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 ...

HOLO first carefully selects high-quality quantum bits and employs advanced ion trapping technology to construct a stable and reliable quantum bit system within the quantum processor. Ion trapping ...

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 ...

Google’s Willow quantum processor ran a specific algorithm 13,000 times faster than a classical supercomputer, according to ...

The future of the spatial economy is quite literally being built on the dust of the past. Scientists are working to scrunch AI models with tensor networks, a mathematical framework borrowed from ...

The central selling point of qubit-based quantum processors is that they can supposedly solve certain types of tasks much faster than a classical computer. This comes however with the major ...

Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of the quantum interactions that take place in materials. In new work, the group ...

(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...