|Monday 6 December 2021|
|Events for day: Wednesday 13 October 2021|
| 11:00 - 12:00 Wednesday Weekly Seminar - google meet|
Holographic Interpretation of Entanglement Wedge Cross-Section and Its Time Evolution
PARTICLES AND ACCELERATORS
Abstract: In the context of gauge/gravity duality, it is known that some information-theoretic quantities in a quantum field theory may have a simple geometric description in a dual gravitational theory and vice versa. The most famous example should be the (entanglement) entropy that is related to the area of a certain extremal surface in a higher dimensional theory of gravity. In this talk, I will briefly review this dictionary and focus on the concept of Entanglement Wedge Cross-Section and its dual descriptions as a measure of correlation in mixed states. In particular, I will argue how this quantity may describe the thermalization proce ...
14:00 - 15:00 Weekly Seminar
Condensed Matter and Statistical Physics Group
Localization and delocalization in one-dimensional Anderson model with a general hopping matrix
Much of our present understanding of wave-function localization in one spatial dimension is based on the original Anderson model on a one-dimensional lattice. The experimental simulation of this model using cold atoms, owing to the high degree of control over system parameters, has made possible the direct observation of localization of matter waves. In this talk, after giving an introduction to Anderson localization, I will present some new results on localization properties of this model with a general hopping matrix.
Date: Wednesday, October 13, 2021
To join ...
15:30 - 17:30 Mathematical Logic Weekly Seminar
Large Fields with Stable and Simple Theories
I will discuss how the property of "largeness" of a field (introduced by
Pop) can be used in the model theory of fields to help solve conjectures and questions about fields whose first order theory is stable or simple.
This is a joint with Erik Walsberg.
Meeting ID: 879 2979 2112
16:00 - 17:00 Quantum Computing & Quantum Information Monthly Seminar
Integrating Machine Learning into the Electronic Structure Theory
The technological and theoretical advances in the past decades have led to the reemergence of machine learning (ML) applications in physical sciences providing unprecedented opportunities to find efficient and accurate solutions to the most challenging problems in these disciplines. Finding the electronic structures of real-world materials is one of the prime examples of such problems in quantum chemistry and condensed matter physics as they will shape the fundamental understanding of dynamics and evolution of electronic and magnetic properties. In this talk, I will present a brief review of the current state of ML applications in material sc ...