Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...

Tensor network methods provide a structured approach to representing and manipulating high-dimensional data by decomposing global information into interconnected low-rank tensors. Originating in the ...

A hunk of material bustles with electrons, one tickling another as they bop around. Quantifying how one particle jostles others in that scrum is so complicated that, beginning in the 1990s, physicists ...

The quantum many body problem has been at the heart of much of theoretical and experimental physics over the past few decades. Even though we have understood the fundamental laws that govern the ...

For analytically solvable DU circuits, they found that when moving away from exactly solvable points, quantum results agreed with advanced classical tensor-network simulations, even at scales where ...