Quantum State Tomography

Quantum state tomography aims to reconstruct the complete description of a quantum system's state from experimental measurements. Current research focuses on improving the efficiency and accuracy of this process, particularly for high-dimensional systems, using techniques like neural networks (including generative adversarial networks and transformers), Riemannian gradient descent, and optimized classical shadow estimation algorithms. These advancements are crucial for characterizing increasingly complex quantum systems and accelerating the development of quantum technologies, impacting fields ranging from quantum computing to quantum sensing.