Recently, deep neural networks have proven capable of predicting some output properties
of relevant random quantum circuits, indicating a strategy to emulate quantum computers …

Density functional theory (DFT) is routinely employed in material science and quantum
chemistry to simulate weakly correlated electronic systems. Recently, deep learning (DL) …

Predicting the output of quantum circuits is a hard computational task that plays a pivotal role
in the development of universal quantum computers. Here we investigate the supervised …

In recent years, machine learning models, chiefly deep neural networks, have revealed
suited to learn accurate energy-density functionals from data. However, problematic …