## Archived seminars in MathematicsSeminars 1 to 50 | Next 50 seminars |

### Colin Fox

*Physics University of Otago*

Date: Tuesday 17 November 2020

### Raphael Krier and Cesar Acevedo Ramirez

*Department of Geolgraphy University of Otago*

Date: Tuesday 20 October 2020

$\cdots$

Spurs and Grooves (SAG) structures can be found on coral reefs around the world. However, there are few studies that relate SAG morphology with wave transformation process. Using an array of pressure sensors and current meters deployed over 10 days we present observations of wave dissipation over SAG structures at Xahualxol, Quintana Roo, Mexico. This site has a different morphology of SAG compared to previous studies. Our results indicate that SAG structures are more important in wave transformation than has previously been reported. The rate of dissipation (up to 80W/m2) and the wave dissipation friction factor, fw, (1.1) found, are also high compared to previous values found on other reefs. We also found that the wave dissipation rate over the spurs can be up to three times higher than in the adjacent grooves. This study demonstrates that SAG morphologies play a discernable role in wave dissipation over the forereef.

### Mike Paulin

*Department of Zoology University of Otago*

Date: Tuesday 13 October 2020

### Dr Hamza Bennani

*Department of Computer Science at Otago*

Date: Tuesday 6 October 2020

We validated the results in vitro on radiographs of dried vertebrae with models constructed from a laser-scanner, then in vivo on radiographs of living patients with models extracted from CT scans or MRI.

The results show the feasibility of generating personalised models of patients from bi-planar radiographs.

The contributions are:

- Evaluation of the methods for creating 3D models of vertebrae and estimation of the errors in comparison with ground truth data. These methods are applicable to other free-form shapes;

- Creation of landmark free ASMs of lumbar vertebrae;

- Definition and evaluation of a process for estimating the shape and position of lumbar spine from uncalibrated bi-planar radiographs.

### Anindya Sen

*Department of Accountancy and Finance University of Otago*

Date: Tuesday 29 September 2020

### Mike Steel

*University of Canterbury*

Date: Tuesday 11 August 2020

### Joshua Ritchie

*Mathematics and Statistics Department University of Otago*

Date: Tuesday 21 July 2020

### David Bryant

*Mathematics and Statistics, University of Otago*

Date: Tuesday 17 March 2020

### Melissa Tacy

*Mathematics and Statistics Department University of Otago*

Date: Tuesday 10 March 2020

### Ronald Peeters

*Economics Department University of Otago*

Date: Tuesday 3 March 2020

### Sebastian Herr

*Bielefeld University*

Date: Tuesday 11 February 2020

### Christian Lubich

*Mathematisches Institut Universitaet Tuebingen*

Date: Tuesday 12 November 2019

### Yiming Ma

*Mathematics and Statistics, University of Otago*

Date: Tuesday 8 October 2019

### Phillip Wilcox

*Mathematics and Statistics, University of Otago*

Date: Thursday 3 October 2019

### Tom McCone

*Department of Mathematics and Statistics*

Date: Tuesday 1 October 2019

### Paul Gardner

*Department of Biochemistry, Otago*

Date: Tuesday 24 September 2019

### Travis Scrimshaw

*University of Queensland*

Date: Tuesday 17 September 2019

### Radek Erban

*University of Oxford*

Date: Tuesday 10 September 2019

### Ronald Peeters

*Economics Department*

Date: Tuesday 3 September 2019

### Jinge Lu

*Otago Computer Science*

Date: Tuesday 20 August 2019

### Fabien Montiel

*Department of Mathematics and Statistics*

Date: Tuesday 13 August 2019

### Dmitry Jakobson

*McGill University*

Date: Tuesday 6 August 2019

### Steven Mills

*Department of Computer Science*

Date: Tuesday 30 July 2019

### Zach Weber

*Philosophy Department University of Otago*

Date: Tuesday 23 July 2019

### Arkadii Slinko

*Department of Mathematics. University of Auckland*

Date: Tuesday 9 July 2019

### Leo Tzou

*University of Sydney*

Date: Tuesday 11 June 2019

### Florian Beyer

*Mathematics and Statistics, University of Otago*

Date: Tuesday 28 May 2019

### Brendan Creutz

*School of Mathematics and Statistics, University of Canterbury*

Date: Tuesday 14 May 2019

### Michael Albert

*University of Otago Computer Science*

Date: Tuesday 7 May 2019

### Geertrui van de Voorde

*School of Mathematics and Statistics University of Canterbury*

Date: Tuesday 16 April 2019

### Sarah Wakes

*Department of Mathematics and Statistics*

Date: Tuesday 9 April 2019

### Tim Candy

*Department of Mathematics and Statistics*

Date: Tuesday 2 April 2019

### Conor Finnegan

*University College Dublin*

Date: Tuesday 26 March 2019

### Andrew Robinson

*University of Melbourne*

Date: Thursday 21 March 2019

### Lech Szymanski

*Department of Computer Science, University of Otago*

Date: Tuesday 19 March 2019

### Robert van Gorder

*Department of Mathematics and Statistics, University of Otago*

Date: Tuesday 12 March 2019

These conditions generalize a variety of results known in the literature, such as the algebraic inequalities commonly used as sufficient criteria for the Turing instability on static domains, and approximate or asymptotic results valid for specific types of growth, or for specific domains.

### Russell Higgs

*School of Mathematics and Statistics, University College Dublin*

Date: Tuesday 5 March 2019

### Alex Gavryushkin

*Department of Computer Science University of Otago*

Date: Tuesday 16 October 2018

### Marnus Stoltz

*Department of Mathematics and Statistics*

Date: Tuesday 9 October 2018

### Nikola Stoilov

*University of Burgundy*

Date: Tuesday 25 September 2018

### Mike Hendy

*Department of Mathematics and Statistics*

Date: Tuesday 18 September 2018

$|a_{ij} |≤1,∀i,j⟹|det(A) |≤n^{(n⁄2)}$,

and found matrices satisfying this bound for many values of $n$.

An $n×n$ real matrix $A=(a_{ij})$ with entries $|a_{ij}|≤1$ satisfying

$| det(A)|=n^{(n∕2)}$

is now referred to as a Hadamard matrix. We will see that for $n≥4$, Hadamard matrices can exist only for $n≡0$ (mod 4). Although there are Hadamard matrices for an infinite number of multiples of 4, the Hadamard conjecture that postulates there exists a Hadamard matrix of order $n$, for each positive integer multiple of 4, has remained unresolved for 125 years.

In this talk I will present some practical applications of Hadamard matrices, including my own discovery of their application in phylogenetics, and reveal a personal encounter with Hadamard's ghost.

### Alex Gavryushkin

*Department of Computer Science*

Date: Tuesday 11 September 2018

### Chris Stevens

*Rhodes University, South Africa*

Date: Tuesday 4 September 2018

We are now in the exciting new era of gravitational wave astronomy, where we can study the universe through the gravitational waves emitted by massive events such as coalescing black holes or neutron stars.

An important part of gravitational wave astronomy is the numerical simulations that compute the emitted gravitational radiation, which are non-trivial since the simulations are on a physical domain of finite extent but gravitational waves are unambiguously defined only at future null infinity (scri+). There are a number of methods for waveform estimation, but only in characteristic extraction is the waveform calculated at scri+.

We present a new algorithm and implementation of characteristic extraction. It has the key feature of being simply extendable to characteristic matching, in which the characteristic evolution provides outer boundary data for the "3+1" simulation. The key advantage of characteristic matching is that it would lead to a significant speed-up in the time required to complete a numerical simulation.

### Melissa Tacy

*Department of Mathematics and Statistics*

Date: Tuesday 21 August 2018

### Dominic Searles

*Department of Mathematics and Statistics*

Date: Tuesday 14 August 2018

### David Bryant

*Department of Mathematics and Statistics*

Date: Thursday 9 August 2018

### Ilija Tolich

*Department of Mathematics and Statistics*

Date: Tuesday 31 July 2018

The Baumslag-Solitar group is an example of an amenable quasi-lattice ordered group. In particular, it is an HNN-extension of the integers. Studying the Baumslag-Solitar group gave us the insight to prove a new means of detecting amenability in quasi-lattice ordered groups and also to construct new examples of amenable quasi-lattice ordered groups.

### Dominic Searles

*Department of Mathematics and Statistics*

Date: Tuesday 29 May 2018

In joint work with Assaf, we consider the application of Kohnert's algorithm to arbitrary box diagrams in the positive quadrant; we call the resulting polynomials Kohnert polynomials. We establish some structural results about Kohnert polynomials, including that their stable limits are quasisymmetric. Certain choices of box diagrams yield bases of the polynomial ring in a natural way; as an application, we use these results to introduce a new basis of polynomials whose stable limit is a new basis of quasisymmetric functions that contains the Schur functions. Some further conjectures regarding Kohnert polynomials will be presented.

### Honours and PGDip students

*Department of Mathematics and Statistics*

Date: Friday 25 May 2018

Qing Ruan : ~~Bootstrap selection in kernel density estimation with edge correction~~

Willie Huang : ~~Autoregressive hidden Markov model - an application to tremor data~~

MATHEMATICS

Tom Blennerhassett : ~~Modelling groundwater flow using Finite Elements in FEniCS~~

Peixiong Kang : ~~Numerical solution of the geodesic equation in cosmological spacetimes with acausal regions~~

Lydia Turley : ~~Modelling character evolution using the Ornstein Uhlenbeck process~~

Ben Wilks : ~~Analytic continuation of the scattering function in water waves~~

Shonaugh Wright : ~~Hilbert spaces and orthogonality~~

Jay Bhana : ~~Visualising black holes using MATLAB~~

### Boris Daszuta

*Department of Mathematics and Statistics*

Date: Tuesday 22 May 2018

In particular, assuming a moment in time symmetry in vacuum reduces the problem of solving the constraints to a restriction of zero scalar curvature associated with the initial data set. A result due to [1] at the analytical level provides a technique for local control on the aforementioned set and may be used to engineer initial data with well-defined asymptotics. In short, one may glue together distinct, known solutions from differing regions in a controlled manner forming new data.

The aim of this talk is to demonstrate how a numerical scheme may be fashioned out of the above and present results pertaining to a numerical gluing construction.

Ref:

[1]: (Corvino, J.) Scalar Curvature Deformation and a Gluing Construction for the Einstein Constraint Equations. ~~Communications in Mathematical Physics~~ 214, 1 (2000), 137-189.