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Symmetry-Adapted Gram Spectrahedra
Algebra & Discrete Mathematics| Speaker: | Isabelle Shankar, UC Berkeley |
| Location: | 1147 MSB |
| Start time: | Mon, Feb 10 2020, 12:10PM |
Description
Sum of squares (SOS)
relaxations are often used to certify nonnegativity of polynomials and are equivalent to solving a semidefinite program (SDP). The feasible
region of the SDP for a given polynomial is the Gram Spectrahedron. For
symmetric polynomials, there are reductions to the problem size that can
be done using tools from representation theory. In joint work with
Alex Heaton, we used this machinery to disprove a conjecture about
symmetric function inequalities. I will give a brief introduction to the
theory used. Moreover, I will describe recent work with Serkan Hosten
on understanding the geometric structure of the spectrahedra that arise
in the study of symmetric SOS polynomials.
