Dwight E. Neuenschwander: Tensor Calculus for Physics, Johns Hopkins University Press, November 2014, 248 S., geb., $45.00, ISBN: 9781421415659 Understanding tensors is essential for any physics ...

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 ...

Interacting system: A diagram of the researchers' four-qubit superconducting quantum chip. (Courtesy: Y Yu) Researchers at Nanjing University in China have used a superconducting quantum chip to ...

We always enjoy [FloatHeadPhysics] explaining any math or physics topic. We don’t know if he’s acting or not, but he seems genuinely excited about every topic he covers, and it is infectious. He also ...

Tensors play a pivotal role in AI and deep learning systems, and share a common heritage with both physics and advanced mathematics. All of which makes it extremely difficult to lock down a definitive ...

Picture a suspension bridge. The river erodes the pillars, semi-trucks rumble across, blasts of gale-force wind whip between the cables. Through it all, the bridge must stand strong. If we can't see ...

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 ...