well
by Transpose(A)*K*A. (if the modal matrix contained normalized
(relative to M) eigenvectors then M would be diagonalized to the
identity).
But, consider the following products
|2 1| * |2 0| |4 1| versus |2 0| * |2 1| |4 2|
|1 1| |0 1| = |2 1| |0 1| |1 1| = |1 1|
So the matrices clearly don't commute, but we have just simultaneously
diagonalized them. I buy the fact the if two hermitian operators
commute then they can be simultaneously diagonalized (seen the proof).
But I would like to know what simultaneous diagonalization implies
(since it doesn't seem to imply commutation).
Any thoughts?
Well, you have two symmetric and *positive definite* matrices,
M and K, and that's sufficient for simultaneous diagonalization.
(In fact, only one of the matrices need to be positive definite.)
M.L.
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| User: "Kevin Roberge" |
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| Title: Re: simultaneous diagonalization |
19 Jun 2004 06:09:15 AM |
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(Mel Lep) wrote in message > >
Well, you have two symmetric and *positive definite* matrices,
M and K, and that's sufficient for simultaneous diagonalization.
(In fact, only one of the matrices need to be positive definite.)
M.L.
Oh, is that the case. Could you suggest a sketch of a proof or a
reference I could look at it? Still there remains the question of why
we use a congruence transformation to do the diagonalizing instead of
a similiarity transformation.
Thanks,
Kevin
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| User: "Mel Lep" |
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| Title: Re: simultaneous diagonalization |
19 Jun 2004 06:05:35 PM |
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(Kevin Roberge) wrote:
mel_lep@yahoo.se (Mel Lep) wrote in message > >
Well, you have two symmetric and *positive definite* matrices,
M and K, and that's sufficient for simultaneous diagonalization.
(In fact, only one of the matrices need to be positive definite.)
Oh, is that the case. Could you suggest a sketch of a proof or a
reference I could look at it? Still there remains the question of why
we use a congruence transformation to do the diagonalizing instead of
a similiarity transformation.
Let's state the relevant theorem in terms of quadratic forms (I hope
you will see the connection to your problem):
Consider two quadratic forms A(x,x) and B(x,x) [obtained from the
symmetric *bilinear* forms A(x,y) and B(x,y)] defined on an affine
space R^n. If one of the quadratic forms, say B(x,x), is positive
definite, there exists an ON-basis, e_1,...,e_n, in which both A(x,x)
and B(x,x) are reduced to canonical ("diagonal") form.
The simple proof:
The trick is to supplement the space R^n with the euclidean metric
(x,y) = B(x,y)
- a valid definition by the properties of B(x,y).
Now, since A(x,y) is *symmetric*, there exists (in the new euclidean
space) an ON-basis e_1,...,e_n [=> B(e_i,e_j) = \delta_ij], which
diagonalizes A(x,x):
A(x,x) = \lambda_1(x_1)^2 + ... + \lambda_n(x_n)^2.
As is easily seen, the given basis also diagonalizes B(x,x):
B(x,x) = B(x_ie_i, x_je_j) ;sum over repeated indices here
= x_i x_j B(e_i,e_j) = (x_1)^2 + ... + (x_n)^2
This theorem on the "simultaneous reduction of two quadratic forms" may
be found in many books on 'linear algebra' or 'linear spaces'.
M.L.
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| User: "Kevin Roberge" |
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| Title: Re: simultaneous diagonalization |
22 Jun 2004 08:36:24 PM |
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(Mel Lep) wrote
Now, since A(x,y) is *symmetric*, there exists (in the new euclidean
space) an ON-basis e_1,...,e_n
So, I wouldn't have had a problem with this step except that recently
I learnt something I wasn't aware of. I had always thought that for a
matrix to be self-adjoint it meant that it was symmetric (or conjugate
symmetric in the case of complex valued matrices). But of course this
isn't the case if the bilinear form defining the inner product isn't
the identity. So if M is an opertator and B is the matrix giving the
inner product then M is self adjoint if and only if Transpose(M)B=BM.
It can be shown that every self-adjoint operator on a real space can
be orthogonally diagonalized, but self-adjoint nolonger implies
symmetric. Does this affect your proof, or not? Can you shed some
more light on this. Thanks.
Kevin
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| User: "Mel Lep" |
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| Title: Re: simultaneous diagonalization |
28 Jun 2004 07:50:23 AM |
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[Sorry about the delay ... other duties calling.]
Kevin Roberge wrote:
mel_lep@yahoo.se (Mel Lep) wrote
Now, since A(x,y) is *symmetric*, there exists (in the new euclidean
space) an ON-basis e_1,...,e_n
So, I wouldn't have had a problem with this step except that recently
I learnt something I wasn't aware of. I had always thought that for a
matrix to be self-adjoint it meant that it was symmetric (or conjugate
symmetric in the case of complex valued matrices). But of course this
isn't the case if the bilinear form defining the inner product isn't
the identity. So if M is an opertator and B is the matrix giving the
inner product then M is self adjoint if and only if Transpose(M)B=BM.
It can be shown that every self-adjoint operator on a real space can
be orthogonally diagonalized, but self-adjoint nolonger implies
symmetric. Does this affect your proof, or not? Can you shed some
more light on this. Thanks.
Well, in the euclidean space E^n with metric defined by B(x,y), the
matrix associated with B(x,y) itself is clearly the unit matrix.
(Forget about any previously given metric!) -- For *any* ON-basis
e_1,...,e_n in E^n :
B(e_i,e_j) = (e_i,e_j) = \delta_ij
-- and B(x,x) is automatically diagonalized:
B(x,x) = (x,x) = (x_1)^2 + ... + (x_n)^2
Now, diagonalize A(x,x) by means of the well known theorem (the
"principal axis theorem"):
Any quadratic form A(x,x) on an euclidean space E^n can be reduced to
diagonal form A(x,x) = \lambda_1 (x_1)^2 + ... + \lambda_n (x_n)^2
by an orthogonal transformation.
cf http://mathworld.wolfram.com/QuadraticForm.html
In the 2D case, A(x,x) = const gives a conic section and B(x,x) = const
a circle. So, choose the basis vectors along the principal axes of
A(x,x) = const, and you are done.
M.L.
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