Ma · Mathematics

Is the Product of Two Symmetric Matrices Similar to a Symmetric Matrix?

Published By the 9to5Science editorial team

At a glance

  1. 1. Check the claim

    For arbitrary real symmetric matrices, the claim is false.

  2. 2. Test the spectrum

    A real symmetric matrix has only real eigenvalues, and similarity preserves eigenvalues.

  3. 3. Use a counterexample

    Multiply two symmetric 2×2 matrices whose product has eigenvalues i and −i.

  4. 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

A=(100−1),B=(0110).A=\begin{pmatrix}1&0\\0&-1\end{pmatrix}, \qquad B=\begin{pmatrix}0&1\\1&0\end{pmatrix}.

Their product is

AB=(01−10).AB=\begin{pmatrix}0&1\\-1&0\end{pmatrix}.

Its characteristic polynomial is

det⁡(λI−AB)=det⁡(λ−11λ)=λ2+1,\det(\lambda I-AB)=\det\begin{pmatrix}\lambda&-1\\1&\lambda\end{pmatrix}=\lambda^2+1,

so its eigenvalues are ii and −i-i. 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 ABAB 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 AA is real symmetric and positive definite, and BB is real symmetric of the same size. Positive definiteness means xTAx>0x^T A x>0 for every nonzero real vector xx. The spectral theorem gives a symmetric positive-definite square root A1/2A^{1/2}, which is invertible. Then

A−1/2(AB)A1/2=A1/2BA1/2.\begin{aligned} A^{-1/2}(AB)A^{1/2} &=A^{1/2}BA^{1/2}. \end{aligned}

The right-hand side is symmetric, since

(A1/2BA1/2)T=A1/2BTA1/2=A1/2BA1/2.(A^{1/2}BA^{1/2})^T=A^{1/2}B^TA^{1/2}=A^{1/2}BA^{1/2}.

Therefore ABAB is similar to the symmetric matrix A1/2BA1/2A^{1/2}BA^{1/2}. The same argument works if BB is positive definite: conjugate ABAB using B1/2B^{1/2} to obtain B1/2AB1/2B^{1/2}AB^{1/2}.

Worked example

Let

A=(4001),B=(2113).A=\begin{pmatrix}4&0\\0&1\end{pmatrix}, \qquad B=\begin{pmatrix}2&1\\1&3\end{pmatrix}.

Both are symmetric, and AA is positive definite. Since A1/2=(2001)A^{1/2}=\begin{pmatrix}2&0\\0&1\end{pmatrix},

AB=(8413),A1/2BA1/2=(8223).AB=\begin{pmatrix}8&4\\1&3\end{pmatrix}, \qquad A^{1/2}BA^{1/2}=\begin{pmatrix}8&2\\2&3\end{pmatrix}.

The second matrix is symmetric, and the calculation above gives

A−1/2(AB)A1/2=(8223).A^{-1/2}(AB)A^{1/2}=\begin{pmatrix}8&2\\2&3\end{pmatrix}.

So the matrices are similar. As a check, both have characteristic polynomial λ2−11λ+20\lambda^2-11\lambda+20 and eigenvalues (11±41)/2(11\pm\sqrt{41})/2.

The exact criterion

For any real square matrix MM, the following are equivalent:

  • MM is similar over the reals to a real symmetric matrix.
  • MM 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 M=PDP−1M=PDP^{-1} for an invertible real matrix PP and a real diagonal matrix DD, then DD itself is symmetric. This criterion applies to M=ABM=AB; symmetry of AA and BB alone does not ensure it.

Common mistakes

  • Assuming the product is symmetric. In general, (AB)T=BA(AB)^T=BA, not ABAB. The product is symmetric exactly when AB=BAAB=BA.
  • 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 A−1/2A^{-1/2}, so it requires AA 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

  1. Matrix Analysis, Second Edition — Roger A. Horn and Charles R. Johnson
  2. Linear Algebra Done Right, Fourth Edition — Sheldon Axler

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