Mathematics & Statistics (School of)
The School has research strengths across Pure Mathematics, Applied Mathematics and Statistics. All the Research groups are internationally-leading, and attract researchers, postgraduate students and collaborators from across the world. The School is also well-known for its research in the History of Mathematics.
For more information please visit the School of Mathematics & Statistics home page.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder
Sub-communities within this community
Collections in this community
Evolution of the transverse density structure of oscillating coronal loops inferred by forward modelling of EUV intensity (2018-07-12) - Journal articleRecent developments in the observation and modelling of kink oscillations of coronal loops have led to heightened interest over the last few years. The modification of the Transverse Density Profile (TDP) of oscillating ...
Modelling the broadband propagation of marine mammal echolocation clicks for click-based population density estimates (2018-02) - Journal articlePassive acoustic monitoring with widely-dispersed hydrophones has been suggested as a cost-effective method to monitor population densities of echolocating marine mammals. This requires an estimate of the area around each ...
(2018-08) - Journal articleSeven different models are applied to the same problem of simulating the Sun’s coronal magnetic field during the solar eclipse on 2015 March 20. All of the models are non-potential, allowing for free magnetic energy, but ...
(2018-08-09) - Journal articleWe prove the statement in the title and exhibit examples of quotients of arbitrary nilpotency class. This answers a question by Holt.
(2018-07-05) - Journal itemComing up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically‐sized datasets from scratch is ...