Manuscript Topics

Introduction
In mathematics, Probabilistic number theory is a subfield of number theory, which Explicitly uses probability to answer questions about the integers and integer-valued functions. One basic idea underlying it is that different prime numbers are, in some serious sense, like independent random variables. This however is not an idea that has a unique useful formal expression. Historically, computation has been a driving force in the development of mathematics. To help measure the sizes of their fields, the Egyptians invented geometry. To help predict the positions of the planets, the Greeks invented trigonometry. Algebra was invented to deal with equations that arose when mathematics was used to model the world.

Challenges 
In order to solve these equations of Number theory, the computational modelling in number theory arose. In particular, Mathematical and computational modelling in number theory have been applied in engineering, science and medicine to study phenomena at a wide range of size scales. In pure mathematics we also compute, and many of our great theorems and conjectures are, at root, motivated by computational experience.
Thanks to advances in computers, many problems in science and engineering can be modeled by polynomial optimization.

Aims of Special Issue 

We aim to design this special issue for researchers with an interest in Mathematical and computational methods in Number theory, algebra and combinatorics. This special issue aims to present theory, methods, and applications of recent/current mathematical and computational methods related to number theory in various area.

Proposal Topics 

Each paper that will be published in this special issue aims at enriching the understanding of current research problems, theories, and applications on the chosen topics. The emphasis will be to present the basic developments concerning an idea in full detail, and also contain the most recent advances made in the area of mathematical theory and its applications related to probabilistic computation in number theory.

Potential topics include but are not limited to the following:
• Mathematical and computational methods and its applications in Probabilistic Number theory
• Computational modeling related to degenerate functions and polynomials
• Properties and theories to degenerate umbral and umbral calculus
• Analytical properties and applications of polylogarithm and polyexponential functions
• Applications of polylogarithmic and polyexponential functions in the view of probabilistic methods
• Random variables and degenerate Poisson random variable related to computational modeling
• Properties of ordinary and general families of Special Polynomials in the view of probabilistic methods
• Multiple zeta function related to Moment of random variable
• Generalization of Spivey’s Recurrence Relation in the view of probabilistic methods
• Operational techniques involving Special Polynomials...etc

Key words
Laguerre polynomials, degenerate Poisson random variable, degenerate Bernstein polynomials, computational modelling in number theory, Dowling lattice, r-truncated Poisson random variables, degenerate binomial random variable, umbral calculus, degenerate umbral calculus, polyexponential function, degenerate poly-Bernoulli polynomials.

Instructions for authors
https://www.aimspress.com/math/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
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