University of Notre Dame

I shall present a new flexible method showing that every countable model of PA admits a pointwise definable end-extension, one in which every point is definable without parameters. Also, any model of PA of size at most continuum admits an extension that is Leibnizian, meaning that any two distinct points are separated by some expressible property. Similar results hold in set theory, where one can also achieve V=L in the extension, or indeed any suitable theory holding in an inner model of the original model.

I will discuss recent progress on understanding the tmf-based Adams spectral sequence, where tmf = topological modular forms.  The idea is to generalize the work of Mahowald and others in the context of bo-resolutions.  The work I will discuss is joint with Prasit Bhattacharya, Dominic Culver, and J.D. Quigley.

Hardt-Simon proved that every area-minimizing hypercone $C$ having only an isolated singularity fits into a foliation of $R^{n+1}$ by smooth, area-minimizing hypersurfaces asymptotic to $C$. We prove that if a minimal hypersurface $M$ in the unit ball $B_1 \subset R^{n+1}$ lies sufficiently close to a minimizing quadratic cone (for example, the Simons' cone), then $M \cap B_{1/2}$ is a $C^{1,\alpha}$ perturbation of either the cone itself, or some leaf of its associated foliation. In particular, we show that singularities modeled on these cones determine the local structure not only of $M$, but of any nearby minimal surface. Our result also implies the Bernstein-type result of Simon-Solomon, which characterizes area-minimizing hypersurfaces in $R^{n+1}$ asymptotic to a quadratic cone as either the cone itself, or some leaf of the foliation.  This is joint work with Luca Spolaor.

Systems of nonlinear polynomial equations arise in a variety of fields in mathematics, science, and engineering.  Many numerical techniques for solving and analyzing solution sets of polynomial equations over the complex numbers, collectively called numerical algebraic geometry, have been developed over the past several decades.  However, since real solutions are the only solutions of interest in many applications, there is a current emphasis on developing new methods for computing and analyzing real solution sets.  This talk will summarize some numerical real algebraic geometric approaches as well as recent successes of these methods for solving a variety of problems in science and engineering.

The uniformly degenerate elliptic equation is a special class of degenerate elliptic equations. It appears frequently in many important geometric problems. For example, the Beltrami-Laplace operator on conformally compact manifolds is uniformly degenerate elliptic, and the minimal surface equation in the hyperbolic space is also uniformly degenerate elliptic. In this talk, we discuss the global regularity for this class of equations in the classical Holder spaces. We also discuss some applications.

The revolution in molecular biology within the last few decades has led to the identification of multiple, diverse inputs into the mechanisms governing the measurement and regulation of organ size. In general, organ size is controlled by both intrinsic, genetic mechanisms as well as extrinsic, physiological factors. Examples of the former include the spatiotemporal regulation of organ size by morphogen gradients, and instances of the latter include the regulation of organ size by endocrine hormones, oxygen availability and nutritional status. However, integrated model platforms, either of in vitro experimental systems amenable to high-resolution imaging or in silico computational models that incorporate both extrinsic and intrinsic mechanisms are lacking. Here, I will discuss collaborative efforts to bridge the gap between traditional assays employed in developmental biology and computational models through quantitative approaches. In particular, we have developed quantitative image analysis techniques for confocal microscopy data to inform computational models – a critical task in efforts to better understand conserved mechanisms of crosstalk between growth regulatory pathways. Currently, these quantitative approaches are being applied to develop integrated models of epithelial growth in the embryonic Drosophila epidermis and the adolescent wing imaginal disc, due to the wealth of previous genetic knowledge for the system. An integrated model of intrinsic and extrinsic growth control is expected to inspire new approaches in tissue engineering and regenerative medicine.

Continuing advances in computing technology provide the power not only to solve

increasingly large and complex process modeling and optimization problems, but also

to address issues concerning the reliability with which such problems can be solved.

For example, in solving process optimization problems, a persistent issue

concerning reliability is whether or not a global, as opposed to local,

optimum has been achieved. In modeling problems, especially with the

use of complex nonlinear models, the issue of whether a solution is unique

is of concern, and if no solution is found numerically, of whether there

actually exists a solution to the posed problem. This presentation

focuses on an approach, based on interval mathematics,

that is capable of dealing with these issues, and which

can provide mathematical and computational guarantees of reliability.

That is, the technique is guaranteed to find all solutions to nonlinear

equation solving problems and to find the global optimum in nonlinear

optimization problems. The methodology is demonstrated using several

examples, drawn primarily from the modeling of phase behavior, the

estimation of parameters in models, and the modeling, using lattice

density-functional theory, of phase transitions in nanoporous materials.