Explore the intersection of quantum physics and machine learning in this 50-minute lecture by Max PRÜFER from TU Wien. Delve into physics-inspired models and Hamiltonian learning techniques used to understand and predict the behavior of complex quantum systems. Gain insights into cutting-edge approaches that bridge the gap between theoretical physics and data-driven methodologies, enhancing our ability to analyze and manipulate quantum phenomena.
Learning Quantum Systems: From Physics-Inspired Models to Hamiltonian Learning
ICTP Condensed Matter and Statistical Physics via YouTube
Overview
Syllabus
Learning quantum systems: from physics-inspired models to Hamiltonian learning
Taught by
ICTP Condensed Matter and Statistical Physics
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