Quantum System

Quantum systems research focuses on understanding and controlling the behavior of quantum phenomena, primarily aiming to leverage their unique properties for computation and information processing. Current research heavily emphasizes developing robust quantum machine learning algorithms, often employing neural networks (like Fourier Neural Operators and Physics-Informed Neural Networks) and classical kernel methods to address noise and efficiently learn quantum dynamics and observables, including out-of-time-ordered correlators. These advancements are crucial for improving the accuracy and scalability of quantum technologies, with implications for materials science, drug discovery, and the development of fault-tolerant quantum computers.