Quantum distance refers to a measure of quantum mechanical similarity between two quantum states. A quantum distance of one ...

Tensor networks were initially developed in deep physics to model the behavior of atoms. Consequently, they are the best tool we currently have to predict and fine-tune the behaviors of solids.

Springer (2020). [5] Introduction. In Fundamentals of Computational Fluid Dynamics, pp. 1–12. Springer (2023). Back to "Fluid Mechanics and Thermal Engineering" ...

We present the results of a computational investigation of the pseudoflow and push-relabel algorithms for the maximum flow and minimum s-t cut problems. The two algorithms were tested on several ...

Google today released TensorFlow Graph Neural Networks (TF-GNN) in alpha, a library designed to make it easier to work with graph structured data using TensorFlow, its machine learning framework.

Meet the engineer who believes he can reduce AI’s energy consumption by up to 30% Huge savings are possible simply by changing the maths of tensor computation, says BitEnergy AI’s Hongyin Luo ...