34th Canadian Conference on Computational Geometry
2022-08-25 - 2022-08-27 | Ryerson University, Toronto, Ontario, Canada
The Canadian Conference on Computational Geometry (CCCG) is a forum to disseminate and discuss theoretical and applied results in discrete and computational geometry.
Computational geometry is concerned with the design of efficient algorithms, the development of software, and the study of the mathematical foundations of computational problems whose formulation involves geometric constraints. The field is motivated by problems from a broad range of application areas, as diverse as computer graphics and animation, computer vision, computer-aided design and manufacturing, geographic information systems, pattern recognition, wireless communications, robotics, protein folding, urban planning, graph drawing, or statistical analysis. The 34th Canadian Conference on Computational Geometry will take place in August 2022 in Toronto, ON.

East Coast Combinatorics Conference
2022-08-17 - 2022-08-18 | University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
The East Coast Combinatorics Conference is an annual conference designed to support and bring together researchers in mathematics and computer science interested in all aspects of combinatorics. A unique feature is the workshop-like atmosphere which encourages active collaboration and participation of faculty and students while highlighting major theoretical advances and applications in the area. In addition to plenary talks, the conference features contributed talks presented by faculty, students, and post-docs.

Intersection of Microlocal Analysis, Harmonic Analysis, and Inverse Problems: A conference in honor of Allan Greenleaf
2022-08-15 - 2022-08-17 | University of Rochester, 500 Joseph C. Wilson Blvd, Rochester, NY, United States
The objective of the conference is to bring together an international group of experts in three areas: microlocal analysis, inverse problems and harmonic analysis. There will be 19 internationally recognized researchers in those subjects, each invited to give a lecture. There has recently been great progress in all these areas, with mutual benefits, and no end in sight. With this conference we hope to foster interaction and collaboration among speakers and other participants from the three different areas. Furthermore, the conference will take the opportunity to honor the research achievements of Professor Allan Greenleaf, who has made fundamental contributions to many of the topics covered by this conference.

Symmetry, Invariants, and their Applications: A Celebration of Peter Olver’s 70th Birthday
2022-08-03 - 2022-08-05 | Halifax, Halifax, Nova Scotia, Canada
This is a proposal for a workshop on symmetry, invariants, and their applications in celebration of Peter Olver’s 70th birthday. Transformation and groups are an omnipresent concept in nature, science, and art. Many biological, chemical, physical, or man-made structures exhibit symmetries as a fundamental design principle or as an essential aspect of their functioning. Symmetry groups also occur in a wide variety of modern applications including computer vision, archaeology, numerical integration, and neural networks, differential equations, geometry, and applied mathematics.
During his prolific career, Peter J. Olver played an important role in the development of symmetry group methods to differential equations, geometry, and applied mathematics.The purpose of the workshop is to bring together leading experts, promising younger researchers, and graduate students from around the world to assess the rapid advances occurring in the field of symmetries and invariants, and to evaluate the most promising directions of future developments.

AARMS Geophysical Inverse Problems Discussion
2022-07-29 13:30 - 14:30 UTC | Online via Zoom
Lelièvre et al., 2012, Joint inversion of seismic traveltimes and gravity data on unstructured grids with application to mineral exploration.
https://library.seg.org/doi/10.1190/geo2011-0154.1

If you are unable to access the paper through that link, please email the organizer (and co-author on the paper) for a copy (plelievre@mta.ca).
This paper looks at various different methods to enforce the similarity of the different models in a joint inversion. This paper will help us discuss previous themes in relation to joint inversion, including the deterioration of numerical behavior for particular objective functions, constructing piecewise-constant models, and determining the value of the regularization parameter(s).

Friday, July 29, 2022 @ 1:30 pm – 2:30 pm (Atlantic time)

Connection details will be published on the organizer’s website:
https://www.esd.mun.ca/~peter/AARMS-CRG.html

AARMS Geophysical Inverse Problems Discussion
2022-07-15 13:30 - 14:30 UTC | Zoom seminar
Friday, July 15, 2022 @ 1:30 pm – 2:30 pm (Atlantic time)
Bijani et al., 2017, Physical-property-, lithology- and surface-geometry-based joint inversion using Pareto Multi-Objective Global Optimization.
If you are unable to access the paper through that link, please email the organizer (and co-author on the paper) for a copy (plelievre@mta.ca).
This paper introduces the concept of multi-objective optimization and Pareto-optimality. In this work, instead of attempting to select a single value for the regularization parameter, the methods sample the entire Pareto-curve (Tikhonov curve), or for more than two objective functions the Pareto-(hyper)surface. The challenge is then deciding how to visualize and otherwise explore all the possible models provided, extract useful information from them, and make reasonable interpretations.
Connection details will be available on the organizer’s website.

Canadian Undergraduate Mathematics Conference / Congrès canadien des étudiant(e)s en mathématiques
2022-07-13 - 2022-07-17 | Université Laval, 2325 Rue de l'Université, Québec, Québec, G1V 0A6, Canada
The Canadian Undergraduate Mathematics Conference (CUMC) is a national conference organized each summer by undergraduate students for undergraduate students at different institutions across Canada.
The CUMC is an opportunity for students to explore mathematics outside their usual surroundings and spark their interest in areas they have not yet been exposed to. Indeed, the core of the gathering consists of a series of talks given by participants. The conference therefore provides a unique chance for students to present what they find most fascinating and exciting, as well as to practice their expository skills in an inclusive and noncompetitive environment. As a national conference, the CUMC is a bilingual event. Moreover, the event seeks to promote diversity within the field of mathematics itself, by offering keynote lectures in both pure and applied fields.
The CUMC is primarily organised by a local organising committee at the host institution, under the aegis of Studc.

Computational Aspects in Finance and Actuarial Sciences
2022-07-08 - 2022-07-09 | University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
The AARMS CRG Conference on Computational Aspects in Finance and Actuarial Sciences will be held July 8-9 in PEI, Canada. This conference is mainly hosted by the Atlantic Association for Research in Mathematical Sciences (AARMS) collaborative research group (CRG) and the School of Mathematical and Computational Sciences (SMCS) at University of Prince Edward Island (UPEI), Canada, and is a unique venue that brings together leaders in finance, and actuarial sciences, across disciplines, and across borders, tackling very important and timely topics in finance and actuarial sciences. Our intention for this conference is to have a broad scope in terms of applications in Finance and Actuarial Sciences but we would like to put emphasis on numerical and computational issues (including trendy topics such as machine learning algorithms in finance and insurance, but also more traditional methods such as numerical solutions for PDEs, Monte Carlo simulations, etc). The conference will include a dynamic program with high quality speakers focusing on innovative research, policy discussions, and business challenges and successes.
ZOOM link: https://us06web.zoom.us/u/kUOl82t1s

Junior Math and Computer Science Camp
2022-07-04 - 2022-07-08 | Acadia University, Wolfville, Nova Scotia, Canada
This week-long day camp is an opportunity for students entering grades 5 or 6 in the Annapolis Valley to participate in fun and enriching science-based activities with Acadia faculty and students to develop their curiosity and enjoyment of math and computer science. It represents an important piece of a multi-year plan to develop the science skills of young students in the Annapolis Valley by bringing young students into the Acadia University outreach program. This will begin the process of positively engaging students with math and computer science at a critical time in their education. Bursaries are provided for those who qualify for financial assistance.

AARMS Geophysical Inverse Problems Discussion
2022-06-24 13:30 - 14:30 UTC | Zoom seminar
Farquharson & Oldenburg, 2004, A comparison of automatic techniques for estimating the regularization parameter in non-linear inverse problems.
Also available here:

https://gif.eos.ubc.ca/sites/default/files/Farquharson_regparam_04.pdf

This paper compares some common approaches for choosing the value of the regularization parameter in underdetermined, minimum-structure-type inverse problems. It can provide an overview for us before looking at more recent ideas.
Friday, June 24, 2022 @ 1:30 pm – 2:30 pm (Atlantic time)

Stinson66 - New Advances in Designs, Codes and Cryptography
2022-06-13 - 2022-06-17 | Fields Institute, 222 College St., Toronto, Ontario, M5T 3J1, Canada
This conference will celebrate Doug Stinson’s 66th birthday and highlight his contributions to the fields of designs, codes, cryptography, and their connections. The goal is to explore recent developments, open problems and conjectures in combinatorial design theory along with applications to related areas including codes, cryptography, networks, and algorithms. We intend to bring together leading researchers from around the world, along with graduate students, postdocs and other early-career researchers. The conference will consist of invited talks only and will provide ample opportunity for discussion and collaboration among the participants.

AARMS Geophysical Inverse Problems Discussion
2022-06-10 01:30 - 14:30 UTC | Zoom seminar
Gündoğdu & Candansayar, 2018, Three-dimensional regularized inversion of DC resistivity data with different stabilizing functionals.
Also available on the author’s ResearchGate page:

https://www.researchgate.net/publication/326068036_Three-dimensional_regularized_inversion_of_DC_resistivity_data_with_different_stabilizing_functionals

This paper compares several regularization functionals that have appeared in geophysical inversion literature. It can provide an overview for us before perhaps looking at some others in more detail, if needed.

Friday, June 10, 2022 @ 1:30 pm – 2:30 pm (Atlantic time)

Applied and geometric analysis--A Session at the CMS Summer meeting
2022-06-06 | Memorial University (St. John’s Campus), St. John's, Newfoundland and Labrador, Canada
This proposed scientific session at CMS Summer Meeting at Memorial University, June 3-6, 2022, will bring together several researchers to present their recent results and discuss further developments of applied geometric analysis.

Session on Design Theory and Graph Decompositions at the 2022 Summer Meeting of the Canadian Mathematical Society
2022-06-03 - 2022-06-06 | Memorial University (St. John’s Campus), St. John's, Newfoundland and Labrador, Canada
Combinatorial design theory has a history dating back to the 18th century when Leonhard Euler pondered the existence of orthogonal pairs of Latin squares. This session will showcase recent results in topics such as classical designs, cycle systems, graph decompositions, Latin squares and other aspects of design theory by bringing together leading and emerging researchers in the field to share their recent results, techniques, and applications.

Public Lecture: Dr. Ivan Shestakov
2022-06-01 19:00 - 20:00 UTC | Memorial University (St. John’s Campus), St. John's, Newfoundland and Labrador, Canada
Dr. Ivan Shestakov will be visiting St. John’s, NL, from May 29 to June 3, as a guest of the Atlantic Algebra Centre in the department of Mathematics and Statistics at Memorial University and as an AARMS Distinguished Lecturer. While there, Dr. Shestakov will give a plenary talk to the International Workshop “Groups, Rings, Lie and Hopf Algebras IV”. The title of the talk is “Non-matrix Varieties and Coordinatization Theorems”. Dr. Shestakov will also deliver a public lecture as described below.
Tame and Wild Automorphisms of Free Algebras
The notion of automorphism captures the idea of symmetry in mathematics. More precisely, an automorphism of an object is an invertible transformation that preserves the object’s structure. Many important objects in algebra possess natural examples of such transformations, which are referred to as elementary automorphisms. For such an object, an automorphism is called tame if it can be represented as a composition of elementary automorphisms, otherwise it is called wild.
It is known that the automorphisms of polynomial algebra and of free associative algebra are tame in case of two generators while in case of three generators there exist wild automorphisms.
In our talk, we will discuss known results and open problems on tame and wild automorphisms in various classes of algebras.
Speaker Bio
Ivan Shestakov was born on August 13, 1947, in Zaval’, Irkutsk region, Russia. After graduating from the Physical-Mathematical School in Novosibirsk, he entered Novosibirsk University in 1965. There he obtained his first results in algebra, under the guidance of professors K. Zhevlakov and A. Shirshov. His Masters thesis “On a Class of Non-commutative Jordan Rings” was awarded the Medal of the Academy of Sciences of USSR for students. In 1970 Shestakov graduated from Novosibirsk University and entered as a researcher the Sobolev Institute of Mathematics. In 1973 he received his Ph.D. from Novosibirsk University, and in 1978 he earned the Doctor of Sciences from the Sobolev Institute of Mathematics for the work “Free Alternative Algebras”. In 1974 Shestakov became a professor of the Novosibirsk State University. Since 1999 he has held a position of Full Professor at the University of Sao Paulo. In 2007 he was awarded, jointly with U. Umirbaev, the E. H. Moore Research Article Prize of the AMS for the solution of the Nagata problem on polynomial automorphisms. In 2009 Shestakov was elected to the Brazilian Academy of Sciences, and in 2010 he was awarded the “Ordem de Merito Scientifico” by the president of Brazil. In 2016 Shestakov was elected a Fellow of the AMS, and in 2017 he was awarded the Gold Medal “For Great Contributions to Mathematics” by the Sobolev Institute of Mathematics (Novosibirsk, Russia). Shestakov’s interests lie in the Ring Theory and Combinatorial Algebra. He has focused on the structure and representations of non-associative algebras and superalgebras, PIalgebras, free algebras and their automorphisms.
Connection Details
To attend in person:
Room EN-2006, S. J. Carew Building
Memorial University
240 Prince Phillip Drive
St. John’s, NL
To attend virtually:
Connection details will be published at:
https://www.mun.ca/aac/

Mathematical foundations of scientific machine learning
2022-06-01 - 2022-06-03 | Memorial University (St. John’s Campus), St. John's, Newfoundland and Labrador, Canada
Workshop hosted by the AARMS CRG in Scientific Machine Learning. Remote participation via Webex possible. Full program and connection details: Program

Groups, Rings, Lie and Hopf Algebras IV
2022-05-30 - 2022-06-02 | Memorial University (St. John’s Campus), St. John's, Newfoundland and Labrador, Canada
The aim of this workshop is to discuss the current state of research in several interrelated areas of algebra. The first three workshops with the same title were held on the St. John’s campus of Memorial University (MUN) in 2001 and at the Bonne Bay Marine Station of MUN in Gros Morne National Park in 2007 and 2012. The current workshop is organized by the Atlantic Algebra Centre (AAC) of MUN in the framework of the collaborative research group “Groups, Rings, Lie and Hopf Algebras” of the Atlantic Association for Research in the Mathematical Sciences (AARMS). It will immediately precede the summer meeting of Canadian Mathematical Society, which will be held in St. Johns from June 3 to June 6.

Calculus Instruction in Atlantic Canada Conference 2022
2022-05-28 | Online via Zoom
This is a one-day online workshop is an opportunity for high school and university calculus instructors from across Atlantic Canada to come together and engage in discussions regarding calculus instruction.
The theme for 2022 is “Adapting Calculus Instruction in a Changing Educational Climate”
We will have speakers in the morning and in the afternoon there will be a workshop and discussion group based on the theme of the conference.
An optional one day workshop regarding engaging students in mathematical reserach in the high school classroom will take place the day after the teaching conference.

AARMS Geophysical Inverse Problems Discussion
2022-05-27 13:30 - 14:30 UTC | Online via Zoom
Farquharson, 2008, Constructing piecewise-constant models in multidimensional minimum-structure inversions.
Also available on the author’s webpage: https://www.esd.mun.ca/~farq/special.html
Considering the discussion at our previous meeting, it seems natural to next look at methods for recovering sharp/blocky/compact features. This one is a relatively short paper, going back to a time when most inversion work was on rectilinear meshes, and it would be sensible to return to these ideas now that unstructured meshes are seeing more use.

Combinatorial Algebra meets Algebraic Combinatorics 2023
2022-05-26 08:00 - 17:00 UTC | University of Waterloo, 200 University Ave W, Waterloo, Ontario, Canada
Combinatorial algebra and algebraic combinatorics are two highly
active areas of research. Their importance is felt throughout
theoretical and applied mathematics, including algebraic geometry,
representation theory, commutative algebra, and mathematical physics;
they have found numerous practical applications in diverse fields.
The connections between these overlapping subjects are central to
the CAAC workshops’ traditional thematic goals. They were
emphasized in a series of expository lectures which were given by
Tony Geramita and Franc{c}ois Bergeron in January 2004 at
Queen’s University. Through these lectures, it became evident
that interesting special cases of Macaulay’s inverse systems, a
fundamental concept in commutative algebra, are essentially the
coinvariant spaces which arise in algebraic combinatorics. These
connections led to collaborative interdisciplinary research among
two historically disjoint communities of scholars.
The CAAC meeting has been held annually since 2004. It
focuses on the continually evolving interactions between combinatorial
algebra and algebraic combinatorics.

Atlantic General Relativity Meeting 2022
2022-05-16 - 2022-05-19 | Online via Zoom
This series of annual meetings focusses on recent advances in all aspects of classical and quantum gravity. Topics include mathematical general relativity, relativistic astrophysics, gravitational waves, cosmology, gravitational aspects of string theory, loop quantum gravity, and numerical relativity. There is particular focus on the development of graduate students and postdoctoral fellows. As in previous years, there is a two day workshop during which three invited experts (from outside the Atlantic region) give introductory lectures aimed on current topics of high interest. This is followed by two days of contributed research talks, with prizes given to the best student and postdoctoral fellows. While originally aimed to foster collaboration between research groups in Atlantic Canada, in recent years, the conference has attracted participants from both the rest of Canada and abroad.

AARMS Geophysical Inverse Problems Discussion Series
2022-05-13 13:30 - 14:30 (America/Halifax) | Zoom seminar
Zhang et al., 2022, Geophysical inversions on unstructured meshes using non-gradient based regularization
The paper above, the main one we will discuss, seeks to improve upon the method in the paper below, which increases some computational demands. We’d like to better understand how well the paper above improves upon: Lelievre et al., 2013, Gradient and smoothness regularization operators for geophysical inversion on unstructured meshes.

CMS-UPEI-AARMS Regional Math Camp
2022-05-06 - 2022-05-08 | University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
The School of Mathematical and Computational Science (SMCS) is once again organizing the UPEI-CMS-AARMS Regional Math Camp, to be held at UPEI between May 6 – May 8, 2022. We anticipate hosting some of the most talented grade 10 and grade 11 math students from across the Island. This year, we expect to invite 25-30 students. We offer students an opportunity to participate in challenging, intellectual activities with their peers, guided by the UPEI SMCS faculty members. The students will arrive on the UPEI campus by 9:00 am on Friday (May 6), spend 2 nights in residence, and depart at noon on Sunday (May 8). With the help of several undergraduate math majors, faculty members will conduct several educational, problem-solving and career sessions during the daytime, and recreational sessions during the evenings. The students will be chaperoned at all times
throughout the weekend.

Atlantic Graph Theory Seminar: Aysel Erey (Gebze Technical University, Turkey)
2022-04-13 15:30 - 16:30 UTC | Zoom seminar
Graph polynomials

In this talk, I will discuss various aspects of several graph polynomials such as the location of their roots, their combinatorial properties and extremal questions.

Join Zoom Meeting: link

AARMS Scientific Machine Learning Seminar: Michael W. Dunham (Department of Earth Sciences, Memorial University)
2022-04-12 11:00 - 12:00 UTC | WebEx seminar
Semisupervised machine learning algorithms and their application to geoscience classification problems

In recent years, many disciplines have been challenged with trying to efficiently extract meaning, or value, out of large datasets. Technological advances have improved data storage capabilities as well as how data can be obtained (e.g., real-time data). Manually interpreting data that are exponentially growing in volume has obvious management and analysis challenges. Machine learning is a solution to these challenges. Machine learning algorithms teach computers to recognize patterns in data and assign repetitive patterns to similar categories. This process automates pattern recognition of data and allows meaningful information to be extracted in an efficient manner.

For many machine learning problems, there are sufficient data to train a wide range of algorithms. Some applications, such as image classification and speech recognition, have large training datasets readily available. However, in several geoscience-related problems, labeled data are generally obtained by sampling the earth in some manner (e.g., drilling wells, field sampling, etc.), which is not trivial due to cost and logistical factors. As such, many earth science-related machine learning problems have limited training data. Supervised machine learning algorithms are prone to overfitting in scarce training data situations, but semisupervised approaches are designed for these problems because the unlabelled data are also used to inform the learning process.

Three geoscience applications inherently challenged with limited training data are well log classification, seismic classification, and bedrock lithology mapping. I apply various semisupervised algorithms to these three geoscience problems and determine if semisupervised algorithms can perform better than supervised methods and under what conditions, if applicable. The semisupervised methods I consider are self-training, label propagation, and semisupervised Gaussian mixture models. I consider several supervised methods in my work, but the most prevalent are gradient boosting decision tree methods (e.g., XGBoost, LightGBM). The results show that semisupervised methods can outperform their supervised counterparts for each of the geoscience applications, but there are situations where this is not always the case. Nonetheless, semisupervised methods are rarely considered for many geoscience disciplines, which is supported by the lack of published examples in the literature. The outcomes of this work help fill this gap, but they also help raise the awareness of semisupervised methods.

Webex link:

https://mun.webex.com/mun/j.php?MTID=mf0e24b554219c531763a22ffce2e82c9

Atlantic Graph Theory Seminar: John Engbers (Marquette University)
2022-04-06 15:30 - 16:30 UTC | Zoom seminar
Extremal questions for vertex colorings of graphs

For graphs $G$ and $H$, an $H$-coloring of $G$ is a map from the vertices of $G$ to the vertices of $H$ so that an edge in $G$ is mapped to an edge in $H$. The graph $H$ can be thought of as the allowable coloring scheme: its vertices are the colors used and its edges indicating colors that can appear on the endpoints of an edge in $G$. When the graph $H$ is the complete graph $K_q$, an $H$-coloring corresponds to a proper vertex coloring of $G$ with $q$ colors; when $H$ is an edge with one looped endvertex, an $H$-coloring corresponds to an independent set in $G$.After familiarizing ourselves with the notion of an $H$-coloring, we will consider the following extremal graph theory question: given a family of graphs and an $H$, which graph in the family has the most number of $H$-colorings, and which has the least number of $H$-colorings? We will discuss some things that are known (and not known!) in a variety of families, including trees and graphs with a fixed minimum degree.

Join Zoom Meeting: link

AARMS Scientific Machine Learning Seminar: Geoffrey McGregor (University of Northern British Columbia)
2022-04-05 11:30 - 12:30 UTC | WebEx seminar
Conservative Hamiltonian Monte Carlo

Markov Chain Monte Carlo (MCMC) methods enable us to extract meaningful statistics from complex distributions which frequently appear in parameter estimation, Bayesian statistics, statistical mechanics and machine learning. Similar to how flipping a coin, or rolling a dice, allows us to sample from the corresponding distributions underlying these processes, MCMC methods enable us to sample from more complex distributions. The sample statistics of the sequence generated by MCMC will converge to those of the target distribution, or “stationary distribution” provided certain acceptance and rejection criteria are satisfied. However, as the dimensionality of the stationary distribution increases, the acceptance rate of traditional MCMC methods inevitably diminishes and their convergence slows down substantially. This has led to recent developments in computational techniques, such as Hamiltonian Monte Carlo (HMC) to improve the performance in convergence and acceptance rate. Specifically, HMC proposes samples for acceptance or rejection by solving a Hamiltonian system of differential equations using volume preserving numerical methods.

In this talk, we introduce the Conservative Hamiltonian Monte Carlo (CHMC) method, which instead utilizes an energy preserving numerical method, known as the Discrete Multiplier Method. We show that CHMC converges to the correct stationary distribution under appropriate conditions and provide numerical examples showcasing improvements on acceptance rates.

This is joint work with Andy Wan from the University of Northern British Columbia.

Webex link:
https://mun.webex.com/mun/j.php?MTID=mdff68bb6ee4a7d34ae94a2b77b2c4888

AARMS Scientific Machine Learning Seminar: Scott MacLachlan (Memorial)
2022-03-29 11:00 - 12:00 UTC | WebEx seminar
Optimization and Learning in the Design of Preconditioners

Computer simulation algorithms are a major tool in many areas of science and industry, particularly in areas where the behaviour of fluids or complex materials governs the physical processes of interest. A typical core of these tools is the numerical approximation of the solution to coupled nonlinear systems of partial differential equations, relying on nonlinear and linear solvers, such as Newton’s method and preconditioned Krylov iterations. Among the most effective preconditioners for these systems are multigrid and domain decomposition methods, which use multiscale representations of the systems to be solved to achieve linear-scaling complexity for the solution of these linear systems. These preconditioners typically rely on heuristics in their construction, to approximate solutions to underlying combinatorial (and other) optimization problems that specify parameters and other components of the preconditioners, based on the discrete problem to which they are being applied. In this talk, I will discuss the use of advanced optimization and machine learning techniques to approximately solve these optimization problems and the impact these techniques can have on advanced preconditioner design.

Webex link:
https://mun.webex.com/mun/j.php?MTID=m8e73e9072ce63a9072b87874c1ee7cae

Dalhousie-AARMS AAMP Seminar: Manuela Girotti (Saint Mary's Uni.)
2022-03-25 16:00 - 17:00 (America/Halifax) | Zoom seminar
Title: Asymptotic Analysis of the Interaction Between a Soliton and a Regular Gas of Solitons (a.k.a. Gulliver and the Lilliputians)
Abstract: N. Zabusky coined the word “soliton” in 1965 to describe a curious feature he and M. Kruskal observed in their numerical simulations of the initial-value problem for a simple nonlinear PDE. The first part of the talk will be a broad introduction to the theory of solitons/solitary waves and integrable PDEs (the KdV and modified KdV equation in particular), describing classical results in the field.

The second part will focus on some new developments and growing interest into a special case of solitons defined as “solitonic gas” or “integrable turbulence”. In particular, we will discuss a recent work on long-time asymptotic behaviour of such type of solitons. We will achieve our results by first framing the problem in the setting of a Riemann–Hilbert problem and then by rigorously analyzing it using the powerful technique of nonlinear steepest descent.

This is a joint work with Tamara Grava (U. Bristol/SISSA), Bob Jenkins (UCF), Ken McLaughlin (CSU) and Alexander Minakov (U. Karlova).
The Dalhousie-AARMS Analysis-Applied Math-Physics Seminar takes place on Fridays from 4 – 5 pm Atlantic Time over Zoom. If you would like to attend, please email the organizers for connection details.

Atlantic Canada Actuarial Student Conference
2022-03-25 - 2022-03-26 | University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
We invite all Actuarial Science students from across the Atlantic region to join us for the 2022 Atlantic Canada Actuarial Student Conference!
Hosted in beautiful downtown Charlottetown, this year’s event will provide students with an opportunity to meet others from the region, gain insightful knowledge about the actuarial field from industry professionals, and provide networking opportunities through a career fair. It is a fantastic opportunity to find potential internships or full-time positions in French and English with several sponsors.
