The requirement to compute Jordan blocks for multiple eigenvalues arises in a number of physical problems, for example panel flutter problems in aerodynamical stability, the stability of electrical power systems, and in quantum mechanics. We introduce a general method for computing a 2-dimensional Jordan block in a parameter-dependent matrix eigenvalue problem based on the so called Implicit Determinant Method. This is joint work with Alastair Spence (Bath).

For many years, sum-factored algorithms for finite elements in rectangular reference geometry have combined low complexity with the mathematical power of high-order approximation.  However, such algorithms rely heavily on the tensor product structure inherent in the geometry and basis functions, and similar algorithms for simplicial geometry have proven elusive.

Bernstein polynomials are totally nonnegative, rotationally symmetric, and geometrically decomposed bases with many other remarkable properties that lead to optimal-complexity algorithms for element wise finite element computations.  The also form natural building blocks for the finite element exterior calculus bases for the de Rham complex so that H(div) and H(curl) bases have efficient representations as well.  We will also their relevance for explicit discontinuous Galerkin methods, where the element mass matrix requires special attention.

Given some class of "geometric spaces", we can make a ring as follows. Additive structure: when U is an open subset a space X,  [X] = [U] + [X - U]. Multiplicative structure:  [X][Y] = [XxY]. In the algebraic setting, this ring (the "Grothendieck ring of varieties") contains surprising structure, connecting geometry to arithmetic and topology.  I will discuss some remarkable
statements about this ring (both known and conjectural), and present new statements (again, both known and conjectural).  A motivating example will be polynomials in one variable. This is joint work with Melanie Matchett Wood.