24-28 June 2019
CERN
Europe/Zurich timezone
There is a live webcast for this event.

Complexity and Random Matrix Approximations

27 Jun 2019, 11:00
30m
500/1-001 - Main Auditorium (CERN)

500/1-001 - Main Auditorium

CERN

400
Show room on map

Speaker

James Halverson

Description

Efforts to better understand the landscape and swampland can be stifled by computational complexity. I will discuss ways in which complexity could be overcome by learning random matrix approximations to string data, including both opportunities and caveats. As a concrete example, generative adversarial networks will be used to learn random matrix approximations to certain Calabi-Yau data, and physical implications will be discussed.

Presentation Materials