Are orthonormal eigenbases unique?

  • Thread starter Bipolarity
  • Start date
In summary, there is no unique orthonormal eigenbasis for a finite-dimensional inner product space with an orthogonally diagonalizable operator. Even in the case of simple diagonalization, the basis is not unique due to the ability to scale any vector in the basis. This also applies to orthonormal bases, as demonstrated by the possibility of extending two non-parallel vectors to their own orthonormal bases. Furthermore, even in the case of eigenspaces with dimension 1, there is still the potential for an infinite number of different orthonormal eigenbases due to the freedom in choosing a unit vector from each eigenspace. Ultimately, normalization choices may further complicate the uniqueness of an or
  • #1
Bipolarity
776
2
Suppose you have an operator ## T: V → V ## on a finite-dimensional inner product space, and suppose it is orthogonally diagonalizable. Then there exists an orthonormal eigenbasis for V. Is this eigenbasis unique?

Obviously, in the case of simple diagonalization, the basis is not unique since scaling (by nonzero) any vector in an eigenbasis yields a valid eigenbasis.

Likewise, an orthonormal basis for a space of at least dimension 2 is not unique, since we can take any two nonparallel vectors in the space and extend each to its own orthonormal basis through Gram-Schmidt. The two bases must be distinct.

But what about an orthonormal eigenbasis? Is this set unique? My guess is that it is, but I need to know for sure so I can think about which direction I want to steer my proof.

Thanks!

BiP
 
Physics news on Phys.org
  • #2
Psst...consider the identity map and two distinct orthonormal bases for V.

Edit: There are plenty of other examples too. This one is just the easiest.
 
Last edited:
  • #3
You can decompose your vector space V uniquely into
[tex] V = \bigoplus_{\lambda} V_{\lambda} [/tex]
where [itex] V_{\lambda} [/itex] is the eigenspace of eigenvalue [itex] \lambda[/itex]. Inside of each eigenspace if the dimension is not equal to 1 you have a lot of freedom as to what basis you pick (as jgens example gives). Even if each eigenspace is 1 dimensional, you still have two unit vectors from each eigenspace that you can pick, so there are still 2n orthornomal eigenbases.
 
  • #4
Office_Shredder said:
Even if each eigenspace is 1 dimensional, you still have two unit vectors from each eigenspace that you can pick, so there are still 2n orthornomal eigenbases.

Unless I'm missing the point completely, I suppose you mean vectors V and -V?

If you count those as "different" vectors, then if V is complex there are infinite number of vectors to pick from. You can multiply the vector by ##e^{i\theta}## for any ##\theta##.

FWIW in practical engineering eigenvalue problems, you often make a further arbitrary choice about normalization (e.g. make the element of the vector with the maximum modulus real and positive) to nail down those arbitrary but annoying differences, when comparing results from slightly different eigensolutions.
 
  • #5
AlephZero said:
Unless I'm missing the point completely, I suppose you mean vectors V and -V?

If you count those as "different" vectors, then if V is complex there are infinite number of vectors to pick from. You can multiply the vector by ##e^{i\theta}## for any ##\theta##.

Oh yeah I forgot sometimes the field isn't [itex]\mathbb{R}[/itex] :redface:
 
  • #6
Ahh I forgot that scaling a vector by a number on the unit disk in the complex plane (or -1 if the field is real)) preserves normalization of the vector.

Thank you guys!

BiP
 

FAQ: Are orthonormal eigenbases unique?

1. What does it mean for an eigenbasis to be orthonormal?

An orthonormal eigenbasis is a set of eigenvectors of a linear transformation that are orthogonal (perpendicular) to each other and have a magnitude of 1. This means that the vectors are not only linearly independent, but also form a right-handed coordinate system.

2. How is the uniqueness of orthonormal eigenbases determined?

The uniqueness of orthonormal eigenbases is determined by the properties of the underlying linear transformation. If the transformation is normal (commutes with its adjoint), then the eigenbasis will be unique. However, if the transformation is not normal, there may be multiple orthonormal eigenbases.

3. Can an orthonormal eigenbasis exist for a non-normal linear transformation?

Yes, an orthonormal eigenbasis can still exist for a non-normal linear transformation. However, it may not be unique and there may be multiple orthonormal eigenbases for the same transformation.

4. How does the uniqueness of orthonormal eigenbases affect the diagonalization of a matrix?

The uniqueness of orthonormal eigenbases is crucial for the diagonalization of a matrix. If the eigenbasis is unique, then the matrix can be diagonalized by simply changing bases. However, if the eigenbasis is not unique, then the matrix may not be diagonalizable.

5. Are there any practical applications for understanding the uniqueness of orthonormal eigenbases?

Yes, understanding the uniqueness of orthonormal eigenbases is important in many areas of mathematics and engineering. For example, it is essential in quantum mechanics, signal processing, and image processing. It also plays a role in understanding the behavior of dynamical systems and differential equations.

Similar threads

Replies
3
Views
1K
Replies
14
Views
2K
Replies
6
Views
2K
Replies
8
Views
2K
Replies
6
Views
3K
Replies
7
Views
2K
Replies
8
Views
3K
Back
Top