Is the Product of Two Symmetric Matrices Similar to a Symmetric Matrix?
At a glance
- 1. Check the claim
For arbitrary real symmetric matrices, the claim is false.
- 2. Test the spectrum
A real symmetric matrix has only real eigenvalues, and similarity preserves eigenvalues.
- 3. Use a counterexample
Multiply two symmetric 2×2 matrices whose product has eigenvalues i and −i.
- 4. Identify when it works
A product is similar to a real symmetric matrix exactly when it is diagonalizable over the reals with real eigenvalues.
The statement is false for arbitrary real symmetric matrices. Symmetry of the factors does not guarantee that their product has the spectral properties of a symmetric matrix. A short counterexample settles the claim; a positive-definite factor gives a useful condition under which the conclusion is true.
A counterexample
Take the real symmetric matrices
Their product is
Its characteristic polynomial is
so its eigenvalues are and . But every real symmetric matrix has real eigenvalues, by the spectral theorem. Similar matrices have the same characteristic polynomial and therefore the same eigenvalues. Thus cannot be similar over the reals—or even over the complex numbers—to a real symmetric matrix.
This example also shows why it is not enough to note that each factor is diagonalizable: the product can have nonreal eigenvalues even though both factors are real symmetric.
A condition that makes the claim true
Suppose is real symmetric and positive definite, and is real symmetric of the same size. Positive definiteness means for every nonzero real vector . The spectral theorem gives a symmetric positive-definite square root , which is invertible. Then
The right-hand side is symmetric, since
Therefore is similar to the symmetric matrix . The same argument works if is positive definite: conjugate using to obtain .
Worked example
Let
Both are symmetric, and is positive definite. Since ,
The second matrix is symmetric, and the calculation above gives
So the matrices are similar. As a check, both have characteristic polynomial and eigenvalues .
The exact criterion
For any real square matrix , the following are equivalent:
- is similar over the reals to a real symmetric matrix.
- is diagonalizable over the reals and all its eigenvalues are real.
One direction follows from the spectral theorem: a real symmetric matrix is orthogonally diagonalizable, and similarity preserves diagonalizability and eigenvalues. For the other direction, if for an invertible real matrix and a real diagonal matrix , then itself is symmetric. This criterion applies to ; symmetry of and alone does not ensure it.
Common mistakes
- Assuming the product is symmetric. In general, , not . The product is symmetric exactly when .
- Confusing symmetry with similarity to a symmetric matrix. A matrix can be nonsymmetric yet similar to a symmetric one, as in the positive-definite example. Conversely, the counterexample’s product is nonsymmetric and cannot be similar to a real symmetric matrix because its eigenvalues are nonreal.
- Dropping the positive-definite assumption. The square-root conjugation uses , so it requires to be invertible. If a factor is only positive semidefinite, that argument does not apply directly; check the product’s diagonalizability and eigenvalues instead.
- Ignoring the field. This discussion concerns real symmetric matrices and similarity to a real symmetric matrix. Similarity preserves the characteristic polynomial regardless of whether the change-of-basis matrix is real or complex, so the nonreal eigenvalues in the counterexample rule out either kind of similarity to a real symmetric target.
References
- Matrix Analysis, Second Edition — Roger A. Horn and Charles R. Johnson
- Linear Algebra Done Right, Fourth Edition — Sheldon Axler
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