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X-WR-CALNAME:Centre for Mathematical Sciences
X-ORIGINAL-URL:https://math-sciences.org
X-WR-CALDESC:Events for Centre for Mathematical Sciences
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DTSTART:20210101T000000
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DTSTART;TZID=UTC:20211103T160000
DTEND;TZID=UTC:20211103T170000
DTSTAMP:20211204T224706
CREATED:20210809T130605Z
LAST-MODIFIED:20211029T095737Z
UID:4082-1635955200-1635958800@math-sciences.org
SUMMARY:Anne Spiering (Trinity College Dublin)
DESCRIPTION:Integrability and chaos in super Yang-Mills theories from anomalous-dimension spectra \nThe discovery of integrability in planar maximally supersymmetric\nYang-Mills (SYM) theory led to considerable advances in the exact\ncomputation of its CFT data. In this talk I will review these advances\nand discuss universal statistical properties of anomalous-dimension\nspectra in SYM theories in the planar limit and at finite rank of the\ngauge group. I will show how they can give insight into the nature of\nthe underlying model\, in particular we will see integrability manifest\nitself in the planar integrable limit of certain SYM theories\, while\nnon-integrable spectra can be described by random matrix theory\,\nindicating their quantum-chaotic nature.
URL:https://math-sciences.org/event/anne-spiering-trinity-college-dublin/
CATEGORIES:Seminars,Theoretical Physics
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BEGIN:VEVENT
DTSTART;TZID=UTC:20211110T160000
DTEND;TZID=UTC:20211110T170000
DTSTAMP:20211204T224706
CREATED:20210726T180202Z
LAST-MODIFIED:20211105T113117Z
UID:4065-1636560000-1636563600@math-sciences.org
SUMMARY:Anna Lisa Varri (Edinburgh)
DESCRIPTION:The dynamics of rotating stellar systems and their black holes\n\nThe study of self-gravitating rotating bodies is a classical fluid dynamics problem with a distinguished history\, yet the equilibrium and stability of rotating spheroidal stellar systems have rarely been explored. After introducing some basic mathematical modelling tools in stellar dynamics\, I will present a family of self-consistent equilibria describing uniformly rotating\, axisymmetric quasi-relaxed stellar systems. Such equilibria define a singular perturbation Vlasov-Poisson problem with a free boundary which can be approached by means of an asymptotic expansion based on the rotation strength parameter. I will then illustrate a generalisation to the case of stellar systems with central black holes\, for which a novel treatment of the boundary conditions of the relevant Poisson equation allows for a solution with matched asymptotics. I will conclude by discussing the astrophysical relevance of such results in the current era of black holes images and gravitational waves detection.
URL:https://math-sciences.org/event/anna-lisa-varri-edinburgh/
LOCATION:Zoom
CATEGORIES:Seminars,Theoretical Physics
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BEGIN:VEVENT
DTSTART;TZID=UTC:20211117T150000
DTEND;TZID=UTC:20211117T160000
DTSTAMP:20211204T224706
CREATED:20210902T152241Z
LAST-MODIFIED:20210903T171019Z
UID:4086-1637161200-1637164800@math-sciences.org
SUMMARY:Neda Trifonova (Aberdeen)
DESCRIPTION:Bayesian Network Modelling Provides Spatial and Temporal Understanding of Ecosystem Dynamics within Shallow Shelf Seas \nAbstract: There is about to be an abrupt step-change in the use of our coastal seas\, specifically by the addition of large-scale offshore renewable energy developments to combat climate change. Many trade-offs will need to be weighed up for the future sustainable management of marine ecosystems between renewables and other uses (e.g.\, fisheries\, marine protected areas). Therefore\, we need a much greater understanding of how different marine habitats and ecosystems are likely to change with both natural and anthropogenic transformations. Ecosystems consist of complex dynamic interactions among species and the environment\, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However\, with the recent adoption of more explorative tools\, like Bayesian networks\, in predictive ecology\, few assumptions can be made about the data and complex\, spatially varying interactions can be recovered from collected field data. In this talk\, Bayesian techniques will be presented to find the data-driven estimates of interactions among a set of physical and biological variables and a human pressure within the last 30 years in a well-studied shallow sea (North Sea\, UK). A hidden variable is incorporated to model functional ecosystem change\, where the underlying interactions dramatically change\, following natural or anthropogenic disturbance. Then\, the learned data-driven interactions will be used to build a dynamic Bayesian network model to examine the response of species to changes in their environment. Other examples will also be illustrated to show the applications of Bayesian network techniques in predictive ecology.
URL:https://math-sciences.org/event/neda-trifonova-aberdeen/
LOCATION:Zoom
CATEGORIES:Applied Mathematics,Seminars,Statistics and Data Science
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