Random Matrix Theory (RMT) has emerged as a potent framework to characterise the statistical properties of eigenvalues in large complex systems, bridging disciplines from quantum physics to number ...

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 ...

Probability distributions of different neutrino mass models. The horizontal axis shows the ordinary logarithm of the neutrino mass squared difference ratio, while the vertical axis shows their ...

This research work is about Limited Data Acquisition for the real life physical experiment of fluid flow across cylinder based on Kernelized Extended Dynamic Mode Decomposition by incorporating ...

In December 2019, the COVID-19 pandemic began, which has claimed the lives of millions of people around the world. This article presents a regional analysis of COVID-19 in Mexico. Due to comorbidities ...

Scientists have used random matrix theory to theoretically show that neutrino mass hierarchy can be mathematically explained. Random matrix theory helps explain neutrino mass differences, supporting ...

We consider the product of a large number of two 2 × 2 matrices chosen randomly (with some correlation): at any round there are transition probabilities for the matrix type, depending on the choice at ...

Abstract: Random matrix theory has found many applications in physics, statistics and engineering since its inception. Although early developments were motivated by practical experimental problems, ...