Analysis, Logic, & Physics Seminar
Organized by Marco Aldi.
| Date | Time | Location | Speaker | Affiliation | Title |
|---|---|---|---|---|---|
| Sept.4 | 3:00 P.M. | Harris Hall 4145 | Eleftherios Chatzitheodoridis | Virginia Commonwealth University | Transfer systems and composition-closed premodel structures on lattices |
| Oct. 2 | TBA | TBA | Josh Turner | University of Virginia | Trees associated with unitary partition complexes |
In this talk I will describe a class of minimization problems arising in modelling shape memory alloys. I will start with a shape memory material illustration, followed by a simple one dimensional model of it. Its extensions in 2D and 3D will help us understand the energetic mechanism behind the formation of twin patterns in physical experiments. By means of sharp upper and lower bounds, we show that the experimentally observed structures provide optimal energy scaling law. Furthermore, under certain assumptions we will see that some of these patterns are true energy minimizers - a rare find in problems of this type! I will also discuss the extension of the linear elastic models for two twins to model multiscale patterns, which appear in recent physical experiments and involve mixing of four twins.
We consider particle interaction energies defined via a pairwise interaction kernel. These energies are directly related to, and can be considered as, discrete versions of continuous interaction energies defined over probability measures. In their discrete or continuum form, such pairwise interaction energies appear in many biological or physical applications, ranging from swarming models to models of molecular structure. Under rather general assumption on the interaction kernel we prove that the discrete energies admit minimizers for sufficiently large number of particles, they converge to their continuum counterpart in the weak-* topology of probability measures, and minimizer of discrete energies converge to the minimizer of the continuum energy. This is a joint work with Davide Carazzato and Aldo Pratelli.
Diffuse domain methods (DDMs) approximate partial differential equations on complex geometries by replacing the sharp boundary interface with a diffuse layer of thickness ε. This approach reformulates the original equation on an extended regular domain, incorporating boundary conditions through singular source terms. In this work, we conduct a matched asymptotic analysis of a DDM approximation for a two-sided problem with transmission Robin boundary conditions. Our results show that, in one dimension, the solution of the DDM approximation asymptotically converges to the solution of the original problem, with exactly first-order accuracy in ε. Furthermore, for the Neumann boundary condition case, we show that the energy functional of the DDM approximation Γ-converges to the energy functional of the original problem, and the solution of the DDM approximation strongly converges, up to a subsequence, to the solution of the original problem in H¹, as ε approaches 0. We also provide numerical simulations that validate and illustrate the analytical result.
I've successfully used set-theoretic ``almost everywhere" reasoning in recent years in a variety of settings (homological algebra, actions of monoids, Weak Factorization Systems in homotopy theory). Most recently, I used it to prove the Flat Cover Conjecture in categories of monoid actions over right-reversible monoids. Here, "almost everywhere" is defined in terms of a certain boolean algebra depending on the setting, and can be modeled using Shelah's Stationary Logic. For example, if P is a projective module over a ring, X is a subset of P, and <X> is the submodule generated by X, it's possible that the quotient P/<X> fails to be projective (e.g., Z is a projective Z-module but Z/2Z is not). But, P/<X> is projective for "almost every" subset X of P, and this is enough to (re)-prove a classic theorem of Kaplansky published in the Annals of Mathematics in the 1950s, that every projective module is a direct sum of countably generated modules. I will discuss how this reasoning works, and discuss some recent applications involving so-called cofibrantly-generated Weak Factorization Systems (a concept originating with Quillen's Small Object Argument).
This mathematical talk concerns the modeling and numerical simulations of the electropermeabilization (EP) phenomenon. Electropermeabilization occurs when biological cells are subjected to short electric pulses with sufficient amplitude and manifests itself in an increase of the cell membrane permeability.
To simulate EP, partial differential equations (PDEs) can be employed. In the existing dynamic models at the cell scale, the electric potential satisfies Poisson’s equation in intra- and extracellular domain with nonlinear dynamic transmission conditions on the membrane. The latter system can be rewritten as an abstract nonlinear evolution equation with a non-local operator, which is a combination of Dirichlet to Neumann maps. This equation is then coupled with a nonlinear ODE on the membrane describing its porosity.
In this talk, I will first introduce an EP model at the cell level and then demonstrate how homogenization techniques—particularly two-scale asymptotic expansions—can be applied to derive a macroscopic model for a large number of cells. I will also present recent numerical results and discuss their relevance in comparison with experimental data. The work is in collaboration with T. Gebäck and I. Pettersson.
In this talk, I will present recent advances in modeling the electric response of biological cells.
A nerve impulse is the propagation of a membrane potential along a nerve in response to various stimuli. To simulate the electrical behavior of biological tissues, we rely on partial differential equations. However, solving these equations analytically is rarely feasible—especially when a nerve bundle contains a large number of axons, which poses significant challenges even for modern numerical methods.
In this presentation, I will outline several electrophysiological models and explain how to derive more computationally tractable macroscopic equations. From a mathematical perspective, this leads to coupled systems of nonlinear evolution equations. Because the diameter of axons in a bundle is typically much smaller than the length of the nerve, we introduce a small parameter representing this ratio and seek an asymptotic approximation of the electric potential as this parameter tends to zero. The approach combines asymptotic analysis, homogenization techniques, and the method of monotone operators to handle the passage to the limit. I will provide a brief introduction to homogenization and focus primarily on the analytical aspects of the models rather than their numerical implementation. This work is done in collaboration with C. Jerez-Hanckes, I. Martinez, V.Rybalko, and A. Rybalko.
I’ll explain a paradigm that pops up repeatedly when people do mathematics – one might call it a generalized Galois correspondence, but it is hardly limited to algebra. Then I’ll give a parade of examples from analysis and linear algebra. Leading the parade will be the fact that in a Euclidean vector space, the perp of the perp of a set is the same as its linear span. Concluding the parade will be some concepts from old school matrix theory/operator theory, easy to understand but surprisingly subtle. As time allows I’ll adapt this to create some new things in operator algebras. By the end it will be clear why these results are quotable.
Anisotropic analogues of mean curvature flow have been considered as models for crystal growth and other phenomena involving the motions of interfaces. They are gradient flows for natural area-like functionals: $I(u) = \int F(\nu)\sqrt{1+|Du|^2} dx$, where F is homogeneous of degree 1. In this talk, I will introduce the contact angle and Neumann boundary value problem to anisotropic mean curvature flow over a convex domain. Our main results include a prior gradient estimate and long time behavior. The solutions converge to ones moving by translation. This talk is based on joint work with my Ph.D. advisor, Nung kwan (Aaron) Yip
We consider the vector Allen-Cahn (Modica-Mortola) energy with a 4-well potential. The goal is to produce a stable, diffuse version of a stable, tetrahedral cone in the absence of any symmetry assumptions. This is accomplished via standard Gamma-convergence theory once we can exhibit a bounded 3D domain which is partitioned by such a cone into a 4 chamber configuration which is a local minimizer of weighted surface area in a sufficiently weak topology.
An (∞, 1)-category is a category enriched in spaces, possibly weakly. Our understanding of (∞, 1)-categories has been advanced thanks to the development of various models for (∞, 1)-categories, that is, mathematical objects that exhibit the structure of an (∞, 1)-category. Two such models are complete Segal spaces, as introduced by Rezk, and Segal categories, as developed from the homotopical perspective by Bergner.
We introduce rational (∞, 1)-categories, which are (∞, 1)-categories enriched in spaces whose higher homotopy groups are rational vector spaces. We produce two models for rational (∞, 1)-categories, rational complete Segal spaces and rational Segal categories. Our argument works for enrichment in general localizations of spaces, such as the vn-periodic spaces of Heuts in unstable chromatic homotopy theory.
We examine two methods for classifying the complexity of countable structures: degree spectra, and Scott analysis. Degree spectra measure how difficult it is to compute copies of structures, while Scott analysis measures the complexity of describing structures up to isomorphism. We examine the possible degree spectra and Scott complexities of countable Presburger groups and compare these results with those for models of Peano Arithmetic. We also discuss how these measures of complexity succeed/fail in distinguishing the intended model of the theory.