Efficient and accurate computation of eigenvalues and eigenvectors is of fundamental importance in the accelerator physics community. Moreover, the eigensystem analysis is generally used for the ...

The main goal of this manuscript is to introduce a discrete dynamical system defined by symmetric matrices and a real parameter. By construction, we rediscovery the Power Iteration Method from the ...

It has been known that the eigenvalues of a certain 2n × 2n matrix can be obtained by use of two smaller matrices of order n which can be easily constructed. An algorithm is given to obtain the ...

Properties from random matrix theory allow us to uncover naturally embedded signals from different data sets. While there are many parameters that can be changed, including the probability ...

Multi-matrix invariants, or equivalently the scalar multi-trace operators of N=4 super Yang-Mills with U(N) gauge symmetry, are in one-to-one correspondence with the elements of the permutation ...

This article presents a from-scratch C# implementation of the second technique: using SVD to compute eigenvalues and eigenvectors from the standardized source data. If you're not familiar with PCA, ...

Boise State’s Computer Science department has made the decision to launch a certificate program tailored for students interested in Large Language Models (LLMs) from a technical standpoint. The ...