Alena Tensor in flat and curved space-time We used Alena Tensor to describe a system with an electromagnetic field, obtaining three forces in flat space-time: electromagnetism (which is not surprising ...

Vienna startup Ora Computing raised €3.5M and proved a 70-billion-parameter large language model can be compressed for under ...

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 ...

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 ...

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 ...

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 ...

Many aspects of gauge theories — such as the one underlying quantum chromodynamics, which describes quark physics — evade common numerical methods. Tensor networks are getting closer to a solution, ...

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 ...

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 ...