Abstract: This paper addresses the problem of designing nonlinear discrete-time dynamical systems for prospective use in low-complexity random signal generators. Drawing upon ergodic systems theory, ...

Abstract: To achieve the maximum information transfer and face a possible eavesdropper, the samples transmitted in continuous-variable quantum key distribution (CV-QKD) protocols are to be drawn from ...

Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

This important study introduces a fully differentiable variant of the Gillespie algorithm as an approximate stochastic simulation scheme for complex chemical reaction networks, allowing kinetic ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The application presented here utilizes the R Shiny platform to ...

1 Department of Mathematics, Kotebe University of Education, Addis Ababa, Ethiopia 2 Department of Statistics, Addis Ababa University, Addis Ababa, Ethiopia The main purpose of this paper is to ...

When is it appropriate to completely reinvent the wheel? To an outsider, that seems to happen a lot in category theory, and probability theory isn’t spared from this treatment. We’ve had a useful ...

What Is A Probability Density Function? A probability density function, also known as a bell curve, is a fundamental statistics concept, that describes the likelihood of a continuous random variable ...

All the scripts were developed on MATLAB 2023a (compatible with MATLAB 2022b or later). This file contains two main scripts: CoherentBasis.m FockBasis.m which define two types of classes. The first ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...