Computer physics of statistical systems

Course: Medical physics

Structural unit: Faculty of Physics

Title
Computer physics of statistical systems
Code
ОК12
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
3
Learning outcomes
Knowledge of the physical foundations of methods of computer modeling of physical processes in medical and biological systems. The ability to use fundamental knowledge of medical physics to conduct theoretical studies of the physical properties of biologically important multiparticle systems. The ability to correctly apply computer modeling techniques to study physical processes occurring in medical and biological systems at the molecular level. Ability to analyze the results of computer modeling of physical processes in multi-particle statistical systems
Form of study
Full-time form
Prerequisites and co-requisites
Know the laws of classical mechanics, quantum mechanics, electrodynamics, statistical physics. To be able to apply the knowledge obtained from the courses of mathematical analysis, differential and integral equations, mathematical physics. To have skills in the application of methods of thermodynamics and molecular physics.
Course content
The subject of the course is physical models, which are the basis of methods of computer modeling of multi-particle statistical systems and their connection with the fundamental laws of thermodynamics and statistical physics. The goal is to provide students with thorough knowledge of the physical foundations of methods of computer modeling of physical properties and processes in multiparticle statistical systems, which are important in the study of methodological-biological systems at the molecular level. The educational task consists in studying the physical foundations of the molecular dynamics method and the Monte Carlo method.
Recommended or required reading and other learning resources/tools
1. M. Tuckerman. Statistical Mechanics: Theory and Molecular Simulation. Oxford University Press, Oxford, 2010 р. - 720 p. 2. D. Frenkel, B. Smit. Understanding molecular simulation: from algorithms to applications. Elsevier, 2001 - 638p. 3. Shi, Y., Ren, P., Schnieders, M. and Piquemal, J.-P. (2015). Polarizable Force Fields for Biomolecular Modeling. In Reviews in Computational Chemistry Volume 28 (eds A.L. Parrill and K.B. Lipkowitz). https://doi.org/10.1002/9781118889886.ch2 4. Cisneros, G. A., Karttunen, M., Ren, P., & Sagui, C. (2014). Classical electrostatics for biomolecular simulations. Chemical reviews, 114(1), 779-814. 5. W. S. Hlavacek. Modeling Biomolecular Site Dynamics: Methods and Protocols // Humana, 2019. - 442 p. 6. H. Kamberaj. Molecular Dynamics Simulations in Statistical Physics: Theory and Applications // Springer, 2021 - 478 p. 7. K.Zhou, B. Liu. Molecular Dynamics Simulation: Fundamentals and Applications // Elsevier, 2022 - 374 p.
Planned learning activities and teaching methods
The total volume is 90 hours, including: lectures – 30 hours; independent work - 60 hours
Assessment methods and criteria
Student evaluation forms: - semester assessment: 1. Verification of estimated individual (home) tasks – 20 points/ 12 points 2. Modular control work on topic 1 – 35 points/ 21 points 3. Modular control work on topic 2 – 25 points/ 15 points - final assessment in the form of credit. The maximum score is 20 points (cut-off score is 12 points). The final number of points for the discipline (maximum 100 points), which is determined as the sum of points for systematic work during the semester and the results of the assessment. For students who during the semester did not reach the minimum grade level (60% of the maximum possible number of points), a final semester test is conducted, the maximum grade for which cannot exceed 36% of the final grade (up to 36 points on a 100-point scale).
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline