Due to great interest, the deadline for applications is extended to 15 December 2020.
This online school is the first in a series of events to be held during 2021 under the joint title “The Hitchhiker's Guide to Condensed Matter and Statistical Physics” whose goal is to sketch a roadmap of current exciting research directions in Condensed Matter and Statistical Physics.
These events are aimed at advanced undergraduate and graduate students, as well as young researchers interested in learning more about different subjects, both from the developing world and elsewhere.
The lectures will be held once a week over 4 weeks in January and February 2021 and will lead the students from basic notions to the open problems in each topic. Each week one of the four lecturers will present 1h of basic notions + 1h of a colloquia style lecture, with ample time for discussions.
The first series of lectures will be dedicated to Machine Learning (ML) and its intersections with Condensed Matter and Statistical Physics. How can statistical physics help in understanding the theory behind ML techniques? What are the most fruitful applications of ML methods to condensed matter physics? The lectures will answer these and other questions related to ML and many-body quantum systems, quantum computing, and material physics.
G. CARLEO,EPFL, Switzerland
J. CARRASQUILLA,Vector Institute for Artificial Intelligence, Canada
B. CHENG,University of Cambridge, United Kingdom
D. SCHWAB,The Graduate Center, CUNY, USA
T. CAN, The Graduate Center, CUNY, USA
W. NGAMPRUETIKORN, The Graduate Center, CUNY, USA
F. VICENTINI, EPFL, Switzerland
Basic notions sessions will be held before the main lectures.