I am a mathematician specializing in algebraic combinatorics, discrete geometry, and representation theory, currently serving as an Assistant Professor of Mathematics at Lawrence University, in the small town of Appleton, Wisconsin.  My research program is driven by sustained focus on foundational open problems—such as the combinatorial characterization of generic infinitesimal rigidity in higher dimensions—seeking results that connect different areas of mathematics. I am equally devoted to the art of teaching and the liberal arts mission, striving to craft rigorous, highly immersive undergraduate experiences that invite students directly into the beauty and discovery of advanced mathematics.

Thanks for visiting my website. Please feel free to contact me via email at alexheaton2 at gmail dot com. For some recent work, see below.

• Generic Rigidity of Graph Frameworks in Euclidean Space

• Graded multiplicity in harmonic polynomials from the Vinberg setting

• Stable Graded Multiplicities for Harmonics on a Cyclic Quiver 

• Euclidean distance and maximum likelihood retractions by homotopy

• Facet volumes of polytopes

• Nonlinear Algebra and Applications 

• Hilbert series of typical representations for Lie superalgebras

• Catastrophe in Elastic Tensegrity Frameworks

• MPI MiS Research Brief: The ubiquity of linear orders in combinatorics.

• Minimality of tensors of fixed multilinear rank

• Logarithmic Voronoi cells

• Dual matroid polytopes and internal activity of independence complexes

• Symmetry adapted Gram spectrahedra

• Exact solutions in log-concave maximum likelihood estimation

• Epsilon local rigidity and numerical algebraic geometry

• Computing a logarithmic Voronoi cell

• An SOS counterexample to an inequality of symmetric functions

• Nonlinear algebra with tensegrity frameworks

• Branching from the general linear group to the symmetric group and the principal embedding

I am working on getting computations and code publicly available for all my projects. This means that major computations in each paper can be checked independently by anyone. In particular, you can check exactly what calculations were made.  So far you can find code for three projects on the MPI MiS mathrepo, available at the links below.

• In this Jupyter notebook we verify the sum of squares counterexample of https://arxiv.org/abs/1909.00081  by explicit computation. Dominance or majorization order fails to capture non-negativity relationships amongst the homogeneous symmetric functions.

• A statistical model is a set of probability distributions on the sample space. For discrete random variables this can be thought of as a subset of the probability simplex in a suitable Euclidean space. One result of https://arxiv.org/abs/2006.09431  states that, for linear models, the logarithmic Voronoi cells are always polytopes. One might hope that finite unions of linear models would admit logarithmic Voronoi cells which are polytopes. However, this is not the case. The log-normal spaces from two disjoint linear models can meet in such a way that the boundary created on a logarithmic Voronoi cell is nonlinear. For an explicit example with two linear models, we present the computations in this notebook.

• As a (very) special case of the main theorem of https://arxiv.org/abs/2007.08909 , the set of two by two matrices of rank 1 is a minimal submanifold of real four-dimensional space with the Frobenius norm.  Minimal submanifolds are a mathematical model of soap films, since they locally minimize volume given a fixed boundary. A minimal submanifold can be defined by the requirement that its mean curvature vector field be everywhere vanishing. In fact, the set of all tensors of any fixed multilinear rank forms a minimal submanifold of its ambient Euclidean space, which yields matrices of fixed rank as the special case we examine computationally in this notebook. The notebook also computes the mean curvature vector field of the independence model on two binary discrete random variables, of interest in statistics. This is displayed below.