MS
Teams
(Please
email
amgrad@uwaterloo.ca
for
the
meeting
link)
Candidate
Einar Gabbassov | Applied Mathematics, University of Waterloo
Title
Analytical and machine learning investigations into classical and quantum information flow in interactions
Abstract
In this study, we examine the dynamics of quantum information flow across multiple scenarios, primarily focusing on the interplay between a qubit-based principal system and an auxiliary system—potentially an environmental or measurement apparatus. This auxiliary system can interact with the principal system with varying intensity and duration. To quantify the intrasystem entanglement and unravel the open dynamics evolving during these interactions, we deploy strictly non-perturbative analytical techniques. Moreover, we exploit advanced machine learning methods to discern complex dynamics and the evolution of the qubit state under the influence of weak measurements or environmental noise.