Quantum generative machine learning for quantum state tomography

In recent years, advancements in the quantum hardware technology have brought us to the dawn of the quantum computing era. While quantum computers are believed to possess immense computational power, designing algorithms to effectively harness this power remains a non-trivial challenge. One area under active exploration is quantum machine learning. To find applications where quantum machine learning can leverage "quantumness" to its advantage, we investigate its performance on classical data with "quantum characteristics." Specifically, we explore the application of quantum generative machine learning techniques to quantum state tomography. Quantum state tomography refers to the operation where, given an ensemble of quantum states prepared identically, one attempts to reconstruct the quantum state based on the measurements. As such, the measured data serves as an ideal candidate for classical data with a quantum origin. Hence, we use quantum state tomography as a testbed to assess the practicality of quantum machine learning.