Spectrum of a Subspace of MatricesWhat is known about the distribution of eigenvectors of random matrices?Is there a nice choice-free argument to count the number of sublattices?Complexity class of matrix generalization of knapsack problemMatrix diagonalization and eigenvector computation constructivelyIs this proof of Perron's theorem correct, and if so is it original?Rotatable matrix, its eigenvalues and eigenvectors

Spectrum of a Subspace of Matrices


What is known about the distribution of eigenvectors of random matrices?Is there a nice choice-free argument to count the number of sublattices?Complexity class of matrix generalization of knapsack problemMatrix diagonalization and eigenvector computation constructivelyIs this proof of Perron's theorem correct, and if so is it original?Rotatable matrix, its eigenvalues and eigenvectors













4












$begingroup$


I conjecture the following:




Let $U subset Bbb C^n times n$ be an affine subspace, and let $S_U$ denote the "spectrum of $U$", that is
$$
S_U = lambda in Bbb C : det(A - lambda I) = 0 text for some A in U.
$$

Then either all elements of $U$ have an identical spectrum, or $S_U = Bbb C$.




Is this correct? Some simple examples of each case: for any fixed $lambda_i$,
$$
U_1 = leftpmatrixlambda_1&t\0&lambda_2: t in Bbb Cright, quad
U_2 = leftpmatrixlambda_1&0\0&t: t in Bbb Cright.
$$

Clearly, $S_U_1 = lambda_1,lambda_2$ and $S_U_2 = Bbb C$. Are there any other possibilities? I suspect that there is a quick algebraic-geometry approach here that I am missing.




An aside: I would also be interested in the case of real affine subspaces of $Bbb C^n times n$, if anyone has insights on what the possibilities are there. Note that the symmetric real matrices are an example of a subspace where we attain $S_U^(Bbb R) = Bbb R subsetneq Bbb C$. We can clearly attain any "line" in $Bbb C$, but I wonder if there are other possibilities.










share|cite|improve this question









$endgroup$


















    4












    $begingroup$


    I conjecture the following:




    Let $U subset Bbb C^n times n$ be an affine subspace, and let $S_U$ denote the "spectrum of $U$", that is
    $$
    S_U = lambda in Bbb C : det(A - lambda I) = 0 text for some A in U.
    $$

    Then either all elements of $U$ have an identical spectrum, or $S_U = Bbb C$.




    Is this correct? Some simple examples of each case: for any fixed $lambda_i$,
    $$
    U_1 = leftpmatrixlambda_1&t\0&lambda_2: t in Bbb Cright, quad
    U_2 = leftpmatrixlambda_1&0\0&t: t in Bbb Cright.
    $$

    Clearly, $S_U_1 = lambda_1,lambda_2$ and $S_U_2 = Bbb C$. Are there any other possibilities? I suspect that there is a quick algebraic-geometry approach here that I am missing.




    An aside: I would also be interested in the case of real affine subspaces of $Bbb C^n times n$, if anyone has insights on what the possibilities are there. Note that the symmetric real matrices are an example of a subspace where we attain $S_U^(Bbb R) = Bbb R subsetneq Bbb C$. We can clearly attain any "line" in $Bbb C$, but I wonder if there are other possibilities.










    share|cite|improve this question









    $endgroup$
















      4












      4








      4





      $begingroup$


      I conjecture the following:




      Let $U subset Bbb C^n times n$ be an affine subspace, and let $S_U$ denote the "spectrum of $U$", that is
      $$
      S_U = lambda in Bbb C : det(A - lambda I) = 0 text for some A in U.
      $$

      Then either all elements of $U$ have an identical spectrum, or $S_U = Bbb C$.




      Is this correct? Some simple examples of each case: for any fixed $lambda_i$,
      $$
      U_1 = leftpmatrixlambda_1&t\0&lambda_2: t in Bbb Cright, quad
      U_2 = leftpmatrixlambda_1&0\0&t: t in Bbb Cright.
      $$

      Clearly, $S_U_1 = lambda_1,lambda_2$ and $S_U_2 = Bbb C$. Are there any other possibilities? I suspect that there is a quick algebraic-geometry approach here that I am missing.




      An aside: I would also be interested in the case of real affine subspaces of $Bbb C^n times n$, if anyone has insights on what the possibilities are there. Note that the symmetric real matrices are an example of a subspace where we attain $S_U^(Bbb R) = Bbb R subsetneq Bbb C$. We can clearly attain any "line" in $Bbb C$, but I wonder if there are other possibilities.










      share|cite|improve this question









      $endgroup$




      I conjecture the following:




      Let $U subset Bbb C^n times n$ be an affine subspace, and let $S_U$ denote the "spectrum of $U$", that is
      $$
      S_U = lambda in Bbb C : det(A - lambda I) = 0 text for some A in U.
      $$

      Then either all elements of $U$ have an identical spectrum, or $S_U = Bbb C$.




      Is this correct? Some simple examples of each case: for any fixed $lambda_i$,
      $$
      U_1 = leftpmatrixlambda_1&t\0&lambda_2: t in Bbb Cright, quad
      U_2 = leftpmatrixlambda_1&0\0&t: t in Bbb Cright.
      $$

      Clearly, $S_U_1 = lambda_1,lambda_2$ and $S_U_2 = Bbb C$. Are there any other possibilities? I suspect that there is a quick algebraic-geometry approach here that I am missing.




      An aside: I would also be interested in the case of real affine subspaces of $Bbb C^n times n$, if anyone has insights on what the possibilities are there. Note that the symmetric real matrices are an example of a subspace where we attain $S_U^(Bbb R) = Bbb R subsetneq Bbb C$. We can clearly attain any "line" in $Bbb C$, but I wonder if there are other possibilities.







      linear-algebra






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      asked 9 hours ago









      OmnomnomnomOmnomnomnom

      1708 bronze badges




      1708 bronze badges























          2 Answers
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          4














          $begingroup$

          This is not true. Consider
          $$
          A(t) = beginpmatrix 0 & t & 0 \ 1 & 0 & 1 \ 1 & 0 & 0
          endpmatrix .
          $$

          Then $det (A(t)+1) = 1$, so $-1notin S$, but clearly the spectrum of $A(t)$ is not constant (for example, $0$ is in the spectrum if and only if $t=0$).






          share|cite|improve this answer









          $endgroup$






















            1














            $begingroup$

            To expand on Christian Remling's answer a bit: in his example, setting $det(A(t) - lambda) = 0$ becomes $(1-lambda)t+lambda^3=0$, and solving for $t$ gives $t = x^3/(x-1)$ -- so for any $lambda in mathbbC$, we have $x in S$ by choosing this $t$, with the exception of $lambda=1$.



            In general for an affine subspace of dimension $d$, we can define the space by $A(t_1,t_2,dots t_d)$, and all entries in $A$ are linear in the $t_i$. Then $det(A(t) - lambda)$ is an $n$th degree polynomial in all the $t_i$ and $lambda$. It is possible that the determinant has no dependence on any $t_i$, in which case we have a finite spectrum. Otherwise, we have a dependence on the $t_i$. Then $det(A(t)-lambda)=0$ has a solution in $t_1$ whenever at least one of the non-constant coefficients is nonzero. (In the above example, as long as the linear coefficient $1-lambdaneq 0$.) Since the leading coefficient (that is not a constant 0 polynomial) is an $n-1$th degree polynomial in $lambda$, it is zero at a most $n-1$ different places, and this is at most $n-1$ places that the spectrum can fail to be continuous. The spectrum only fails to be continuous when all of the coefficients in the $t_1$ polynomial are zero, so this is an upper bound. So, theorem:



            For an affine subspace of $ntimes n$ matrices, the spectrum is either finite (of size at most $n$), or it is $mathbbCsetminus K$, where $K$ is a finite set of exceptions (of size at most $n-1$).






            share|cite|improve this answer









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              active

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              4














              $begingroup$

              This is not true. Consider
              $$
              A(t) = beginpmatrix 0 & t & 0 \ 1 & 0 & 1 \ 1 & 0 & 0
              endpmatrix .
              $$

              Then $det (A(t)+1) = 1$, so $-1notin S$, but clearly the spectrum of $A(t)$ is not constant (for example, $0$ is in the spectrum if and only if $t=0$).






              share|cite|improve this answer









              $endgroup$



















                4














                $begingroup$

                This is not true. Consider
                $$
                A(t) = beginpmatrix 0 & t & 0 \ 1 & 0 & 1 \ 1 & 0 & 0
                endpmatrix .
                $$

                Then $det (A(t)+1) = 1$, so $-1notin S$, but clearly the spectrum of $A(t)$ is not constant (for example, $0$ is in the spectrum if and only if $t=0$).






                share|cite|improve this answer









                $endgroup$

















                  4














                  4










                  4







                  $begingroup$

                  This is not true. Consider
                  $$
                  A(t) = beginpmatrix 0 & t & 0 \ 1 & 0 & 1 \ 1 & 0 & 0
                  endpmatrix .
                  $$

                  Then $det (A(t)+1) = 1$, so $-1notin S$, but clearly the spectrum of $A(t)$ is not constant (for example, $0$ is in the spectrum if and only if $t=0$).






                  share|cite|improve this answer









                  $endgroup$



                  This is not true. Consider
                  $$
                  A(t) = beginpmatrix 0 & t & 0 \ 1 & 0 & 1 \ 1 & 0 & 0
                  endpmatrix .
                  $$

                  Then $det (A(t)+1) = 1$, so $-1notin S$, but clearly the spectrum of $A(t)$ is not constant (for example, $0$ is in the spectrum if and only if $t=0$).







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered 6 hours ago









                  Christian RemlingChristian Remling

                  12.8k2 gold badges24 silver badges45 bronze badges




                  12.8k2 gold badges24 silver badges45 bronze badges
























                      1














                      $begingroup$

                      To expand on Christian Remling's answer a bit: in his example, setting $det(A(t) - lambda) = 0$ becomes $(1-lambda)t+lambda^3=0$, and solving for $t$ gives $t = x^3/(x-1)$ -- so for any $lambda in mathbbC$, we have $x in S$ by choosing this $t$, with the exception of $lambda=1$.



                      In general for an affine subspace of dimension $d$, we can define the space by $A(t_1,t_2,dots t_d)$, and all entries in $A$ are linear in the $t_i$. Then $det(A(t) - lambda)$ is an $n$th degree polynomial in all the $t_i$ and $lambda$. It is possible that the determinant has no dependence on any $t_i$, in which case we have a finite spectrum. Otherwise, we have a dependence on the $t_i$. Then $det(A(t)-lambda)=0$ has a solution in $t_1$ whenever at least one of the non-constant coefficients is nonzero. (In the above example, as long as the linear coefficient $1-lambdaneq 0$.) Since the leading coefficient (that is not a constant 0 polynomial) is an $n-1$th degree polynomial in $lambda$, it is zero at a most $n-1$ different places, and this is at most $n-1$ places that the spectrum can fail to be continuous. The spectrum only fails to be continuous when all of the coefficients in the $t_1$ polynomial are zero, so this is an upper bound. So, theorem:



                      For an affine subspace of $ntimes n$ matrices, the spectrum is either finite (of size at most $n$), or it is $mathbbCsetminus K$, where $K$ is a finite set of exceptions (of size at most $n-1$).






                      share|cite|improve this answer









                      $endgroup$



















                        1














                        $begingroup$

                        To expand on Christian Remling's answer a bit: in his example, setting $det(A(t) - lambda) = 0$ becomes $(1-lambda)t+lambda^3=0$, and solving for $t$ gives $t = x^3/(x-1)$ -- so for any $lambda in mathbbC$, we have $x in S$ by choosing this $t$, with the exception of $lambda=1$.



                        In general for an affine subspace of dimension $d$, we can define the space by $A(t_1,t_2,dots t_d)$, and all entries in $A$ are linear in the $t_i$. Then $det(A(t) - lambda)$ is an $n$th degree polynomial in all the $t_i$ and $lambda$. It is possible that the determinant has no dependence on any $t_i$, in which case we have a finite spectrum. Otherwise, we have a dependence on the $t_i$. Then $det(A(t)-lambda)=0$ has a solution in $t_1$ whenever at least one of the non-constant coefficients is nonzero. (In the above example, as long as the linear coefficient $1-lambdaneq 0$.) Since the leading coefficient (that is not a constant 0 polynomial) is an $n-1$th degree polynomial in $lambda$, it is zero at a most $n-1$ different places, and this is at most $n-1$ places that the spectrum can fail to be continuous. The spectrum only fails to be continuous when all of the coefficients in the $t_1$ polynomial are zero, so this is an upper bound. So, theorem:



                        For an affine subspace of $ntimes n$ matrices, the spectrum is either finite (of size at most $n$), or it is $mathbbCsetminus K$, where $K$ is a finite set of exceptions (of size at most $n-1$).






                        share|cite|improve this answer









                        $endgroup$

















                          1














                          1










                          1







                          $begingroup$

                          To expand on Christian Remling's answer a bit: in his example, setting $det(A(t) - lambda) = 0$ becomes $(1-lambda)t+lambda^3=0$, and solving for $t$ gives $t = x^3/(x-1)$ -- so for any $lambda in mathbbC$, we have $x in S$ by choosing this $t$, with the exception of $lambda=1$.



                          In general for an affine subspace of dimension $d$, we can define the space by $A(t_1,t_2,dots t_d)$, and all entries in $A$ are linear in the $t_i$. Then $det(A(t) - lambda)$ is an $n$th degree polynomial in all the $t_i$ and $lambda$. It is possible that the determinant has no dependence on any $t_i$, in which case we have a finite spectrum. Otherwise, we have a dependence on the $t_i$. Then $det(A(t)-lambda)=0$ has a solution in $t_1$ whenever at least one of the non-constant coefficients is nonzero. (In the above example, as long as the linear coefficient $1-lambdaneq 0$.) Since the leading coefficient (that is not a constant 0 polynomial) is an $n-1$th degree polynomial in $lambda$, it is zero at a most $n-1$ different places, and this is at most $n-1$ places that the spectrum can fail to be continuous. The spectrum only fails to be continuous when all of the coefficients in the $t_1$ polynomial are zero, so this is an upper bound. So, theorem:



                          For an affine subspace of $ntimes n$ matrices, the spectrum is either finite (of size at most $n$), or it is $mathbbCsetminus K$, where $K$ is a finite set of exceptions (of size at most $n-1$).






                          share|cite|improve this answer









                          $endgroup$



                          To expand on Christian Remling's answer a bit: in his example, setting $det(A(t) - lambda) = 0$ becomes $(1-lambda)t+lambda^3=0$, and solving for $t$ gives $t = x^3/(x-1)$ -- so for any $lambda in mathbbC$, we have $x in S$ by choosing this $t$, with the exception of $lambda=1$.



                          In general for an affine subspace of dimension $d$, we can define the space by $A(t_1,t_2,dots t_d)$, and all entries in $A$ are linear in the $t_i$. Then $det(A(t) - lambda)$ is an $n$th degree polynomial in all the $t_i$ and $lambda$. It is possible that the determinant has no dependence on any $t_i$, in which case we have a finite spectrum. Otherwise, we have a dependence on the $t_i$. Then $det(A(t)-lambda)=0$ has a solution in $t_1$ whenever at least one of the non-constant coefficients is nonzero. (In the above example, as long as the linear coefficient $1-lambdaneq 0$.) Since the leading coefficient (that is not a constant 0 polynomial) is an $n-1$th degree polynomial in $lambda$, it is zero at a most $n-1$ different places, and this is at most $n-1$ places that the spectrum can fail to be continuous. The spectrum only fails to be continuous when all of the coefficients in the $t_1$ polynomial are zero, so this is an upper bound. So, theorem:



                          For an affine subspace of $ntimes n$ matrices, the spectrum is either finite (of size at most $n$), or it is $mathbbCsetminus K$, where $K$ is a finite set of exceptions (of size at most $n-1$).







                          share|cite|improve this answer












                          share|cite|improve this answer



                          share|cite|improve this answer










                          answered 5 hours ago









                          Alex MeiburgAlex Meiburg

                          4912 silver badges13 bronze badges




                          4912 silver badges13 bronze badges































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