MCQST Special Colloquium: Ting Cao

5 June 2024
from 14:00 to 16:00

MCQST Special Colloquium | Ting Cao (University of Washington)

MCQST Colloquium

Address / Location

MPI of Quantum Optics | Herbert Walther Lecture Hall

Hans-Kopferman-Straße 1



Show Map

Hide Map

The MCQST Colloquium Series features interdisciplinary talks given by visiting international speakers. The monthly colloquium covers topics spanning all MCQST research units and will be broadcast live via Zoom for audiences worldwide. The main goal of the series is to create the framework for idea exchange, to strengthen links with QST leading groups worldwide, as well as to act as an integral part of the local educational environment.

MCQST Special Colloquium: Ting Cao

We are excited to invite you to the special edition of the MCQST colloquium, where Ting Cao will give a talk on "New Theoretical Insights into Moiré Solids from Machine Learning".

New Theoretical Insights into Moiré Solids from Machine Learning

This talk will show our recent theoretical and computational investigations into moiré superlattices using machine-learning-based approaches. We start by demonstrating that a deep neural network guided by first-principles data can be used to examine moiré structural reconstruction in various homobilayers and heterobilayers of transition metal dichalcogenides. Going beyond the capacity of direct DFT calculations, our machine-learning-enabled workflow discovers salient structural features, band topology, and excitonic states all controlled by twist angles, layer composition, and other tuning knobs. This knowledge can be used to inform accurate continuum models and to predict new forms of moiré potential and correlated topological phases. Finally, we connect our theoretical discoveries to experimental results and explore potential applications.

About Ting Cao

Ting Cao is an assistant professor of Materials Science & Engineering at the University of Washington. His research uses quantum physics, advanced modelling techniques, and high-performance parallel computing to understand condensed matter and predict material properties.

Join in-person or via Zoom

Meeting ID: 998 9779 8115
Passcode: mcqst2024

Accept privacy?

Accept privacy?

Scroll to top