Jeremy has more than 2200 published articles on Collider to his name, and has been writing for the site since February 2022. He's an omnivore when it comes to his movie-watching diet, so will gladly ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Click to share on X (Opens in new window) X Click to share on Facebook (Opens in new window) Facebook Michael ends up finding himself trapped on the roof of his school with the Agents closing in on ...

Abstract: The recently developed two-directional unconditionally stable single-field (US-SF) finite-difference time-domain (FDTD) method is generalized to a 3-D. The method is based on the application ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

Add a description, image, and links to the tridiagonal-matrix-algorithm topic page so that developers can more easily learn about it.

Abstract: The solution of tridiagonal linear systems is used in in various fields and plays a crucial role in numerical simulations. However, there is few efficient solver for tridiagonal linear ...

Matrix classes for matrices that are block-tridiagonal and sparse, and simply "block sparse". These talk together, and furthermore containts an algorithm for inversion of the block-tridiagonal version ...