Conference for Young Researchers in Mathematics and Theoretical Physics

The PhD students in Mathematics and Theoretical Physics at the Science Institute will present their work on May 19, in Askja, room N-130. Here you can see the preliminary schedule:

1. Álfheiður Edda Sigurðardóttir, Potential Theory
   • Abstract: The electrical potential around any charged object is a subharmonic function with certain growth. The study of such functions is what mathematicians call Potential Theory, and the aim of this talk will be to introduce that theory.
2. Evangelos Tsolakidis, Gedankenexperiment for Deformations
   • Abstract: The study of systems at different scales which lead to the renormalization group method, has been a main protagonist in theoretical physics over the last half century with numerous applications. During this talk, I will present the main ideas and consequences of scaling transformations in the observed behaviour of systems through a thought experiment, focusing mostly on the classification of deformations and their physical importance.
3. Tamari Meshveliani, Self-interacting dark matter: an overview
   • Abstract: In my presentation, I will talk about dark matter and its importance in structure formation. I will overview the current standard model of cosmology (Lambda-CDM) and continue with introducing the Self-Interacting Dark Matter and its advantage to explain the small-scale (< few Mpc) structures. 
4. Matthias B. Harksen, Non-Relativistic Closed String Theory,  
   • Abstract: In [arXiv:hep-th/0009181] a non-relativistic closed string theory model was proposed (the Gomis-Ooguri model). The goal of the talk will be to derive this model (more specifically equation (3.8) in the referenced paper).
5. Alexia Nix, String Theory, the AdS/CFT correspondence and all that 
   • Abstract: During this talk we will give a brief introduction to the basic properties of String Theory. We will follow with an elementary introduction of the so-called AdS/CFT correspondence and highlight how we may use this duality as a window to the unknown features that govern strongly coupled theories, which are generally difficult to understand. As we shall see, this correspondence has not been proven and thus remains a conjecture. Therefore, various so-called holographic precision tests have been established in an effort to provide evidence for this duality and this will be the main focus of the talk.
6. Atli Fannar Franklín, Permutations on Few Inversions
   • Abstract: The generating function for permutations of {1, 2, …, n} with exactly n inversions is presented. Moreover, the generating function for exactly n – i inversions is presented as well along with an overview of the proofs for these claims.
7. Daniel Amankwah, The Jones polynomial and its limitations 
   • Abstract: The talk will be an exposition of the Kauffman bracket polynomial model of the Jones polynomial, tangle methods for computing the Jones polynomial, and the use of these methods to produce non-trivial links that cannot be detected by the Jones polynomial.
8. Rahul Poddar, Asymptotic Symmetries and Holography
   • Abstract: Asymptotic symmetries are very important tools for understanding holographic dualities. We will look at a simple example of holography, namely the AdS_3/CFT_2 correspondence. We will begin by understanding conformal symmetry, and what implications this has for a quantum field theory with this symmetry. Then we will see how negatively curved spacetimes in 3 dimensions implement this symmetry holographically, and how this suggests that quantum gravity is holographic in nature.
9. Brynjólfur G. Guðrúnar Jónsson, Improved 21st century projections of sub-daily extreme precipitation by spatio-temporal recalibration 
   • Abstract: In this talk, I will present my PhD research on incorporating data-level spatial correlations in the Generalized Extreme Value (GEV) distribution for improved modeling of extreme precipitation in large datasets. Using the Max-and-smooth method of Hrafnkelsson et al. (2020) we can add spatial correlations to the parameters governing each location’s GEV distribution (i.e. the time between extreme events is similar in nearby locations), but we also need to model the correlations in the observed data itself (i.e. extreme events happen at similar times in nearby locations). By using copulas, multivariate distributions with all univariate margins being Uniform(0, 1) distributed, we might be able to more accurately represent the data-level correlations while aiming to keep the computation-time feasible.