# Video Content by Date

### 2020

Abstract:

This talk introduces a probabilistic approach to numerically compute geometric convergence rates in discrete or continuous stochastic systems. Choosing appropriate coupling mechanisms and combining them together, works well in many settings, especially in high-dimensions. Using this approach, it is observed that the rate of geometric ergodicity of a randomly perturbed system can, to some extent, reveal the degree of chaoticity of the unperturbed system. Potential applications of the coupling method and the visualization of higher dimensional non-convex functions, e.g., the loss functions of neural networks, will be discussed.

Abstract:

Recently there has been a lot of progress in classifying phases of gapped quantum many-body systems. From the mathematical viewpoint, a phase of a quantum system is a connected component of the “space” of gapped quantum systems, and it is natural to study the topology of this space. I will explain how to probe it using generalizations of the Berry curvature. I will focus on the case of lattice systems where all constructions can be made rigorous. Coarse geometry plays an important role in these constructions.

Dec, 7: Uniqueness of Clusters in Percolation
Speaker: Nishant Chandgotia
Abstract:

Suppose mu is a probability measure which is shift invariant on {0,1}^{Z^d} and we know that for almost every configuration x in {0,1}^{Z^d} there are connected components of 1s which are infinite. In this talk, we will follow a paper by Burton and Keane (generalising results by Aizenman, Kesten and Newman) to give an elegant proof of the fact that, under fairly general conditions (say full support), the number of connected components of infinite cardinality is at exactly one.

Abstract:

Measuring the impact of scientific articles is important for evaluating the research output of individual scientists, academic institutions, and journals. While citations are raw data for constructing impact measures, there exist biases and potential issues if factors affecting citation patterns are not properly accounted for. In this work, we address the problem of field variation and introduce an article-level metric useful for evaluating individual articles’ visibility. This measure derives from joint probabilistic modeling of the content in the articles and the citations among them using latent Dirichlet allocation (LDA) and the mixed membership stochastic blockmodel (MMSB). Our proposed model provides a visibility metric for individual articles adjusted for field variation in citation rates, a structural understanding of citation behavior in different fields, and article recommendations that take into account article visibility and citation patterns.

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Accessibility is a fundamental tool when working with partially hyperbolic systems. For instance, in the 1970s it was used as a tool to show certain systems were transitive, and in the 1990s it was used to establish stable ergodicity. We will review the general notion and how it applies in these settings. We will also review the result from 2003 by Dolgopyat and Wilkinson on the C^1 density of stably transitive systems.

Nov, 9: Smooth Realization and Conjugation By Approximation
Speaker: Alistair Windsor
Abstract:

Going back to the foundation work of von Neuman there is a question of whether there are smooth models of the models of classical ergodic theory. When both measure and map are required to be smooth there is only one known obstruction but essentially no general results. Within the class of zero entropy transformation we have a method called conjugation by approximation that can be used to realize many interesting properties. I will describe the method and some of the classical and modern consequences of this.

Nov, 6: Turán numbers for a 4-uniform hypergraph
Speaker: Karen Gunderson
Abstract:

For any $r\geq 2$, an $r$-uniform hypergraph $\mathcal{H}$, and integer $n$, the \emph{Tur\'{a}n number} for $\mathcal{H}$ is the maximum number of hyperedges in any $r$-uniform hypergraph on $n$ vertices containing no copy of $\mathcal{H}$. While the Tur\'{a}n numbers of graphs are well-understood and exact Tur\'{a}n numbers are known for some classes of graphs, few exact results are known for the cases $r \geq 3$. I will present a construction, using quadratic residues, for an infinite family of hypergraphs having no copy of the $4$-uniform hypergraph on $5$ vertices with $3$ hyperedges, with the maximum number of hyperedges subject to this condition. I will also describe a connection between this construction and a switching' operation on tournaments, with applications to finding new bounds on Tur\'{a}n numbers for other small hypergraphs.

Abstract:

Many systems exhibit a digit bias. For example, the first digit base 10 of the Fibonacci numbers or of 2^n equals 1 about 30% of the time; the IRS uses this digit bias to detect fraudulent corporate tax returns. This phenomenon, known as Benford's Law, was first noticed by observing which pages of log tables were most worn from age- it's a good thing there were no calculators 100 years ago! We'll discuss the general theory and application, talk about some fun examples (ranging from the 3x + 1 problem to the Riemann zeta function), and discuss some current open problems suitable for undergraduate research projects.

Nov, 4: Shape Recognition of Convex Bodies
Speaker: Sergii Myroshnychenko
Abstract:

A broad class of convex geometry problems deals with questions on retrieval of information about (convex) sets from data about different types of their projections, sections, or both. Examples of such assumptions are volume estimates, rigidity of structure, symmetry conditions etc.

In this talk, we will discuss known results and recent developments regarding the dual notions of point-projections and non-central sections of convex bodies. In particular, we provide a partial affirmative answer to the question on a shape recognition posed by A. Kurusa, and discuss a generalization of V. Klee's theorem for polyhedra.

Nov, 4: The Infinite HaPPY Code
Speaker: Monica Jinwoo Kang
Abstract:

I will construct an infinite-dimensional analog of the HaPPY code as a growing series of stabilizer codes defined respective to their Hilbert spaces. These Hilbert spaces are related by isometries that will be defined during this talk. I will analyze its system in various aspects and discuss its implications in AdS/CFT. Our result hints that the relevance of quantum error correction in quantum gravity may not be limited to the CFT context.

For other events in this series see the quanTA events website.

Nov, 2: What is a Foster-Lyapunov-Margulis Function?
Speaker: Jayadev Athreya, University of Washington
Abstract:

We'll show how a simple idea from probability theory on the recurrence of random walks can be used in many important dynamical and geometric situations, building on work of Eskin-Margulis and others. No prior knowledge of probability theory, random walks, or geometry is required. If time permits, as an unrelated "dessert" of sorts, we'll give a brief proof of the Hopf ratio ergodic theorem using the Birkhoff ergodic theorem for flows.

Oct, 29: The Cost of 2-Distinguishing Hypercubes
Speaker: Debra Boutin
Abstract:

The distinguishing number of a graph is the smallest number of colors necessary to color the vertices so that no nontrivial automorphism preserves the color classes. If a graph can be distinguished with two colors, the distinguishing cost is the smallest possible size of a color class over all 2-distinguishing colorings. In this talk I will present the long-sought-after (at least by me, :-) ) cost of 2-distinguishing hypercubes. We will begin the talk with definitions and intuitive examples of distinguishing and of cost, cover a bit of history, and work our way to a new technique using binary matrices. Then will we be able to state and understand the new results on hypercubes.

Oct, 26: 2020 PIMS-UBC Math Job Forum for Postdoctoral Fellows and Graduate Students
Speaker: Andrew Brown, Eugene Li, Kathryn Nyman, Brian Wetton
Abstract:

The PIMS-UBC Math Job Forum is an annual Forum to help graduate students and postdoctoral fellows in Mathematics and related areas with their job searches. The session is divided in two parts: short presentations from our panel followed by a discussion.

Learn the secrets of writing an effective research statement, developing an outstanding CV, and giving a winning job talk. We will address questions like: Who do I ask for recommendation letters? What kind of jobs should I apply to? What can I do to maximize my chances of success?

Oct, 26: An invitation to "Entropy in Dimension One"
Speaker: Kathryn Lindsey
Abstract:

Which real numbers arise as the entropies of continuous, multimodal, postcritically finite self-maps of real intervals? This is the "one-dimensional" analogue of a more famous open question: which real numbers arise as the dilatations of pseudo-Anosov surface diffeomorphisms? In "Entropy in Dimension One," W. Thurston answers this one-dimensional version of the question. We'll discuss a small subset of the many beautiful ideas and questions in this paper.

Oct, 19: Measure rigidity of Cartan actions
Speaker: Kurt Vinhage
Abstract:

We'll take an introductory peek into the measure rigidity program for higher-rank abelian actions by looking at the simplest case, Anosov Z^k actions on (k+1)-dimensional tori. The main structures and ideas appearing in the theory will be explained, as well as how the situation becomes more complicated under fewer assumptions.

Oct, 14: Packings of Partial Difference Sets
Speaker: Shuxing Li
Abstract:

As the underlying configuration behind many elegant finite structures, partial difference sets have been intensively studied in design theory, finite geometry, coding theory, and graph theory. Over the past three decades, there have been numerous constructions of partial difference sets in abelian groups with high exponent, accompanied by numerous very different and delicate techniques. Surprisingly, we manage to unify and extend a great many previous constructions in a common framework, using only elementary methods. The key insight is that, instead of focusing on one single partial difference set, we consider a packing of partial difference sets, namely, a collection of disjoint partial difference sets in a finite abelian group. Although the packing of partial difference sets has been implicitly studied in various contexts, we recognize that a particular subgroup reveals crucial structural information about the packing. Identifying this subgroup allows us to formulate a recursive lifting construction of packings in abelian groups of increasing exponent.

This is joint work with Jonathan Jedwab.

#### Speaker Bio

Shuxing Li received his Ph. D. degree in Mathematics from Zhejiang University, China, in 2016. From September 2016 to September 2017, he was a postdoctoral fellow at Department of Mathematics, Simon Fraser University. He was an Alexander von Humboldt Postdoctoral Fellow from October 2017 to September 2019, at Faculty of Mathematics, Otto von Guericke University Magdeburg, Germany. Since November 2019, he is a PIMS Postdoctoral Fellow at Department of Mathematics, Simon Fraser University. His research focuses on finite configurations with strong symmetry, which involves algebraic and combinatorial design theory, algebraic coding theory, and finite geometry. In 2018, he received the Kirkman Medal from the Institute of Combinatorics and its Applications in recognition of the excellence of his research.

Abstract:

I will discuss a lemma which is usually attributed to Atkinson, is very useful and apparently has been rediscovered multiple times. The lemma says that if (X, B, mu, T) is an ergodic system and f is in L^1(mu) with mean zero, then the Birkhoff sums of f do not diverge almost surely. Moreover the sums switch signs in a wide sense, infinitely many times. I will give the proof and discuss some applications of this result. Then I will discuss higher dimensional analogues, where the situation is significantly more complicated.

Abstract:

Pick a point at random in a finite volume hyperbolic surface and simultaneously flow in all directions from it. For the typical starting point these expanding circles will equidistribute and this talk will present a (more general) argument of Margulis establishing this fact.

Abstract:

Over fifty years ago Richard Kenneth Guy joined the then Department of Mathematics, Statistics and Computer Science at the nascent University of Calgary. Although he retired from the University in 1982, he continued, even in his last year, to come in to the University every day and work on the mathematics that he loved. In this talk I will provide a glimpse into the life and research of this most remarkable man. In doing this, I will recount several of the important events of Richard’s life and briefly discuss some of his mathematical contributions.

: Dr. Hugh Williams is internationally recognized as an expert in computational number theory and its applications to cryptography. Shortly after obtaining his Ph.D. in 1969 from the Department of Applied Analysis and Computer Science at the University of Waterloo, he joined the newly established Department of Computer Science at the University of Manitoba, where he was promoted to the rank of Full Professor in 1979. He also served there as Associate Dean of Science for Research Development for seven years (1994-2001). He moved to the University of Calgary in 2001 to take up the iCORE Chair for Algorithmic Number Theory and Cryptography (2001-2013) and retired as Emeritus Professor of Mathematics and Statistics in 2016. Dr. Williams has authored over 150 refereed journal papers, 30 refereed conference papers and 20 books or book chapters, and from 1983-85 held a national Killam Research Fellowship. In February 2009, Dr, Williams was selected for a six year term as the inaugural Director of the Tutte Institute for Mathematics and Computing (TIMC), a highly classified research facility established by the federal government. In 2016, he was appointed Professor Emeritus in Mathematics and Statistics at the University of Calgary.

Abstract:

Richard Guy was a supporter of the database of integer sequences right from its beginning in the 1960s. This talk will be illustrated by sequences that he contributed, sequences he wrote about, and especially sequences with open problems that he would have liked but that I never got to tell him about.

Oct, 2: Crossing Numbers of Large Complete Graphs
Speaker: Noam Elkies
Abstract:

TBA

Abstract:

An account of how a great Guy and his Brown coauthor created a 300-page book entitled "The Unity of Combinatorics" out of a 30-page paper from 1995 of the same name. The latter was an outline of a proposed lecture series, whose purpose was to feature the many connections within the vast area of combinatorics, thereby dispelling the then prevalent notion that combinatorics is just a bag of tricks. In writing the book, we took this notion and ran with it --- and how!

I'll talk about a number of these connections and some topics that seem almost magical, including Beatty sequences, Conway worms, games played with turtles instead of coins, and a way of viewing the non-negative integers as a field. The book begins with a child playing with colored blocks on his living-room rug and ends with a description of the Miracle Octad Generator. Finally, I'll talk about working with this gentlemanly giant of the world of numbers and sequences and patterns and games.

Oct, 2: Aliquot sequences
Speaker: Carl Pomerance
Abstract:

These are sequences formed by iterating the sum-of-proper-divisors function. For example: 12, 16, 15, 9, 4, 3, 1, 0. Of interest since Pythagoras, who remarked on the fixed point 6 (a perfect number) and the 2-cycle 220, 284 (an amicable pair), aliquot sequences were also one of Richard Guy's favorite subjects. The Catalan--Dickson conjecture asserts that every aliquot sequence is bounded (either terminates at zero or becomes periodic), while the Guy--Selfridge counter-conjecture asserts that many aliquot sequences diverge to infinity. It is interesting that Guy and Selfridge would make such a claim since no aliquot sequence is known to diverge, though the numerical evidence is certainly suggestive. The first case in doubt is the sequence beginning with 276. This talk will survey what's known about the problem and give evidence for and against the two countervailing views.

Abstract:

Richard started the Unsolved Problems in Combinatorial Games Column. I'll consider some of his favourites, talk about some developments, and add a few reminiscences.

Oct, 2: The favorite elliptic curve of Richard
Speaker: Jaap Top
Abstract:

Even in the title of one of his papers, Richard Guy called the elliptic curve with equation $y^2 = x^3 - 4x + 4$ his favorite. During the CNTA-XIV meeting in Calgary in 2016, I recalled some of his reasons for this (with Richard listening from the front row). The story as well as a few additional developments will also be the topic of the present lecture.

Oct, 2: The Notorious Collatz conjecture
Speaker: Terence Tao
Abstract:

Start with any natural number. If it is even, divide it by two. If instead it is odd, multiply it by three and add one. Now repeat this process indefinitely. The Collatz conjecture asserts that no matter how large an initial number one starts with, this process eventually reaches the number one (and then loops back to one indefinitely after that). This conjecture has been tested for quintillions of initial numbers, but remains unsolved in general; it is perhaps one of the simplest to state problems in all of mathematics that remains open; it is also one of the most notorious "mathematical diseases" that can lure professional and amateur mathematicians alike into devoting hours of futile effort into trying to solve the problem. While it is itself mostly a curiosity, and the full resolution still remains well out of reach of current technology, the Collatz problem is a model example of the more general concept of a dynamical system, which occurs throughout mathematics and science; and so progress on the Collatz conjecture can shed some light on the more general problem of understanding dynamical systems. In this lecture we give some of the history of the Collatz conjecture and some of its variants, and also describe some recent partial results on the problem.

Terence Tao was born in Adelaide, Australia in 1975. He has been a professor of mathematics at UCLA since 1999. Tao's areas of research include harmonic analysis, PDE, combinatorics, and number theory. He has received a number of awards, including the Fields Medal in 2006, the MacArthur Fellowship in 2007, the Waterman Award in 2008, and the Breakthrough Prize in Mathematics in 2015. Terence Tao also currently holds the James and Carol Collins chair in mathematics at UCLA, and is a Fellow of the Royal Society and the National Academy of Sciences.

Abstract:

Quantum phase transitions occur when a quantum system undergoes a sharp change in its ground state, e.g. between a ferro- and para-magnet. I will present a remarkable set of transitions, called quantum critical, that are described by conformal field theories (CFTs). I will focus on 2 and 3 spatial dimensions, where the conformal symmetry is powerful yet less constraining than in 1 dimension. We will probe these scale-invariant theories via the structure of their quantum entanglement. The methods will include large-N expansions, the AdS/CFT duality from string theory, and large-scale numerical simulations. Finally, we’ll see that certain quantum Hall states, which are topological in nature, possess very similar entanglement properties. This hints at broader principles that relate very different quantum states.

For other events in this series see the quanTA events website.

Sep, 27: Weak factorization and transfer systems
Speaker: Kyle Ormsby
Abstract:

Transfer systems are discrete objects that encode the homotopy theory of N∞ operads, i.e., the operads whose algebras are homotopy commutative monoids with a class of equivariant transfer (or norm) maps. They have a rich combinatorial structure defined in terms of the subgroup lattice of the group of equivariance, G. Indeed, if G is a cyclic p-group, there are Catalan-many transfer systems that assemble into the Tamari lattice (i.e., associahedron). In this talk, I will show that when G is finite Abelian, transfer systems are in natural bijection with weak factorization systems on the poset category of subgroups of G. This leads to a novel involution on the lattice of transfer systems, generalizing an observation of Balchin–Bearup–Pech–Roitzheim for cyclic groups of squarefree order. I will conclude with an enumeration of saturated transfer systems and comments on the Rubin and Blumberg–Hill saturation conjecture.

This is joint work with Angélica Osorno and a team of Reed College undergraduates: Evan Franchere, Usman Hafeez, Peter Marcus, Weihang Qin, and Riley Waugh (the Electronic Collaborative Mathematics Research Group, or eCMRG).

Abstract:

Representation stability, formalized in 2012 by Church, Ellenberg, and Farb, is a property exhibited by the homology of the configuration space of points in the plane: even as the number of points goes to infinity, the jth homology is generated by cycles in which at most 2j of the points move. What about the configuration space of disks of width 1 in an infinite strip of width w? This disks in a strip space behaves more like the no-k-equal configuration space of the line, where k-1 but not k points may be collocated; we show that the homology of this no-k-equal space exhibits generalized representation stability as defined by Sam–Snowden and Ramos. The method is to compute homology combinatorially using discrete Morse theory. Unlike other examples of homology with generalized representation stability, here the asymptotic behavior depends on the degree of homology.

Sep, 27: Characterizing handle-ribbon knots
Speaker: Maggie Miller
Abstract:

Kauffman conjectured that a knot K is slice if and only if it bounds a genus-g Seifert surface containing a g-component slice link as a cut system. It’s very easy to show that a knot is ribbon if and only if it bounds a genus-g Seifert surface containing a g-component unlink as a cut system. Alex Zupan and I proved something in the middle of these statements: a knot is handle-ribbon (aka strongly homotopy-ribbon, aka something I will define in the talk) if and only if it bounds a genus-g Seifert surface containing a g-component R link L as a cut system—meaning that zero-surgery on L yields #_ g S^1 × S^2 . This gives a 3-dimensional definition of a 4-dimensional property. I’ll talk about these 3.5D knot properties and maybe how we use these techniques to extend a statement of Casson and Gordon. (The work in this talk is joint with Alexander Zupan from the University of Nebraska–Lincoln.)

Abstract:

Given a knot K in the 3-sphere, the 4-genus of K is the minimal genus of an orientable surface embedded in the 4-ball with boundary K. If the knot K has a symmetry (e.g., K is periodic or strongly invertible), one can define the equivariant 4-genus by only minimising the genus over those surfaces in the 4-ball which respect the symmetry of the knot. I'll discuss ongoing work with Keegan Boyle trying to understand the equivariant 4-genus.

Sep, 26: Enumerative geometry via the A^1-degree
Speaker: Sabrina Pauli
Abstract:

Morel's $A^1$ -degree in $A^1$-homotopy theory is the analog of the Brouwer degree in classical topology. It takes values in the Grothendieck-Witt ring $GW(k)$ of a field $k$, that is the group completion of isometry classes of non-degenerate symmetric bilinear forms. We can use the $A^1$ -degree to count algebro-geometric objects in $GW(k)$, giving an $A^1$-enumerative geometry over non-algebraically closed fields. Taking the rank and the signature recovers classical counts over the complex and the real numbers, respectively. For example, the count of lines on a smooth cubic surface enriched in $GW(k)$ has rank 27 and signature 3.

Sep, 23: Random discrete surfaces
Speaker: Thomas Budzinski
Abstract:

A triangulation of a surface is a way to divide it into a finite number of triangles. Let us pick a random triangulation uniformly among all those with a fixed size and genus. What can be said about the behaviour of these random geometric objects when the size gets large? We will investigate three different regimes: the planar case, the regime where the genus is not constrained, and the one where the genus is proportional to the size. Based on joint works with Baptiste Louf, Nicolas Curien and Bram Petri.

Aug, 6: PIMS Summer Public Lecture: John Mighton
Speaker: John Mighton
Abstract:

Math provides us with mental tools of incredible power. When we learn math we learn to see patterns, to think logically and systematically, to draw analogies, to perceive risk, to understand cause and effect--among many other critical skills.

Yet we tolerate and in fact expect a vast performance gap in math among students and live in a world where many adults aren't equipped with these crucial tools. This learning gap is unnecessary, dangerous and tragic, and it has led us to a problem of intellectual poverty which is apparent everywhere--in fake news, political turmoil, floundering economies, even in erroneous medical diagnoses.

The study of math is an ideal starting point to break down social inequality and empower individuals to build a smarter, kinder, more equitable world. In this talk Mighton will share his vision for a numerate society for all, not just a chosen few.

### Speaker Biography

Dr. John Mighton is a playwright turned mathematician and author who founded JUMP Math as a charity in 2001. His work in fostering numeracy and in building children's self-confidence through success in math has been widely recognized. He has been named a Schwab Foundation Social Entrepreneur of the Year, an Ernst & Young Social Entrepreneur of the Year for Canada, an Ashoka Fellow, an Officer of the Order of Canada, and has received five honorary doctorates. John is also the recipient of the 10th Annual Egerton Ryerson Award for Dedication to Public Education.

John developed JUMP Math to address both the tragedy of low expectations for students and that of math anxiety in teachers. John began tutoring children in math as a financially-struggling playwright, and his success in helping students achieve levels of success that teachers and parents had thought impossible fueled his belief that everyone has great untapped potential.

The experience of repeatedly witnessing the heart-breaking paradox of high potential and low achievement led him to conclude that the widely-held assumption that mathematical talent is a rare genetic gift has created a self-fulfilling prophecy of low achievement. A generally high level of math anxiety among many elementary school teachers, itself an outcome of that belief system, creates an additional challenge.
John had to overcome his own "massive math anxiety" before making the decision to earn a Ph.D. in Mathematics at the University of Toronto. He was later awarded an NSERC Fellowship for postdoctoral research in knot and graph theory. He is currently a Fellow of the Fields Institute for Research in Mathematical Sciences and has taught mathematics at the University of Toronto. He has also lectured in philosophy at McMaster University, where he received a master’s degree in philosophy.

His plays have been performed around the world and he is the recipient of several national awards for theatre, including two Governor General’s Awards. He played the role of Tom in the film Good Will Hunting.

Abstract:

Malaria is a leading cause of death in many low-income countries despite being preventable, treatable and curable. One of the major roadblocks to malaria elimination is the emergence and spread of antimalarial drug resistance, which evolves when malaria parasites are exposed to a drug for prolonged periods. In this talk, I will introduce several statistical and mathematical models for monitoring the emergence and spread of antimalarial drug resistance. Results will be presented from a Bayesian geostatistical model that have generated spatio-temporal predictions of resistance based on prevalence data available only at discrete study locations and times. In this way, the model output provides insight into the spatiotemporal spread of resistance that the discrete data points alone cannot provide. I will discuss how the results of these models have been used to update public health policy.

Abstract:

Systemic chemotherapy is one of the main anticancer treatments used for most kinds of clinically diagnosed tumors. However, the efficacy of these drugs can be hampered by the physical attributes of the tumor tissue, such as tortuous vasculature, dense and fibrous extracellular matrix, irregular cellular architecture, metabolic gradients, and non-uniform expression of the cell membrane receptors. This can impede the transport of therapeutic agents to tumor cells in quantities sufficient to exert the desired effect. In addition, tumor microenvironments undergo dynamic spatio-temporal changes during treatment, which can also obstruct the observed drug efficacy. To examine ways to improve drug delivery on a cell-to-tissue scale (single-cell pharmacology), we developed the microscale pharmacokinetics/pharmacodynamics modeling framework “microPKPD”. I will present how this framework can be used to design optimal schedules for various treatments and to investigate the development of drug-induced resistance.

Abstract:

We study the problem of classifying stationary measures and orbit closures for non-abelian action on surfaces. Using a result of Brown and Rodriguez Hertz, we show that under a certain average growth condition, the orbit closures are either finite or dense. Moreover, every infinite orbit equidistributes on the surface. This is analogous to the results of Benoist-Quint and Eskin-Lindenstrauss in the homogeneous setting, and the result of Eskin-Mirzakhani in the setting of moduli spaces of translation surfaces.

We then consider the problem of verifying this growth condition in concrete settings. In particular, we apply the theorem to two settings, namely discrete perturbations of the standard map and the \Out(F_2)-action on a certain character variety. We verify the growth condition analytically in the former setting, and verify numerically in the latter setting.

Abstract:

The first response of epithelial cells to local wounds is a dramatic increase in cytosolic calcium. This increase occurs quickly – calcium floods into damaged cells within 0.1 s, moves into adjacent cells over ~20 s, and appears in a much larger set of surrounding cells via a delayed second expansion over 40-300 s – but calcium is nonetheless a reporter: cells must detect wounds even earlier. Using the calcium response as a proxy for wound detection, we have identified an upstream G-protein-coupled-receptor (GPCR) signaling pathway, including the receptor and its chemokine ligand. We present experimental and computational evidence that multiple proteases released during cell lysis/wounding serve as the instructive signal, proteolytically liberating active ligand to diffuse to GPCRs on surrounding epithelial cells. Epithelial wounds are thus detected by the activation of a protease bait. We will discuss the experimental evidence and a corresponding computational model developed to test the plausibility of these hypothesized mechanisms. The model includes calcium currents between each cell’s cytosol and its endoplasmic reticulum (ER), between cytosol and extracellular space, and between the cytosol of neighboring cells. These calcium currents are initiated in the model by cavitation-induced microtears in the plasma membranes of cells near the wound (initial influx), by flow through gap junctions into adjacent cells (first expansion), and by the activation of GPCRs via a proteolytically activated diffusible ligand (second expansion). We will discuss how the model matches experimental observations and makes experimentally testable predictions.

Supported by NIH Grant 1R01GM130130.

Jul, 8: From 1918 to 2020: Analyzing the past and forecasting the Future
Speaker: David Earn, Jonathan Dushoff
Abstract:

Comparisons are constantly being made between the 1918 influenza pandemic and the present COVID-19 pandemic. We will discuss our previous work on influenza pandemics, and the tools we have used to understand the temporal patterns of those outbreaks. Applying similar tools to the COVID-19 pandemic is easier in some respects and harder in others. We will describe our current approach to modelling the spread of COVID-19, and some of the challenges and limitations of epidemic forecasting.

Abstract:

"Quantitative weak mixing" is the term used to bound the dimensions of spectral measures of a measure-preserving system. This type of study has gained popularity over the last decade, led by a series of results of Bufetov and Solomyak for a large class of flows which include general one-dimensional tiling spaces as well as translation flows on flat surfaces, as well as results on quantitative weak mixing by Forni. In this talk I will present results which extend the results for flows to higher rank parabolic actions, focusing on quantitative results for a broad class of tilings in any dimension. The talk won't assume familiarity with almost anything, so I will define all objects in consideration.

Abstract:

Furstenberg proved that the horocycle flow on any compact quotient of SL(2,R) is uniquely ergodic. This has been generalized by many people. I will present a proof due to Yves Coudène, which I find elegant and can prove some of the generalizations of Furstenberg's theorem too.

Jun, 26: Geometric Langlands for hypergeometric sheaves
Speaker: Masoud Kamgarpour
Abstract:

Generalised hypergeometric sheaves are rigid local systems on the punctured projective line with remarkable properties. Their study originated in the seminal work of Riemann on the Euler--Gauss hypergeometric function and has blossomed into an active field with connections to many areas of mathematics. I will report on a joint work with Lingfei Yi, where we construct the Hecke eigensheaves whose eigenvalues are the irreducible hypergeometric local systems. This confirms a central conjecture of the geometric Langlands program for hypergeometrics. The key tool we use is the notion of rigid automorphic data due to Zhiwei Yun. This talk is based on the preprint arXiv:2006.10870.

Jun, 26: On generalized hyperpolygons
Speaker: Laura Schaposnik
Abstract:

In this talk we will introduce generalized hyperpolygons, which arise as Nakajima-type representations of a comet-shaped quiver, following recent work joint with Steven Rayan (arXiv:2001.06911). After showing how to identify these representations with pairs of polygons, we shall associate to the data an explicit meromorphic Higgs bundle on a genus-g Riemann surface, where g is the number of loops in the comet. We shall see that, under certain assumptions on flag types, the moduli space of generalized hyperpolygons admits the structure of a completely integrable Hamiltonian system. Time permitting, we shall conclude the talk by mentioning some partial results on current work on the construction of triple branes (in the sense of Kapustin-Witten mirror symmetry), and dualities between tame and wild Hitchin systems (in the sense of Painlevé transcendents).

Jun, 25: Finding mirrors for Fano quiver ﬂag zero loci
Speaker: Elana Kalashnikov
Abstract:

One interesting feature of the classiﬁcation of smooth Fano varieties up to dimension three is that they can all be described as certain subvarieties in GIT quotients; in particular, they are all either toric complete intersections (subvarieties of toric varieties) or quiver ﬂag zero loci (subvarieties of quiver ﬂag varieties). Fano varieties are expected to mirror certain Laurent polynomials; given such a Fano toric complete intersection, one can produce a Laurent polynomial via the Landau-Ginzburg model. In this talk, I’ll discuss ﬁnding mirrors of four dimensional Fano quiver ﬂag zero loci via ﬁnding degenerations of the ambient quiver ﬂag varieties. These degenerations generalise the Gelfand-Cetlin degeneration, which in the Grassmannian case has an important role in the cluster structure of its coordinate ring.

Jun, 25: Exact Lagrangians in conical symplectic resolutions
Speaker: Filip Zivanovic
Abstract:

Conical symplectic resolutions are a vast family of holomorphic symplectic manifolds that appear in representation theory, algebraic and differential geometry, and also in theoretical physics. Their typical examples arise from the hyperkähler quotient construction (quiver and hypertoric varieties) but also from the representation theory of Lie algebras (resolutions of Slodowy varieties, slices in affine Grassmannians). In this talk, I will focus on their symplectic topology. In particular, we find families of non-isotopic exact Lagrangian submanifolds in them arising from different C*-actions. These Lagrangians have a very nice symplectic topology; in particular, we conjecture (work in progress) that all of their Floer-theoretic invariants are completely determined by their topology. At the end of the talk, I will discuss the special cases of Nakajima quiver varieties and resolutions of Slodowy varieties, where their count becomes feasible and interesting in its own.

Jun, 25: Birational geometry of quiver varieties
Speaker: Gwyn Bellamy
Abstract:

In this talk I will report on joint work in progress with A. Craw and T. Schedler on the birational geometry of quiver varieties. We give an explicit local description of the birational transformations that occur under variation of GIT for quiver varieties. The main consequence of this local picture is that one can show that all Q-factorial terminalizations of quiver varieties (excluding the (2,2) case) can be obtained by VGIT. I will try to explain what our results mean in two concrete classes of examples. Namely, for framed affine Dynkin quivers (corresponding to wreath product quotient singularities) and star shape quivers (corresponding to hyperpolygon spaces).

Abstract:

We prove the conjecture by Gyenge, Némethi and Szendrői in arXiv:1512.06844, arXiv:1512.06848 giving a formula of the generating function of Euler numbers of Hilbert schemes of points Hilbn(C2/Γ) on a simple singularity C2/Γ, where Γ is a finite subgroup of SL(2). This is based on my preprint arXiv:2001.03834.

Abstract:

The talk describes a substantial extension of the Middle East Respiratory Syndrome (MERS) model constructed, analyzed and simulated in Al-Asuoad et. al. BIOMATH 5 (2016)1, Al-Asuoad, Oakland University Dissertation (2017), and Al-Asuoad and Shillor, BIOMATH 7(1)(2018)2 to the case of the current COVID-19 Respiratory Syndrome pandemic that is sweeping the globe. It is caused by the new SARS-CoV-2 coronavirus that has been identified in December 2019 and since then outbreaks have been reported in all parts of the world. To help predict the dynamics and possible controls of the pandemic we developed a mathematical model for the pandemic. The model has a compartmental structure similar but more complex to the SARS and MERS models. It is a coupled system of nonlinear ordinary differential equations (ODEs) and a differential inclusion for the contact rate parameter. The talk will describe the model in detail, mention some of its analysis, and describe our computer simulations of the pandemic in South Korea. The main modeling novelties are in taking into account the shelter-in-place directives, the rates at which the populations obey them and the observed changes in the infectiveness of ‘contact number’ of the SARS-CoV-2 virus. The model predictions are fitted to some of the data from the outbreak in South Korea. Since the DFE (in South Korea) is found to be asymptotically stable, the pandemic will eventually die out (as long as some control measures remain in place). And, indeed, the model simulations show that the COVID-19 will in the near future be contained. However, the containment time and the severity of the outbreak depend crucially on the contact coefficients and the isolation or shelter-in-place rate constant. The simulations show that when randomness is added to the model coefficients the model captures the pandemic dynamics very well. Finally, the model highlights the importance of isolation of infected individuals and may be used to assess other control measures. It is general and will be used to analyze outbreaks in other parts of the world.

*with Aycil Cesmelioglu and Anna M. Spagnuolo

1 http://dx.doi.org /10.11145/j.biomath.2016.12.141
2 http://dx.doi.org/10.11145/j.biomath.2018.02.277

Abstract:

We assess Ontario’s reopening plans, taking into account the healthcare system capacity and uncertainties in contact rates during different reopening phases. Using stochastic programming and a disease transmission model, we find the optimal timing for each reopening phase that maximizes the relaxation of social contacts under uncertainties, while not overwhelming the health system capacity by an expected arrival time of a SARS-CoV-2 vaccine/drug.

* Written with Michael Chen and LIAM De-escalation Group

Abstract:

It is common in SIR models to assume that the infection rate is proportional to the product S*I of susceptible and infected individuals. This form is motivated by the law of mass action from chemistry. While this assumption works at the onset of the outbreak, it needs to be modified at higher rates such as seen currently in much of the world (as of June 2020). We propose a physics-based model which leads to a simple saturation formula based on first principles incorporating the spread radius and population density. We then apply this modified SIR model to coronavirus and show that it fits much better than the classical'' law of mass action.

Jun, 24: CAIMS - PIMS Coronavirus Modelling Conference - Panel
Speaker: Penelope Morel, Adrianne Jenner, Jane Heffernan, Wei Dai, Rohit Rao
Abstract:

A panel session was heard after the morning session of the third day of this conference. The panelists were the speakers from the 4 preceeding talks.

1. The immune response to SARS-CoV-2: Friend or Foe? - Penelope Morel
2. Modelling the systemic and tissue-level immune response to SARS-CoV-2 - Adrianne Jenner
3. Models for immune system interaction and evolution - Jane Heffernan
4. A Quantitative Systems Pharmacology Model of the Immune Response to SARS-COV-2 - Wei Dai, Rohit Rao
Abstract:

Rapid development of a QSP model to support novel COVID-19 therapies. We intend to publish this model quickly to encourage community feedback. The simulated dynamics of immune response are modeled by describing viral activation of innate and adaptive immune processes involving both pro-inflammatory mediators regulating viral clearance and cell damage (e.g. neutrophils and cytotoxic lymphocytes) as well as counter-regulatory immune suppressive mediators (e.g. Treg cells and IL-10).

Jun, 24: Models for immune system interaction and evolution
Speaker: Jane Heffernan
Abstract:

We have developed mathematical models to study SARS-CoV-2 pathogen evolution probabilities, and immunization effectiveness. In this talk, I will provide an overview of our models, and will discuss some preliminary results.

Abstract:

The primary distinction between severe and mild COVID-19 infections is the immune response. Disease severity and fatality has been observed to correlate with lymphopenia (low blood lymphocyte count) and increased levels of inflammatory cytokines and IL-6 (cytokine storm), damaging dysregulated macrophage responses, and T cell exhaustion due to limited recruitment. The exact mechanism driving the dynamics that ultimately result in severe COVID-19 manifestation remain unclear. Over the past two months, we have been working on developing tissue- and systemic-level models of the immune response to SARS-CoV-2 infection with the goal of pinpointing what may be causing dysregulated immune dynamics in severe cases. At the tissue level, we been working as part of an international collaboration to build a computational framework to study SARS-CoV-2 in the tissues. This platform is based upon PhysiCell, an open-source computational cell-based software. With this model, we have been investigating how the level of pro-inflammatory cytokines influence immune cell recruitment into the infected tissue and how this correlates with tissue damage. In parallel, we have constructed a systemic, within-host delay-differential equation model that accounts for the interactions between immune cell subsets, cytokines, lung tissue, and virus to help understand differential responses in COVID-19. While this work is still ongoing, this talk will address how a variety of mathematical and computational techniques contribute to the ongoing study of SARS-CoV-2 infections, helping to increase our understanding of COVID-19 severity.

* with Sofia Alfonso (McGill University), Rosemary Aogo (University of Tennessee Health Science Center), Courtney Davis (Pepperdine University), Amber M. Smith (University of Tennessee Health Science Center), Morgan Craig (Université de Montréal, CHU Sainte-Justine Research Centre)

Jun, 24: The immune response to SARS-CoV-2: Friend or Foe?
Speaker: Penelope Morel
Abstract:

The novel SARS-CoV-2 coronavirus is responsible for worldwide pandemic that has infected over 8 million people resulting in close to 500,000 deaths. The immune response to SARS-CoV-2 involves both innate and adaptive responses and it appears that the timing and magnitude of these responses are important factors in determining the outcome of the infection. For the vast majority of those infected by SARS-CovV-2 the clinical course is mild, with a significant proportion of individuals experiencing asymptomatic infection. In mild cases, it appears that classic anti- viral immunity, manifested by early type 1 interferon production, virus-specific CD8 T cells and the generation of neutralizing antibodies, is responsible for rapid viral clearance. However, the picture is very different for the 10% of infected individuals who develop serious disease, which can lead to respiratory failure, multi-organ failure and death. This is associated with a hyperinflammatory state, with high levels of circulating cytokines, and a failure of the adaptive immune response. New data are emerging concerning the factors, both genetic and environmental, that determine the clinical outcome of disease. In this talk we will examine the host and viral factors that lead either to rapid viral clearance or to severe clinical disease. Deeper understanding of the immune response to SARS-CoV-2 will lead to the development of novel therapeutics that can be tested in a modeling framework.

Abstract:

We present an age stratified SEIR model of COVID 19 accounting for mitigated social contacts. With this model we explore a series of relaxation and return to normal scenarios, in terms of health system burden.

Abstract:

To date, intervention modelling in support of the COVID-19 public health response has focused on non-pharmaceutical interventions. With biomedical tools undergoing clinical trials, it is the moment to think ahead and assess how future interventions, based on these likely imperfect tools, could be used to control the COVID-19 epidemic and allow some de-escalation of current mitigation strategies. In this talk, we will discuss our preliminary work on antibody testing and vaccine interventions in a COVID-19 transmission model based on differential equations.

Jun, 23: Specification and the measure of maximal entropy
Speaker: Vaughn Climenhaga
Abstract:

There are various proofs that a transitive uniformly hyperbolic dynamical system has a unique measure of maximal entropy. I will outline a proof due to Bowen that uses the specification and expansivity properties, focusing on the example of shift spaces. If time permits, I will describe how Bowen's proof works for equilibrium states associated to nonzero potential functions.

Jun, 23: A branching process with contact tracing
Speaker: Martin Barlow
Abstract:

I will look at a simple theoretical model of a standard branching process with branchers removed by a contact tracing procedure. The talk will identify the parameter range in which the contact tracing is able to make the process sub- critical.

Jun, 23: Modelling the impact of asymptomatic individuals
Speaker: Cedric Chauve
Abstract:

We designed a simple SEIR-like model including asymptomatic individuals and we explore a wide grid of parameters related to asymptomatic rate and infectiousness.

Abstract:

We show how a simple deterministic epidemic model without spatial structure can reproduce the evolution of confirmed Covid-19 case numbers in diverse countries and Brazilian states through use of a time-dependent contagion factor, beta(t). One expects that this function provides a link between the growth rate and mitigation policies. The model inserts a state A (presymptomatic) between states E (exposed) and I (infected) in the usual SEIR model, as well as distinguishing between confirmed and unconfirmed infected. With transition rates fixed at literature values, we vary the four free parameters in beta(t) to obtain a good description of time series of the cumulative number of confirmed cases. We then analyze the relation between changes in the contagion factor, as inferred from the time- series analysis, and mobility indexes based on cell-phone data.

Abstract:

We investigate a SIRS epidemic model with spatial diffusion and nonlinear incidence rates. We show that for small diffusion rate of the infected class D_I, the infected population tends to be highly localized at certain points inside the domain, forming K spikes. We then study three distinct destabilization mechanisms, as well as a transition from localized spikes to plateau solutions. Two of the instabilities are due to coarsening (spike death) and self-replication (spike birth), and have well-known analogues in other reaction-diffusion systems such as the Schnakenberg model. The third transition is when a single spike becomes unstable and moves to the boundary. This happens when the diffusion of the recovered class, DR becomes sufficiently small. In all cases, the stability thresholds are computed asymptotically and are verified by numerical experiments. We also show that the spike solution can transit into a plateau-type solution when the diffusion rates of recovered and susceptible class are sufficiently small. Implications for disease spread and control through quarantine are discussed.

Abstract:

Evolutionary epidemiological models illustrate how selection might act on SARS-CoV-2. Considering the limited data, selection favors increased transmission, longer pre-symptomatic periods, fewer asymptomatic cases, and lower disease severity. Viral mutations are expected to affect combinations of these traits, however, making it challenging to predict the direction and disease impact of evolution.

Jun, 23: In-host Modelling of COVID-19 in Humans
Speaker: Esteban Abelardo Hernandez Vargas
Abstract:

COVID-19 pandemic has underlined the impact of emergent pathogens as a major threat for human health. The development of quantitative approaches to advance comprehension of the current outbreak is urgently needed to tackle this severe disease. In this work, different mathematical models are proposed to represent SARS-CoV-2 dynamics in infected patients. Considering different starting times of infection, parameters sets that represent infectivity of SARS-CoV-2 are computed and compared with other viral infections that can also cause pandemics. Based on the target cell limited model, SARS-CoV-2 infecting time between susceptible cells is much slower than those reported for Ebola virus infection (about 3 times slower) and influenza infection (60 times slower). The within-host reproductive number for SARS-CoV-2 is consistent to the values of influenza infection (1.7-5.35). The best model to fit the data was including immune cell response, which suggests a slow immune response peaking between 5 to 10 days post onset of symptoms. The model with eclipse phase, time in a latent phase before becoming productively infected cells, was not supported. Interestingly, both, the target cell model and the model with immune responses, predict that SARS-CoV-2 may replicate very slowly in the first days after infection, and it could be below detection levels during the first 4 days post infection. A quantitative comprehension of SARS-CoV-2 dynamics and the estimation of standard parameters of viral infections is the key contribution of this pioneering work. This work can serve for future evaluation of the potential drugs with different methods of action to inhibit SARS-CoV-2.

Abstract:

The disease caused by SARS-CoV-2 is a global pandemic that threatens to bring long-term changes worldwide. Approximately 80% of infected patients are asymptomatic or have mild symptoms such as fever or cough, while rest of the patients have varying degrees of severity of symptoms, with 3-4% mortality rate. Severe symptoms such as pneumonia and Acute Respiratory Distress Syndrome can be caused by tissue damage mostly due to aggravated and unresolved innate and adaptive immune response, often resulting from a cytokine storm. However, the mechanistic underpinnings of such responses remain elusive, with an incomplete understanding of how an intricate interplay among infected cells and cells of innate and adaptive immune system can lead to such diverse clinicopathological outcomes. Here, we use a dynamical systems approach to dissect the emergent nonlinear intra-host dynamics among virally infected cells, the immune response to it and the consequent immunopathology. By mechanistic analysis of cell- cell interactions, we have identified key parameters affecting the diverse clinical phenotypes associated with COVID- 19. This minimalistic yet rigorous model can explain the various phenotypes observed across the clinical spectrum of COVID-19, various co-morbidity risk factors such as age and obesity, and the effect of antiviral drugs on different phenotypes. It also reveals how a fine-tuned balance of infected cell killing and resolution of inflammation can lead to infection clearance, while disruptions can drive different severe phenotypes. These results will help further the case of rational selection of drug combinations that can effectively balance viral clearance and minimize tissue damage.

Abstract:

On March 23rd and March 30th, 2020, the Mexican Federal government implemented social distancing measures to mitigate the COVID-19 epidemic. In this work a mathematical model is used to explore atypical transmission events within the confinement period, triggered by the timing and strength of short time perturbations of social distancing. Is shown that social distancing measures were successful in achieving a significant reduction of the epidemic curve growth rate in the early weeks of the intervention. However, “flattening the curve” had an undesirable effect, since the epidemic peak was delayed too far, almost to the government preset day for lifting restrictions (June 1st, 2020). If the peak indeed occurs in late May or early June, then the events of children's day and Mother’s Day may either generate a later peak (worst case scenario), a long plateau with relatively constant but high incidence (middle case scenario) or the same peak date as in the original baseline epidemic curve, but with a post-peak interval of slower decay.

Abstract:

A SEIRS model was developed to describe the spread of COVID-19 in Mexico, assuming different quarantine scenarios as a function of the conditions of hospital shortage. The presented model takes into account the heterogeneity of the state of infection, that is, the groups of clinical variants that can occur when the disease is contracted. Finally, the model allows different policy options to be implemented in different sectors of population.

Abstract:

This is the prototype of an agent based model for a closed universe of a population experiencing a contagion-based epidemic, in which risk factors, movement, time of incubation and asymptomatic infection are all parameters. The model allows the operator to intervene at any step and change parameters, thus analytically visualizing the effect of policies like more testing, contract tracing, and shelter in place. Under current development, CovidSimMV is an ABM that supports a Multiverse of different environments, in which agents move from one to another according to ticket with stops. Each universe has its own characteristic mix of residents, transients and attached staff, and persons are able to adopt different roles and characteristics in different universes. The fundamental disease characteristics of incubation, asymptomatic infection, confirmed cases will be preserved. The Multiverse model will support a rich diversity of environments and interpersonal dynamics. These are JavaScript programs that can be run in a browser as HTML files. The code is open source, and available on github.com/ecsendmail.

Abstract:

During an epidemic, the interplay of disease and opinion dynamics can lead to outcomes that are different from those predicted based on disease dynamics alone. Opinions and the behaviors they elicit are complex, so modeling them requires a measure of abstraction and simplification. In this talk, we develop a differential equation model that couples SIR-type disease dynamics with opinion dynamics. We assume a spectrum of opinions that change based on current levels of infection as well as interactions that to some extent amplify the opinions of like-minded individuals. Susceptibility to infection is based on the level of prophylaxis (disease avoidance) that an opinion engenders. In this setting, we observe how the severity of an epidemic is influenced by the distribution of opinions at disease introduction, the relative rates of opinion and disease dynamics, and the amount of opinion amplification. Some insight is gained by considering how the effective reproduction number is influenced by the combination of opinion and disease dynamics.

Abstract:

Contact tracing is a key initiative in public health to contain Covid-19. At CarePredict, Inc., we developed a real-time digital contact tracing system that Long Term Care (LTC) facilities can use to rapidly identify and contain exposed, asymptomatic and symptomatic COVID-19 contacts. An SEIR deterministic model was developed to compare traditional and digital intervention methods for contact tracing in LTC Facilities. Data from our LTC facilities, skilled nursing homes, and nursing home data of residents affected by Covid-19, is utilized to form our parameter estimates and to inform the projections of the impact of contact tracing interventions. The model quantifies infection spread comparing across symptom tracing, manual contact tracing, PCR testing, and digital contact tracing in a nursing home setting. We computed the reproductive number per intervention type and compare parameter sensitivity to the base model to understand key components that can reduce spread.

Abstract:

We present a simulation study of the spread of an epidemic like COVID-19 with temporary immunity on finite spatial and non-spatial network models. In particular, we assume that an epidemic spreads stochastically on a scale-free network and that each infected individual in the network gains a temporary immunity after its infectious period is over. After the temporary immunity period is over, the individual becomes susceptible to the virus again. When the underlying contact network is embedded in Euclidean geometry, we model three different intervention strategies that aim to control the spread of the epidemic: social distancing, restrictions on travel, and restrictions on maximal number of social contacts per node. Our first finding is that on a finite network, a long enough average immunity period leads to extinction of the pandemic after the first peak, analogous to the concept of herd immunity''. For each model, there is a critical average immunity duration $L_c$ above which this happens. Our second finding is that all three interventions manage to flatten the first peak (the travel restrictions most efficiently), as well as decrease the critical immunity duration $L_c$, but elongate the epidemic. However, when the average immunity duration $L$ is shorter than $L_c$, the price for the flattened first peak is often a high second peak: for limiting the maximal number of contacts, the second peak can be as high as 1/3 of the first peak, and twice as high as it would be without intervention. Thirdly, interventions introduce oscillations into the system and the time to reach equilibrium is, for almost all scenarios, much longer. We conclude that network-based epidemic models can show a variety of behaviors that are not captured by the continuous compartmental models.

Abstract:

To mitigate the COVID-19 pandemic, much emphasis exists on implementing non-pharmaceutical interventions to keep the reproduction number below one. But using that objective ignores that some of these interventions, like bans of public events or lockdowns, must be transitory and as short as possible because of their significative economic and societal costs. Here we derive a simple and mathematically rigorous criterion for designing optimal transitory non- pharmaceutical interventions. We find that reducing the reproduction number below one is sufficient but not necessary. Instead, our criterion prescribes the required reduction in the reproduction number according to the maximum health services' capacity. To explore the implications of our theoretical results, we study the non- pharmaceutical interventions implemented in 16 cities during the COVID-19 pandemic. In particular, we estimate the minimal reduction of the contact rate in each city that is necessary to control the epidemic optimally. We also compare the optimal start of the intervention with the start of the actual interventions applied in each city. Our results contribute to establishing a rigorous methodology to guide the design of non-pharmaceutical intervention policies. Preprint: https://www.medrxiv.org/content/10.1101/2020.05.19.20107268v1

Abstract:

Community spread of coronavirus disease 2019 (COVID-19) continues to be high in many areas, likely due, in part, to insufficient testing and contact tracing. As regional test kit shortages are likely to continue with increased transmission, it is important that available testing capacity be used effectively. To date, testing for COVID-19 has largely been restricted to persons reporting symptoms, with no additional criteria being systematically employed to select who is tested. In situations when testing capacity is limited, we propose the use of a clinical prediction rule to allow for prioritized testing of people who are most likely to test positive for COVID-19. Using data from the University of Utah Health system, we developed a robust, deployable clinical prediction rule which incorporates data on demographics and clinical characteristics to predict which patients are most likely to test positive. We then incorporated prioritized testing into a stochastic SEIR model for COVID-19 to measure changes in disease burden compared to a model with indiscriminate testing. Our best performing clinical prediction rule achieved an AUC of 0.7. When incorporated into the SEIR model, prioritized testing resulted in a delay in the timing of the infection peak, a meaningful reduction in both the total number of infected individuals and the peak height of the infection curve, and thus a reduction in the excess demand on local hospital resources. These effects were strongest for lower values of Rt and higher proportions of infected individuals seeking testing.

Jun, 22: Spatiotemporal Transmission Dynamics of COVID-19 in Spain
Speaker: Ashok Krishnamurthy
Abstract:

Mathematical modelling of infectious diseases is an interdisciplinary area of increasing interest. Tracking and forecasting the full spatio-temporal evolution of an epidemic can help public health officials to plan their emergency response and health care. We present advanced methods of spatial data assimilation to epidemiology, in this case to the ebb and flow of COVID-19 across the landscape of Spain. Data assimilation is a general Bayesian technique for repeatedly and optimally updating an estimate of the current state of a dynamic model. We present a stochastic spatial Susceptible-Exposed-Infectious-Recovered-Dead (S-E-I-R-D) compartmental model to capture the transmission dynamics and the spatial spread of the ongoing COVID-19 outbreak in Spain. In this application the machinery of data assimilation acts to integrate incoming daily incidence data into a fully spatial population model, within a Bayesian framework for the tracking process. For the current outbreak in Spain we use registered data (CCAA-wide daily counts of total COVID-19 cases, recovered, hospitalized, and confirmed dead) from the Instituto de Salud Carlos III (ISCIII) situation reports. Our simulations show good correspondences between the stochastic model and the available sparse empirical data. A comparison between daily incidence data set and our SEIRD model coupled with Bayesian data assimilation highlights the role of a realization conditioned on all prior data and newly arrived data. In general, the SEIRD model with data assimilation gives a better fit than the model without data assimilation for the same time period. Our analyses may shed light more broadly on how the disease spreads in a large geographical area with places where no empirical data is recorded or observed. The analysis presented herein can be applied to a large class of compartmental epidemic models. It is important to remember that the model type is not particularly crucial for data assimilation, the Bayesian framework is the key. Data assimilation neither requires nor presupposes that the model of the infectious disease be in the family of S-I-R compartmental models. The projected number of newly infected and death cases up to August 1, 2020 are estimated and presented.

Abstract:

SARS-CoV-2 is a novel pathogen causes the COVID-19 pandemic. Some of the basic epidemiological parameters, such as the exponential epidemic growth rate and R0 are debated. We collected and analyzed data from China, eight European countries and the US using a variety of inference approaches. In all countries, the early epidemic grew exponentially at rates between 0.19-0.29/day (epidemic doubling times between 2.4-3.7 days). I will discuss the appropriate serial intervals to estimate the basic reproductive number R0 and argue that existing evidence suggests a highly infectious virus with an R0 likely between 4.0 and 7.1. Further, we found that similar levels of intervention efforts are needed, no matter the goal is mitigation or containment. Early, strong and comprehensive intervention efforts to achieve greater than 74-86% reduction in transmission are necessary.

Abstract:

Provincial and US state case, hospitalization, and death data can be characterized by relatively long periods of nearly constant growth/decline along with some large outbreaks. This talk will compare the spread in the different jurisdictions and how it has changed with relaxed social distancing measures.

Abstract:

Given a discrete subset V in the plane, how many points would you expect there to be in a ball of radius 100? What if the radius is 10,000? Due to the results of Fairchild and forthcoming work with Burrin, when V arises as orbits of non-uniform lattice subgroups of SL(2,R), we can understand asymptotic growth rate with error terms of the number of points in V for a broad family of sets. A crucial aspect of these arguments and similar arguments is understanding how to count pairs of saddle connections with certain properties determining the interactions between them, like having a fixed determinant or having another point in V nearby. We will spend the first 40 minutes discussing how these sets arise and counting results arise from the study of concrete translation surfaces. The following 40 minutes will be spent highlighting the proof strategy used to obtain these results, and advertising the generality and strength of this argument that arises from the computation of all higher moments of the Siegel--Veech transform over quotients of SL(2,R) by non-uniform lattices.

Abstract:

This main result of this talk is that there exists a billiard flow in a polygon that is weakly mixing with respect to Lebesgue measure on the unit tangent bundle to the billiard. This strengthens Kerckhoff, Masur and Smillie's result that there exists ergodic billiard flows in polygons. The existence of a weakly mixing billiard follows, via a Baire category argument, from showing that for any translation surface the product of the flows in almost every pair of directions is ergodic with respect to Lebesgue measure. This in turn is proven by showing that for every translation surface the flows in almost every pair of directions do not share non-trivial common eigenvalues. This talk will explain the problem, related results, and approach. The talk will not assume familiarity with translation surfaces. This is joint work with Giovanni Forni.

Abstract:

Diffusion is the enemy of life. This is because diffusion is a ubiquitous feature of molecular motion that is constantly spreading things out, destroying molecular aggregates. However, all living organisms, whether single cell or multicellular have ways to use the reality of molecular diffusion to their advantage. That is, they expend energy to concentrate molecules and then use the fact that molecules move down their concentration gradient to do useful things. In this talk, I will show some of the ways that cells use diffusion to their advantage, to signal, to form structures and aggregates, and to make measurements of length and size of populations. Among the examples I will describe are signalling by nerves, cell polarization, bacterial quorum sensing, and regulation of flagellar molecular motors. In this way, I hope to convince you that living organisms have made diffusion their friend, not their enemy.

Jun, 9: The counting formula of Eskin and McMullen
Speaker: Paul Apisa
Abstract:

Given a lattice acting on the hyperbolic plane, how many orbits of a point intersect the ball the radius of r as r gets big? Similarly, given a hyperbolic surface with a geodesic gamma, how many lifts of gamma to the hyperbolic plane intersect the ball of radius r? Using the mixing of geodesic flow on hyperbolic surfaces, Eskin and McMullen found a short beautiful argument to find the asymptotics for these counting questions (and more general ones on affine symmetric spaces). The key insight is to relate the counting problems to the equidistribution of circles under geodesic flow. In this talk I will discuss how to deduce circle equidistribution and counting problem asymptotics from mixing. The talk will involve many pictures and focus on the case of hyperbolic surfaces, however, the arguments presented will be general and their application to counting on general affine symmetric spaces will be explained at the end of the talk.

Abstract:

Furstenberg's conjecture on the dimension of the intersection of x2,x3-invariant Cantor sets can be restated as a bound on the dimension of linear slices of the product of x2,x3-Cantor sets, which is a self-affine set in the plane. I will discuss some older and newer variants of this, where the self-affine set is replaced by a self-similar set such as the Sierpinski triangle, Sierpinski carpet or (support of) a complex Bernoulli convolution. Among other things, I will show that the intersection of the Sierpinski carpet with circles has small dimension, but on the other hand the Sierpinski carpet can be covered very efficiently by linear tubes (neighborhoods of lines). The latter fact is a recent result joint with A. Pyörälä, V. Suomala and M. Wu.

Jun, 2: Bohr and Measure Recurrent Sets
Speaker: Nishant Chandgotia
Abstract:

Given a probability preserving system (X, \mu, T) and a set U of positive measure contained in X we denote by N(U,U) the set of integers n such that the measure of U intersected with T^n(U) is positive. These sets are called return-time sets and are of very special nature. For instance, Poincaré recurrence theorem tells us that the set must have bounded gaps while Sarkozy-Furstenberg theorem tells us that it must have a square. The subject of this talk is a very old question (going back to Følner-1954 if not earlier) whether they give rise to the same family of the sets as when we restrict ourselves to compact group rotations. This was answered negatively by Kříž in 1987 and recently it was proved by Griesmer that a return-time set need not contain any translate of a return-time set arising from compact group rotations. In this talk, I will try to sketch some of these proofs and give a flavour of results and questions in this direction.

May, 28: Almost-Prime Times in Horospherical Flows
Abstract:

There is a rich connection between homogeneous dynamics and number theory. Often in such applications it is desirable for dynamical results to be effective (i.e. the rate of convergence for dynamical phenomena are known). In the first part of this talk, I will provide the necessary background and relevant history to state an effective equidistribution result for horospherical flows on the space of unimodular lattices in $\mathbb{R}^n$. I will then describe an application to studying the distribution of almost-prime times (integer times having fewer than a fixed number of prime factors) in horospherical orbits and discuss connections of this work to Sarnak’s Mobius disjointness conjecture. In the second part of the talk I will describe some of the ingredients and key steps that go into proving these results.

Abstract:

Multiscale multicellular models combine representations of subcellular biological networks, cell behaviors, tissue level effects and whole body effects to describe tissue outcomes during development, homeostasis and disease. I will briefly introduce these simulation methodologies, the CompuCell3D simulation environment and their applications, then focus on a multiscale simulation of an acute primary infection of an epithelial tissue infected by a virus like SARS-CoV-2, a simplified cellular immune response and viral and immune-induced tissue damage. The model exhibits four basic parameter regimes: where the immune response fails to contain or significantly slow the spread of viral infection, where it significantly slows but fails to stop the spread of infection, where it eliminates all infected epithelial cells, but reinfection occurs from residual extracellular virus and where it clears the both infected cells and extracellular virus, leaving a substantial fraction of epithelial cells uninfected. Even this simplified model can illustrate the effects of a number of drug therapy concepts. Inhibition of viral internalization and faster immune-cell recruitment promote containment of infection. Fast viral internalization and slower immune response lead to uncontrolled spread of infection. Existing antivirals, despite blocking viral replication, show reduced clinical benefit when given later during the course of infection. Simulation of a drug which reduces the replication rate of viral RNA, shows that a low dosage that provides only a relatively limited reduction of viral RNA replication greatly decreases the total tissue damage and extracellular virus when given near the beginning of infection. However, even a high dosage that greatly reduces the rate of RNA replication rapidly loses efficacy when given later after infection. Many combinations of dosage and treatment time lead to distinct stochastic outcomes, with some replicas showing clearance or control of the virus (treatment success), while others show rapid infection of all epithelial cells (treatment failure). This switch between a regime of frequent treatment success and frequent failure occurs is quite abrupt as the time of treatment increases. The model is open-source and modular, allowing rapid development and extension of its components by groups working in parallel.

Abstract:

The Bratteli-Vershik model is a method of producing minimal actions of the integers on a Cantor set. It was given by myself, Rich Herman and Chris Skau, building on seminal ideas of Anatoly Vershik, over 30 years ago. Rather disappointingly and surprisingly, there isn't a good version for $\mathbb{Z}^2$ actions. I'll report on a new outlook on the problem and recent progress with Thierry Giordano (Ottawa) and Christian Skau (Trondheim). The new outlook focuses on the model as an answer to the question: which cohomological invariants can arise from such actions? I will not assume any familiarity with either the original model or the cohomology. The first half of the talk will be a gentle introduction to the $\mathbb{Z}$-case and the second half will deal with how to adapt the question to get an answer for $\mathbb{Z}^2$

May, 20: Binocular Rivalry; Modeling by Network Structure
Speaker: Marty Golubitsky
Abstract:

Binocular rivalry explores the question of how the brain copes with contradictory information. A subject is shown two different pictures – one to each eye. What images does the subject perceive? Results from rivalry experiments usually lead to alternation of percepts and are often surprising. Hugh Wilson proposed modeling rivalry in the brain by using structured networks of differential equations. We use Wilson networks as modeling devices and equivariant Hopf bifurcation as a tool to both post-dict and predict experimentally observed percepts. This work is joint with Casey Diekman, Zhong-Lin Lu, Tyler McMillen, Ian Stewart, Yunjiao Wang, and Yukai Zhao.

Abstract:

In this talk we will introduce Bratteli diagrams and Vershik maps. Herman-Putnam-Skau proved that for every minimal Cantor dynamical system there exists a Bratteli-Vershik model. We will discuss the proof of this theorem, some of its applications and recent developments. We will also discuss Bratteli-Vershik models for Borel dynamical systems (Bezuglyi-Dooley-Kwiatkowski). Finally, we will briefly talk about connections between Bratteli diagrams and flows on translation surfaces (Lindsey-Treviño).

Abstract:

TBA

Abstract:

The COVID-19 global pandemic has led to unprecedented public interest in mathematical modelling as a tool to understand the dynamics of disease spread and predict the impact of public health interventions. In this pair of talks, we will describe how mathematical models are being used, with particular reference to the British Columbia epidemic.

In the first talk, Prof. Caroline Colijn (Dept. of Mathematics, Simon Fraser University) will outline the key features of the British Columbia data and focus on how modelling has allowed us to estimate the effectiveness of the provincial response. In the second talk, Prof. Daniel Coombs (Dept. of Mathematics and Inst. of Applied Mathematics, University of British Columbia) will describe forward-looking modelling approaches that can provide some guidance as the province moves towards partial de-escalation of measures. Each talk will be 30 mins in length and followed by a question and discussion period.

For more details on the group's work and to contact the team, please visit https://bccovid-19group.ca/

May, 14: Veech's Criterion for a process to be prime
Speaker: Jon Chaika
Abstract:

This talk will present Veech's criterion for an ergodic probability measure preserving system to be prime. It will define factors of measure preserving systems, prime and self-joinings and provide examples. It uses disintegration of measures, the ergodic decomposition and Haar's Theorem. It will state these results and have examples of disintegration of measures and the ergodic decomposition, but wont discuss their proofs.

May, 7: Factors of Gibbs measures on subshifts (2 of 2)
Speaker: Sophie MacDonald
Abstract:

Classical results of Dobrushin and Lanford-Ruelle establish, in rough terms, that for a local energy function on a subshift without too much long-range order, the translation-invariant Gibbs measures are precisely the equilibrium measures. There are multiple definitions of a Gibbs measure in the literature, which do not always coincide. We will discuss two of these definitions, one introduced by Capocaccia and the other used by Dobrushin-Lanford-Ruelle, and outline a proof (available at arxiv.org/abs/2003.05532) that they are equivalent.

We will also discuss forthcoming work, in which we show that Gibbsianness is preserved by pushforward through a certain kind of almost invertible factor map. As an application in one dimension, we show that for a sufficiently regular potential, any equilibrium measure on an irreducible sofic shift is Gibbs. As far as we know, this is the first reasonably general result of the Lanford-Ruelle type for a class of subshifts without the topological Markov property.

Joint work with Luísa Borsato, with extensive advice from Brian Marcus and Tom Meyerovitch.

This lecture was given in two parts. The video on this page was given as a follow up to a pre-recorded video.

May, 7: Factors of Gibbs measures on subshifts (1 of 2)
Speaker: Sophie MacDonald
Abstract:

Classical results of Dobrushin and Lanford-Ruelle establish, in rough terms, that for a local energy function on a subshift without too much long-range order, the translation-invariant Gibbs measures are precisely the equilibrium measures. There are multiple definitions of a Gibbs measure in the literature, which do not always coincide. We will discuss two of these definitions, one introduced by Capocaccia and the other used by Dobrushin-Lanford-Ruelle, and outline a proof (available at [arxiv.org/abs/2003.05532]) that they are equivalent.

We will also discuss forthcoming work, in which we show that Gibbsianness is preserved by pushforward through a certain kind of almost invertible factor map. As an application in one dimension, we show that for a sufficiently regular potential, any equilibrium measure on an irreducible sofic shift is Gibbs. As far as we know, this is the first reasonably general result of the Lanford-Ruelle type for a class of subshifts without the topological Markov property.

Joint work with Luísa Borsato, with extensive advice from Brian Marcus and Tom Meyerovitch.

This lecture was given in two parts. The video on this page was distributed as a pre-recorded session ahead of a second live lecture.

Abstract:

Until very recently most cancer biologists operated with the assumption that the most common route to metastasis involved cells of the primary tumor transforming to a motile single-cell phenotype via complete EMT (the epithelial-mesenchymal transition). This change allowed them to migrate individually to distant organs, eventually leading to clonal growths in other locations. But, a new more nuanced picture has been emerging, based on advanced measurements and on computational systems biology approaches. It has now been realized that cells can readily adopt states with hybrid properties, use these properties to move collectively and cooperatively, and reach distant niches as highly metastatic clusters. This talk will focus on the accumulating evidence for this revised perspective, the role of biological physics theory in instigating this whole line of investigation, and on open questions currently under investigation.

Abstract:

TBA

Apr, 30: Quantum Unique Ergodicity
Speaker: Lior Silberman
Abstract:

TBA

Apr, 28: An introduction to naive entropy
Speaker: Dominik Kwietniak
Abstract:

There are simple formulas defining "naive entropy" for continuous/measure preserving actions of a countable group G on a compact metric/probability space. It turns out that if G is amenable, then this naive entropy coincides with topological/Kolmogoro-Sinai entropy of the action, while for non-amenable groups both naive entropies take only two values: 0 or infinity. During my talk, I will try to sketch the proofs of these facts. I will follow: T. Downarowicz, B. Frej, P.-P. Romagnoli, Shearer's inequality and infimum rule for Shannon entropy and topological entropy. Dynamics and numbers, 63-75, Contemp. Math., 669, Amer. Math. Soc., Providence, RI, 2016. MR3546663 and P. Burton, Naive entropy of dynamical systems. Israel J. Math. 219 (2017), no. 2, 637-659. MR3649602.

Abstract:

The horospherical flow on finite-volume hyperbolic surfaces is well-understood. In particular, effective equidistribution of non-closed horospherical orbits is known. New difficulties arise when studying the infinite-volume setting. We will discuss the setting in finite- and infinite-volume manifolds, and the measures that play a crucial role in the latter. Joint work with Jacqueline Warren.

Abstract:

In this talk, we will use compartmental models to examine the power of age-targeted mitigation strategies for COVID-19. We will present evidence that, in the context of strategies which end with herd immunity, age-heterogeneous strategies are better for reducing direct mortalities across a wide parameter regime. And using a model which integrates empirical data on age-contact patterns in the United States and recent estimates of COVID-19 mortality and hospitalization rates, we will present evidence that age-targeted approaches have the potential to greatly reduce mortalities and ICU utilization for COVID-19, among strategies which ultimately end the epidemic by reaching herd immunity. This is joint work with Maria Chikina.

Abstract:

Caroline Series' The modular surface and continued fractions

Apr, 14: Boshernitzan's criterion for unique ergodicity
Speaker: Jon Chiaka
Abstract:

TBA

Apr, 8: Multiple fission cycles in Chlamydomonas
Speaker: John Tyson
Abstract:

In this talk I will present a "dynamical paradigm" for modeling networks of interacting genes and proteins that regulate every aspect of cell physiology. The paradigm is based on dynamical systems theory of nonlinear ODEs, especially one- and two-parameter bifurcation diagrams. I will show how we have used this paradigm to unravel the mechanisms controlling "multiple fission" cycles in the photosynthetic green alga Chlamydomonas. While most eukaryotic cells maintain a characteristic size by executing binary division after each mass doubling, Chlamydomonas cells can grow more than eight-fold during daytime before undergoing rapid cycles of DNA replication, mitosis and cell division at night, which produce up to 16 daughter cells. We propose that this unusual strategy of growth and division (which is clearly advantageous for a photosynthetic organism) can be governed by a size-dependent bistable switch that turns on and off a limit cycle oscillator that drives cells through rapid cycles of DNA synthesis and mitosis. We show that this simple ‘sizer-oscillator’ arrangement reproduces the experimentally observed features of multiple-fission cycles and the response of Chlamydomonas cells to different light-dark regimes. Our model makes unexpected predictions about the size-dependence of the time of onset of cell-cycle oscillations after cells are transferred from light to dark conditions, and these predictions are confirmed by single-cell experiments.

Collaborators: Stefan Heldt and Bela Novak (Oxford Univ) on the modeling; Fred Cross (Rockefeller Univ) on the experiments.

Mar, 25: In Progress COVID-19 modelling
Speaker: Alastair Jamieson-Lane
Abstract:

A variety of strategies and approaches have been proposed, and implemented by governments, for COVID mitigation. In this presentation, I introduce some of these, briefly discuss some of the resulting difficulties - in particular in the context of the northern Netherlands, where I have been working most recently. We then take a preliminary look at the possibility of targeted quarantine' . Many questions, both mathematical, clinical, logistical and ethical remain to be answered, and as such, this presentation will be closer to a discussion session than the usual Mathbio Works in progress seminars. All feedback appreciated and welcome

Abstract:

Dynamical systems concepts have mostly been developed to understand the behaviour of autonomous, i.e. input-free, nonlinear systems. Even in this case, it is well recognized that such systems can display a wide range of dynamical behaviours. Understanding how non-autonomous systems behave is an additional mathematical challenge that gives insight into how complex systems can perform computational activities in response to inputs. In this talk I will discuss ways that the dynamics of network attractors can be used to describe and predict not only the how the systems perform computations, but also how they may make errors during the computations.

### Speaker Biography

Peter Ashwin is Professor of Mathematics at the University of Exeter (UK) since 2007. His main interests are in nonlinear dynamical systems and applications: bifurcation theory and dynamical systems, especially synchronization problems, symmetric chaotic dynamics, spatially extended systems and nonautonomous systems. Applications of dynamical systems include climate (bifurcations, tipping points), fluids (bifurcations and mixing), laser systems (synchronization), neural systems (computational properties), materials and electronic systems (digital signal processing) and biophysical modelling (cell biology).

Abstract:

A large part of stochastic portfolio theory, as initiated by Robert Fernholz in the 1990s, is concerned with construction of practical equity portfolios that can beat the stock market index by active rule-based trading. The truly remarkable part of the theory is that it requires no probabilistic modeling on the future behavior of stock prices. There is a Monge-Kantorovich optimal transport problem that naturally arises in the construction of such portfolios. This transport problem is a multiplicative analog of the well-studied quadratic Kantorovich- Wasserstein transport with equally striking properties. We will see aspects of this transport problem from theoretical uses such as defining gradient flows in a non-metric setting to practical uses such as in determining the right frequency of trading. Interesting probability theory comes in as we consider entropic relaxation of this problem giving rise to multiplicative Schrodinger bridges.

Abstract:

Let $L/K$ be a Galois extension of number fields with Galois group $G$, and let $C⊂G$ be a conjugacy class. Attached to each unramified prime ideal p in OK is the Artin symbol $\sigma p$, a conjugacy class in $G$. In 1922 Chebotarev established what is referred to his density theorem (CDT). It asserts that the number $\pi C(x)$ of such primes with $\sigma p=C$ and norm $Np≤x$ is asymptotically $\left|C\right|\left|G\right|\mathrm{Li} (x)$ as $x\rightarrow\infty$ where $\mathrm{Li} (x)$ is the usual logarithmic integral. As such, CDT is a generalisation of both the prime number theorem and Dirichlet's theorem on primes in arithmetic progressions. In light of Linnik's result on the least prime in an arithmetic progression, one may ask for a bound for the least prime ideal whose Artin symbol equals C. In 1977 Lagarias and Odlyzko proved explicit versions of CDT and in 1979 Lagarias, Montgomery and Odlyzko gave bounds for the least prime ideal in the CDT. Since 2012 several unconditional explicit results of these theorems have appeared with contributions by Zaman, Zaman and Thorner, Ahn and Kwon, and Winckler. I will present several recent results we have proven with Das, Ng, and Wong.

Jan, 20: Regular Representations of Groups
Speaker: Joy Morris
Abstract:

A natural way to understand groups visually is by examining objects on which the group has a natural permutation action. In fact, this is often the way we first show groups to undergraduate students: introducing the cyclic and dihedral groups as the groups of symmetries of polygons, logos, or designs. For example, the dihedral group $D_8$ of order 8 is the group of symmetries of a square. However, there are some challenges with this particular example of visualisation, as many people struggle to understand how reflections and rotations interact as symmetries of a square.

Every group G admits a natural permutation action on the set of elements of $G$ (in fact, two): acting by right- (or left-) multiplication. (The action by right-multiplication is given by $\left{t_g : g \in G\right}, where$t_g(h) = hg$for every$h \in G$.) This action is called the "right- (or left-) regular representation" of$G$. It is straightforward to observe that this action is regular (that is, for any two elements of the underlying set, there is precisely one group element that maps one to the other). If it is possible to find an object that can be labelled with the elements of$G$in such a way that the symmetries of the object are precisely the right-regular representation of$G$, then we call this object a "regular representation" of$G$. A Cayley (di)graph$Cay(G,S)$on the group$G$(with connection set$S$, a subset of$G$) is defined to have the set$G$as its vertices, with an arc from$g$to$sg$for every$s$in$S$. It is straightforward to see that the right-regular representation of$G$is a subset of the automorphism group of this (di)graph. However, it is often not at all obvious whether or not$Cay(G,S)$admits additional automorphisms. For example,$Cay(Z_4, {1,3})$is a square, and therefore has$D_8$rather than$Z_4$as its full automorphism group, so is not a regular representation of$Z_4\$. Nonetheless, since a regular representation that is a (di)graph must always be a Cayley (di)graph, we study these to determine when regular representations of groups are possible.

I will present results about which groups admit graphs, digraphs, and oriented graphs as regular representations, and how common it is for an arbitrary Cayley digraph to be a regular representation.