Machine learning unravels quantum atomic vibrations in materials

Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of ...
AZoQuantum on MSN

AI-Powered Method Accelerates Analysis of Atomic Interactions in Materials

Scientists at the California Institute of Technology have devised an AI-based approach to accelerate computations of quantum ...
EDN

AccelChip adds singular value decomposition core generator to toolkit

SAN FRANCISCO — AccelChip Inc. has added a singular value decomposition (SVD) core generator to its AccelWare Advanced Math Toolkit to ease and speed implementation of sensor array processing ...
Phys.org

Speeding up calculations that reveal how electrons interact in materials

Materials scientists and engineers would like to know precisely how electrons interact and move in new materials and how the devices made with them will behave. Will the electrical current flow easily ...

Guogong Zhisoft Applies for POD Patent to Accelerate Electromagnetic Computational Model Reduction Optimization

The latest information from the National Intellectual Property Administration shows that Guogong Zhisoft (Nanjing) Information Technology Co., Ltd. applied for a patent in June 2025, titled "A Sample ...
Nature

Parallel Algorithms for Singular Value Decomposition

Parallel algorithms for singular value decomposition (SVD) have risen to prominence as an indispensable tool in high-performance numerical linear algebra. They offer significant improvements in the ...
Visual Studio Magazine

Principal Component Analysis from Scratch Using Singular Value Decomposition with C#

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...