How Large Must the Kernel of Polynomials in Matrices Be?

Update: If you want to hear more about this, there will actually be an online talk by Guillaume and Octavio on our paper, on Monday, September 13, in the UC Berkeley Probabilistic Operator Algebra Seminar.

Assume I have two symmetric matrices X and Y and I tell you the eigenvalues, counted with multiplicity, of each of them. Then I apply a polynomial P (which is also known to you) to those matrices and ask you to guess the size of the kernel of P(X,Y). If your guess is smaller than the actual size, the Queen of Hearts will pay out your guess in gold; otherwise, if your guess is too large, off with your head. Is there any strategy to survive this for sure and to get out as rich as possible? Let’s say, I don’t even tell you the size of the matrices and only give you the relative number of the eigenvalues, like: the first matrix X has 2/3 of its eigenvalues at 0, 1/6 at 1, and 1/6 at 2; the second matrix Y has 3/4 of its eigenvalues at -1, 1/8 at 0 and 1/8 at +1. What is your guess for the size of the kernel of the anti-commutator P(X,Y)=XY+YX? To be on the safe side you can of course always choose zero; this let’s you survive in any case, but it won’t make you rich. Is there a better guess, which still guarantees you keep your head?

My guess is 5/12. If you want to know how I get this and, in particular, how I can be so sure that this is the best safe bet – have a look on my new paper, joint with Octavio Arizmendi, Guillaume Cebron, Sheng Yin, “Universality of free random variables: atoms for non-commutative rational functions“, which we just uploaded to the arXiv.

If you want to think about the problem before having a look at the paper, take X as before, but Y having now 1/2 of its eigenvalues at -1, 3/8 at 0 and 1/8 at +1. Which of the following is your guess for the size of the kernel of the anti-commutator in this case:

  • 5/12 
  • 1/6
  • 1/2
  • 1/3

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