Search Talks

I discuss a new scenario called Hylogenesis (hylo=matter) that explains the baryon and dark matter densities of Universe in a unified way. Early universe dynamics generate the baryon asymmetry and an equal antibaryon asymmetry in a GeV-scale hidden sector. The hidden antibaryons are dark matter. Our model has a striking signature that dark matter can annihilate baryons, mimicking nucleon decay. I discuss the effective nucleon decay rates and implications for existing nucleon decay searches.

We describe a classification of 4d N=2 superconformal theories obtained from the compactification of 6d N=(2,0) A_N theories on punctured Riemann surfaces. We show the basic building blocks to construct any such theory and its various S-dual frames. A host of new S-dualities and interacting (non-Lagrangian) superconformal theories are unconvered. We also compute various properties of these interacting superconformal theories.

Black holes are associated with a variety of the most extreme and counter-intuitive phenomena in astronomy and physics. However, despite the passage of nearly 40 years since the discovery of the first strong black hole candidate, we have scant evidence that general relativity provides an accurate description of gravity in the immediate vicinity of astrophysical black holes. Over the next few years this will change dramatically.

The simulation of systems of anyons offers a significant challenge to the condensed matter physicist. These systems are presently of substantial theoretical and experimental interest due to their potential for universal quantum computation, but due to their non-trivial exchange statistics, the tools available for their study have been limited. In this talk, I will present a formalism whereby any existing tensor network algorithm may be adapted for use with both Abelian and non-Abelian anyons, culminating in our recent simulations of infinite 1-D chains of interacting anyons using the Multi-scale Entanglement Renormalisation Ansatz, or MERA, demonstrating that tensor network algorithms may be effectively employed in the study of anyonic systems.