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 ...

When the FORTRAN programming language debuted in 1957, it transformed how scientists and engineers programmed computers. Complex calculations could suddenly be expressed in concise, math-like notation ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

The Google Tensor G4 on the Pixel 9 phones performs poorly on the Geekbench CPU test, despite packing the latest ARM cores. The older ARM Mali-G715 GPU on the Tensor G4 is also pretty weak, ...

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...

(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 ...

Google’s in-house Tensor chips have steadily improved over the years to become a reliable daily driver with solid battery efficiency. Still, performance has often been a sticking point. While previous ...

Qiskit addons are a collection of modular tools for building utility-scale workloads powered by Qiskit. This addon enables a Qiskit user to perform approximate quantum compilation using tensor ...

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The study of many-body quantum systems out of equilibrium remains a significant challenge, with complexity barriers arising in both state- and operator-based representations. Here, we review the ...