Tensor networks take a central role in quantum physics as they can provide an efficient approximation to specific classes of quantum states. The associated graphical language can also easily describe and pictorially reason about quantum circuits, channels, protocols and open systems. In a recent study, A. Jahn and a research team in the departments of complex quantum systems, materials and energy and mathematics and computer science in Germany introduced a versatile and efficient framework to study tensor networks by extending previous tools. The researchers used bulk tiling (computing geometric technique) in their work to obtain highly accurate critical data and established a link between holographic quantum error-correcting codes and tensor networks. They expect the work to stimulate further investigations of tensor network models to capture bulk-boundary correspondences. The results are now published on Science Advances.