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Let $A$ be a linear operator which acts on the vector space $V=\langle x_1,x_2, \ldots,x_n\rangle$. Suppose we know its eigenvalues - $\lambda_1, \lambda_2, \ldots, \lambda_n.$

Now consider the vector space $V^{(2)} \subset {\rm Sym}^2 V$ generated by elements $x_i x_j, i<j,$ $\dim V^{(2)}=\binom{n}{2}.$ Let us extend the operator $A$ on $V^{(2)}$ by linearity and by $A(x_i x_j)=A(x_i)A(x_j)$. Denote the extension by $A^{(2)}$ and suppose that $A^{(2)}$ is an injective endomorphism of $V^{(2)}$.

Question. What is the eigenvalues of the $A^{(2)}?$ My first answer was that the set of eigenvalues consists of elements $\lambda_i \lambda_j, i<j$ but simple examples with small $n$ show that is wrong answer.

Edit. We may assume that $A$ is a permutation of the basis vectors.

Leox
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    To write $< x_1,x_2, \ldots,x_n>$ is not proper usage; I changed it to $\langle x_1,x_2, \ldots,x_n\rangle$. ${}\qquad{}$ – Michael Hardy Aug 19 '15 at 20:11
  • Can we assume that $A$ is injective? Also, when we write $x_ix_j$, what do we mean? – bartgol Aug 19 '15 at 20:31
  • @bartgol that wouldn't be enough: the map $$ A = \pmatrix{2&1\0&1} $$ fails similarly – Ben Grossmann Aug 19 '15 at 20:35
  • yes,I mean that $A$ is injective. $x_i x_j=x_j x_i$ and it is an element of the symmetric algebra of the vector space.Please see an exmple below. – Leox Aug 19 '15 at 20:39
  • So, is $x_ix_j$ the same as the symmetric part of the matrix $x_i x_j^T$ (or better, the vectorization of that)? – bartgol Aug 19 '15 at 20:45
  • @bartgol that is certainly one way to think about it. Leox is ultimately using some form of the symmetric tensor product – Ben Grossmann Aug 19 '15 at 20:55
  • Well, I'm puzzled then. Cause if that's the definition of $x_ix_j$, then the statement should be true, since $$ A(x_ix_j)=Ax_i Ax_j = \frac{1}{2}(Ax_i (Ax_j)^T + Ax_j (Ax_i)^T))=\frac{\lambda_i\lambda_j}{2}( x_ix_j^T+x_jx_i^T)=\lambda_i\lambda_j x_ix_j. $$

    Edit: assuming $x_i,x_j$ are eigenvectors of $A$.

    – bartgol Aug 19 '15 at 21:07
  • @bartgol that assumes that the $x_i$ are the eigenvectors, which they are apparently not necessarily – Ben Grossmann Aug 19 '15 at 21:08
  • Sure, but you can always expand $x_i,x_j$ on the eigenvector basis of $A$, no? – bartgol Aug 19 '15 at 21:10
  • Aaaah, but that brings in all the eigenvectors and shuffles together the eigenvalues... – bartgol Aug 19 '15 at 21:15

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When you talk about the eigenvalues of $A^{(2)}$ over $V^{(2)}$, you assume that the image of $A^{(2)}$ lies within $V^{(2)}$ (or, in other words, that $V^{(2)}$ is an invariant subspace of $A \otimes A$). Note, however, that this is not generally the case. For example, we can consider the map $A$ over $\langle x_1,x_2 \rangle$ defined by $$ Ax_1 = Ax_2 = x_1 $$ or in terms of matrices, $A = \left(\begin{smallmatrix}1&1\\0&0\end{smallmatrix}\right)$.

Note that $A^{(2)}(x_1x_2) = x_1x_1 \notin V^{(2)}$.

Because $A^{(2)}$ (as restricted to $V^{(2)}$) is not an endomorphism, it doesn't make sense to talk about its "eigenvalues".


Suppose that $A$ permutes the vectors $\{x_i\}$ by some permutation $\sigma \in S_n$. That is, $Ax_i = x_{\sigma(i)}$. For convenience, let $x_{ij} = x_ix_j$.

Note that $A^{(2)}$ is itself a permutation of the basis vectors $\{x_i x_j:i<j\}$. In particular, we have $$ A^{(2)}:x_{ij} \mapsto x_{\sigma(i)\sigma(j)} $$ Ultimately, the eigenvalues depend on the cycle decomposition of this new permutation. This depends only on the cycle decomposition of the original permutation.

For example: suppose that $A$ is the map $$ x_1 \to x_2 \to x_3 \to x_1\\ x_4 \to x_5 \to x_4 $$ That is, $A$ has the cycle decomposition $(1 2 3)(45)$. Then $A^{(2)}$ can be written out as $$ x_{12} \to x_{23} \to x_{13} \to x_{12}\\ x_{45} \to x_{45}\\ x_{14} \to x_{25} \to x_{34} \to x_{15} \to x_{24} \to x_{35} \to x_{14} $$ If we were to list the elements of $\{x_{ij}:i<j\}$ in lexicographical order, we could rewrite the above as $$ 1 \to 5 \to 2 \to 1\\ 10 \to 10\\ 3 \to 7 \to 8 \to 4 \to 6 \to 9 \to 3 $$ So that the new permutation has the cycle decomposition $$ (1 \;5\; 2)(3\; 7\; 8\; 4\; 6\; 9)(10) $$ So, we're looking for the eigenvalues of a permutation that decomposes into one $3$-cycle, one $6$-cycle, and one $1$-cycle. Our eigenvalues will be each of the roots of $\lambda^3 = 1$, each of the roots of $\lambda^6 = 1$, and each of the roots of $\lambda = 1$.

Ben Grossmann
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  • Well, suppose that $A(V^{(2)})=V^{(2)}$. I will correct. – Leox Aug 19 '15 at 20:21
  • First of all, you meant $A(V^{(2)}) \subseteq V^{(2)}$. Second of all, the fact that $V^{(2)}$ isn't usually an invariant subspace is a hint that whatever the answer will be, it won't be "nice"; at least, if we're going to get a nice answer, we need a nice characterization of the maps $A$ that make $A^{(2)}$ an endomorphism. It would help if you could provide some context for this question. For example: why are you asking it? Does this come out of some bigger problem? Also, have you heard of the antisymmetric tensor product? – Ben Grossmann Aug 19 '15 at 20:28
  • For example, let $n=6$ and let $$ A( x_{{3}})=x_{{2}},A(x_{{2}})=x_{{3}},A(x_{{1}})=x_{{1}},A(x_{{6}})=x_{{6}},A(x_{{5}})=x_{{4}},A(x_{{4}})=x_{{5}}. $$ In this case we have that $A$ is an endomorphism. The eigenvalues of $A$ is $$ [-1, -1, 1, 1, 1, 1], $$ and the eigenvalues of $A^{(2)}$ is $$[-1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1]$$ so it is not $\lambda_i \lambda_j$. P.S. Ok, I will looking about antisymmetric product. I hope that there is a "nice" answer. – Leox Aug 19 '15 at 20:37
  • @Leox can we assume that $A$ is necessarily a permutation of the vectors ${x_i}$? – Ben Grossmann Aug 19 '15 at 20:41
  • Yes, we may assume that $A$ is a permutation. – Leox Aug 19 '15 at 20:43
  • @Leox maybe you should ask a separate question to find out which maps $A$ will work for us – Ben Grossmann Aug 19 '15 at 20:43
  • I have edited the question and assume that $A$ is a permutation. – Leox Aug 19 '15 at 20:46
  • See my latest edit – Ben Grossmann Aug 20 '15 at 13:14
  • Please see my another question http://math.stackexchange.com/questions/1404651/find-trace-of-linear-operator – Leox Aug 21 '15 at 06:28