Speaker
Glen Evenbly
(University of Sherbrooke)
Description
The use of wavelet-based constructions has led to significant progress in the analytic understanding of holographic tensor networks, such as the multi-scale entanglement renormalization ansatz (MERA). In this talk I will give an overview of the (past and more recently established) connections between wavelets and MERA, and the discuss the important results that have followed. I will also discuss work currently underway that exploits the wavelet-MERA connection in order to produce new families of wavelets that are optimal for certain tasks, such as image compression.
