Software and computer systems for high energy physics

Course: Quantum field theory

Structural unit: Faculty of Physics

Title
Software and computer systems for high energy physics
Code
ВБ 3.3
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
6
Learning outcomes
Know the basic technologies for working with large volumes of data used in high-energy physics Know software packages and complexes for simulating collisions between nuclei and elementary particles To know the chronology of the universe, the phenomena of high-energy physics in the early universe Know software packages for simulating high-energy physics processes in the early universe Be able to use technologies of parallel, cloud, distributed computing Be able to apply the simplest machine learning algorithms to data sorting problems To be able to classify software packages and complexes depending on the area of ​​their application, the numerical methods underlying them Be able to estimate the complexity of the data processing algorithm depending on the amount of data Be able to work with the documentation for the software package
Form of study
Full-time form
Prerequisites and co-requisites
1. Know the basics of the general course of physics, classical and quantum mechanics, electrodynamics, thermodynamics, numerical methods, cosmology. 2. To be able to reduce a physical problem to a correctly posed computational problem, analyze the results of one's work. 3. Have skills in working with a computer, educational literature, interaction with colleagues during training.
Course content
Module 1. PKK for ground-based FVE experiments 1 Modern experiments in high-energy physics: typical setup, implementation, problem of data processing and storage 2 Parallel, cloud, distributed computing. Grid systems. Modern supercomputers 3 Application of artificial intelligence and machine learning technologies to data processing of simulations and real experiments 4 Simulation of proton-proton and nucleus-nucleus collisions: UrQMD 5 Modeling processes outside the Standard Model Module 2. PKK for simulations in the cosmology of the early universe 6 High-energy physics in the early universe 7 Boltzmann codes for describing the evolution of primary perturbations in the early universe: CAMB, CLASS 8 Simulations of the formation of the large-scale structure of the Universe: Millennium project, EAGLE, Illustris 9 Modeling the dynamics of scalar and gauge fields in an expanding universe: Defrost, GABE, CosmoLattice
Recommended or required reading and other learning resources/tools
1. Fruchwirth R. et al. (Eds.). Data Analysis Techniques for High-Energy Physics. – Cambridge: Cambridge University Press, 2000. 2. Lista L. Statistical Methods for Data Analysis in Particle Physics. – Berlin: Springer, 2017. 3. Martinez V.J. et al. (Eds.). Data Analysis in Cosmology. – Berlin: Springer, 2009. 4. Behnke O. et al. (Eds.). Data Analysis in High Energy Physics: A Practical Guide to Statistical Methods. – Singapore: Wiley-VCH, 2013. 5. Brun R. et al. (Eds.). From the Web to the Grid and Beyond: Computing Paradigms Driven by High Energy Physics. – Berlin: Springer, 2012.
Planned learning activities and teaching methods
• Lectures • Practical training • Individual work
Assessment methods and criteria
• Current control in the form of an oral survey • control works • Control of homework • assessment work
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline