Infopaket

Modern Computational Technologies in Physics of Nuclei and Elementary Particles

ВБ 3.1

Вибіркова дисципліна для ОП

Second

2023/2024

3 Semester

6

Know the theoretical foundations of numerical methods for solving typical problems that arise in the physics of the nucleus and elementary particles Know the syntax of the Wolfram language and the principles of building programs Know the theoretical foundations and methods of parallel computing provided by the Wolfram language Know the methods of visualization of the results of calculations, processing and storage of data provided by the Wolfram language Be able to apply numerical methods to solve typical problems arising in the physics of the nucleus and elementary particles Be able to analyze the program code for efficiency, speed and apply methods of its optimization To be able to apply the methods of parallel calculations, to analyze their effectiveness Be able to visualize the results of calculations in the form of charts, graphs, pictures, videos and operate with different types of files

Full-time form

1. Know the basics of linear algebra, mathematical analysis, theory of functions of a complex variable, differential equations, tensor analysis, mathematical physics, probability theory, statistics, and numerical methods. 2. To be able to reduce a physical problem to a correctly set computational problem, evaluate the accuracy of the performed calculations, analyze the results of one's work. 3. Have skills in working with a computer, educational literature, interaction with colleagues during training.

Module 1. Functionality of the Wolfram language 1 Syntax of the Wolfram Language 2 Functional of linear algebra and tensor analysis 3 Mathematical analysis, differential equations and their systems 4 Symbolic calculations, simplification of expressions, work with special functions 5 Construction of 2D, 3D, contour graphs, diagrams, import and export of files Module 2. Data processing and parallel programming in the Wolfram language 6 Working with large data sets 7 Statistical data processing 8 Parallel computing and GPU computing capabilities 9 Work with neural networks

Basic: 1. Hastings C., Mischo K., Morrison M. Hands-On Start to Wolfram Mathematica® and Programming with the Wolfram Language™. – Champaign: Wolfram Media, 2016. 2. Leon J. G. S. Mathematica® Beyond Mathematics. The Wolfram Language™ in the Real World, Boca Raton: CRC Press, 2017. 3. Torrence B.F., Torrence E.A. The Student’s Introduction to Mathematica® and the Wolfram Language™. – Cambridge: Cambridge University Press, 2019. Additional: 1. Alva J.V. Beginning Mathematica and Wolfram for Data Science. – Berkeley: Apress, 2021. – 416 p. 2. Wolfram S. The Mathematica Book. – Champaign: Wolfram Media, 2003.

• Lectures • Practical training • Individual work

• Current control in the form of an oral survey • control works • thematic control of independent work • assessment work

Ukrainian