# Mathematics

## Classification and rigidity for group von Neumann algebras.

Any countable group G gives rise to a von Neumann algebra L(G). The classification of these group von Neumann algebras is a central theme in operator algebras. I will survey recent rigidity results which provide instances when various algebraic properties of groups, such as the presence or absence of a direct product decomposition, are remembered by their von Neumann algebras. I will also explain the strongest such rigidity results, where L(G) completely remembers G, and discuss some of the open problems in the area.

## Remarks on multi-marginals entropic optimal transport and Sinkhorn algorithm

Entropic optimal transport has received a lot of attention in recent years and has become a popular framework for computational optimal transport thanks to the Sinkhorn scaling algorithm. In this talk, I will discuss the multi-marginal case which arises in different applied contexts in physics, economics and machine learning. I will show in particular that the multi-marginal Schrödinger system is well posed (joint work with Maxime Laborde) and that the multi-marginal Sinkhorn algorithm converges linearly.

## Random Hyperbolic Surfaces Via Flat Geometry

Mirzakhani gave an inductive procedure to build random hyperbolic surfaces by gluing together smaller random pieces along curves. She proved that as the length of the gluing curve grows, these families equidistribute in the moduli space of hyperbolic surfaces. In this talk, I’ll explain how the conjugacy (exposited in James’s talk) between the earthquake and horocycle flows provides a template for translating equidistribution results for flat surfaces into equidistribution results for hyperbolic ones. Using this correspondence, we address Mirzakhani’s twist torus conjecture and exhibit new limiting distributions for hyperbolic surfaces built out of symmetric pieces. This is joint work (in progress) with James Farre.

## Optimal curvature in long-range cell-cell communication

Cells in tissue can communicate short-range via direct contact, and long-range via diffusive signals. In addition, another class of cell-cell communication is by long, thin cellular protrusions that are ~100 microns in length and ~100 nanometers in width. These so-called non-canonical protrusions include cytonemes, nanotubes, and airinemes. But, before establishing communication, they must find their target cell. Here we demonstrate airinemes in zebrafish are consistent with a finite persistent random walk model. We study this model by stochastic simulation, and by numerically solving the survival probability equation using Strang splitting. The probability of contacting the target cell is maximized for a balance between ballistic search (straight) and diffusive (highly curved, random) search. We find that the curvature of airinemes in zebrafish, extracted from live cell microscopy, is approximately the same value as the optimum in the simple persistent random walk model. We also explore the ability of the target cell to infer direction of the airineme’s source, finding the experimentally observed parameters to be at a Pareto optimum balancing directional sensing with contact initiation.

## Conjugating flows on the moduli of hyperboic and flat surfaces

A measured geodesic lamination on a hyperbolic surface encodes the

horizontal trajectory structure of certain quadratic differentials.

Thurston’s earthquake flow along such a lamination induces a dynamical

system on the moduli space of hyperbolic surfaces sharing many properties

with the classical Teichmüller horocycle flow. Mirzakhani gave a dynamical

correspondence between the earthquake and horocycle flows, defined

Lebesgue-almost everywhere. In this talk, we extend Mirzakhani’s conjugacy

and define an extension of the earthquake flow to an action of the upper

triangular group P in PSL(2,R) mapping certain flow lines to Teichmüller

geodesics. We classify the P-invariant ergodic probability measures as

those coming from affine invariant measures on quadratic differentials and

show that our map is a measurable isomorphism between P actions with

respect to these measures. This is joint work with Aaron Calderon.

## Cell symmetry breaking for movement through a mechanochemical mechanism

To initiate movement, cells need to form a well-defined "front" and "rear" through the process of cellular polarization. Polarization is a crucial process involved in embryonic development and cell motility and it is not yet well understood. Mathematical models that have been developed to study the onset of polarization have explored either biochemical or mechanical pathways, yet few have proposed a combined mechano-chemical mechanism. However, experimental evidence suggests that most motile cells rely on both biochemical and mechanical components to break symmetry. I will describe a mechano-chemical mathematical model for emergent organization driven by both cytoskeletal dynamics and biochemical reactions. We have identified one of the simplest quantitative frameworks for a possible mechanism for spontaneous symmetry breaking for initiation of cell movement. The framework relies on local, linear coupling between minimal biochemical stochastic and mechanical deterministic systems; this coupling between mechanics and biochemistry has been speculated biologically, yet through our model, we demonstrate it is a necessary and sufficient condition for a cell to achieve a polarized state.

## Stochasticity in an ecological model of the microbiome influences the efficacy of simulated bacteriotherapies

We consider a stochastic bistable two-species generalized Lotka-Volterra model of the microbiome and use it as a testbed to analytically and numerically explore the role of direct (e.g., fecal microbiota transplantation) and indirect (e.g., changes in diet) bacteriotherapies. Two types of noise are included in this model, representing the immigration of bacteria into and within the gut (additive noise) and variations in growth rate associated with the spatially inhomogeneous distribution of resources (multiplicative noise). The efficacy of a bacteriotherapy is determined by comparing the mean first-passage times (the average time required for the system to transition from one basin of attraction to the other) with and without the intervention. Concepts from transition path theory are used to investigate how the role of noise affects these bacteriotherapies.

## Density estimation under total positivity and conditional independence

Nonparametric density estimation is a challenging problem in theoretical statistics -- in general a maximum likelihood estimate (MLE) does not even exist! Introducing shape constraints allows a path forward.

In this talk I will first discuss non-parametric density estimation under total positivity (i.e. log-supermodularity) and log-concavity. Although they possess very special structure, totally positive random variables are quite common in real world data and have appealing mathematical properties. Given i.i.d. samples from a totally positive and log-concave distribution, we prove that the MLE exists with probability one assuming there are at least 3 samples. We characterize the domain of the MLE and if the observations are 2-dimensional, we show that the logarithm of the MLE is a tent function (i.e. a piecewise linear function) with "poles" at the observations, and we show that a certain convex program can find it.

I will finish by discussing density estimation for log-concave graphical models. As before, we show that the MLE exists and is unique with probability 1. We also characterize the domain of the MLE, and show how to find it if the graphical model corresponds to a chordal graph. I will conclude by discussing some future directions.

#### Speaker Biography

Dr. Robeva is an Assistant Professor with the Department of Mathematics at the University of British Columbia. From 2016 – 2019, Dr. Robeva was a Statistics Instructor and an NSF Postdoctoral Fellow in the Department of Mathematics and the Institute for Data, Systems, and Society, at the Massachusetts Institute of Technology. Dr. Robeva completed her PhD in 2016 from UC Berkeley, and won the Bernard Friedman Memorial Prize in Applied Mathematics, for her thesis.

#### About the Prize

The UBC-PIMS Mathematical Sciences Young Faculty Award prize was created by two founding donors, Anton Kuipers and Darrell Duffie, to recognize UBC researchers for their leading edge work in mathematics or its applications in the sciences. Dr Elina Robeva is the 2020 winner and will give her colloquium on Thursday April 21, 2021.

## Feedback onto cellular polarization from paxillin, implications for migrating cells

Cellular polarization plays a critical during cellular differentiation, development, and cellular migration through the establishment of a long-lived cell-front and cell-rear. Although mechanisms of polarization vary across cells types, some common biochemical players have emerged, namely the RhoGTPases Rac and Rho. The low diffusion coefficient of the active form of these molecules combined with their mutual inhibitory interaction dynamics have led to a prototypical pattern-formation system that can polarizes cell through a non-Turing pattern formation mechanism termed wave-pinning. We investigate the effects of paxillin, a master regulator of adhesion dynamics, on the Rac-Rho system through a positive feedback loop that amplifies Rac activation. We find that paxillin feedback onto the Rac-Rho system produces cells that (i) self-polarize in the absence of any input signal (i.e., paxllin feedback causes a Turing instability) and (ii) become arrested due to the development of multiple protrusive regions. The former effect is a positive finding that can be related to certain cell-types, while the latter outcome is likely an artefact of the model. In order to minimize the effects of this artefact and produce cells that can both self-polarize as well as migrate for extended periods of time, we revisit some of model's parameter values and use lessons from previous models of polarization. This approach allows us to draw conclusions about the biophysical properties and spatiotemporal dynamics of molecular systems required for autonomous decision making during cellular migration.

## Extrinsic and intrinsic controls of cortical flow regulate C. elegans embryogenesis

Cell division is a vital mechanism for cell proliferation, but it often breaks its symmetry during animal development. Symmetry-breaking of cell division, such as the orientation of the cell division axis and asymmetry of daughter cell sizes, regulates morphogenesis and cell fate decision during embryogenesis, organogenesis, and stem cell division in a range of organisms. Despite its significance in development and disease, the mechanisms of symmetry-breaking of cell division remain unclear. Previous studies heavily focused on the mechanism of symmetry-breaking at metaphase of mitosis, wherein a localized microtubule-motor protein activity pulls the mitotic spindle. Recent studies found that cortical flow, the collective migration of the cell surface actin-myosin network, plays an independent role in the symmetry-breaking of cell division after anaphase. Using nematode C. elegans embryos, we identified extrinsic and intrinsic cues that pattern cortical flow during early embryogenesis. Each cue specifies distinct cellular arrangements and is involved in a critical developmental event such as the establishment of the left-right body axis, the dorsal-ventral body axis, and the formation of endoderm. Our research started to uncover the regulatory mechanisms underlying the cortical flow patterning during early embryogenesis.