Covers the complexity and learnability in complex quantum systems, focusing on quantum advantages in learning and predicting properties of quantum states.
Covers quantum mechanics exercises on spatial interference and coupling between oscillators, emphasizing independent problem-solving and the implications of measurement in quantum systems.
Explores the Eigenstate Thermalization Hypothesis in quantum systems, emphasizing the random matrix theory and the behavior of observables in thermal equilibrium.
Introduces mathematical tools for communication systems and data science, focusing on stochastic processes and preparing students for advanced courses.
Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.