Computational Methods in Modern Physics

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Computational Methods in Modern Physics

Course Description

Different computing methods used for simulations in contemporary physics problems are presented through four topics. Ray tracing in curved spacetime: Spacetime. Curved spacetime. Metric. Path length. Riemannov tensor. Einstein s equation and spherically symmetric solutions. Light propagation in curved spacetime. Numerical solutions of differential equation. Ray-tracing. Gravitational lens. Application of machine learning to event classification in high energy physics: Introduction to ground-based gamma-astronomy: observed objects and instruments. Data acquisition and analysis chain. Event reconstruction. Problem of signal separation in the presence of high levels of noise. Application of random forest algorithm to the gamma-hadron separation problem in high energy physics. Atomic bonds in molecules and solids: quantum-mechanical model and classical approximation. Crystal lattice. Material surface adsorption: chemisorption and physisorption. Van der Waals material layers (graphen as an example). Finding optimal structure by quantum-mechanical simulation and/or using classical approximation. Calculation of ionizing radiation shields by fast engineering methods. Green's function method for point and distributed radiation sources. Build-up factor for gamma radiation inside shields. Green's function for removing fast neutrons in water. Diffusion approximation of the neutron transport equation and some of its applications.

Learning Outcomes

Describe the curved spacetime and light trajectories in the curved spacetime.
Apply ray tracing technique to optics problems.
Describe the crystal lattice and interatomic forces.
Apply the concept of force and energy to finding the optimum configuration of a system.
Explain the concept of short and long range interactions.
Identify quantitatively abrupt structural change in a system.
Apply a machine learning algorithm to a classification problem.

Forms of Teaching

Lectures

Introduction to physics of the topic

Independent assignments

Work on projects

Laboratory

Help for work on projects

Grading Method

	Continuous Assessment		Exam
Type	Threshold	Percent of Grade	Threshold	Percent of Grade
Laboratory Exercises	0 %	20 %	0 %	20 %
Homeworks	0 %	80 %	0 %	0 %
Exam: Written			0 %	80 %

Week by Week Schedule

High-energy physics events
High-energy physics events, Application of machine learning to event classification
Application of machine learning to event classification
Metric in curved spacetime
Geodesic equation, Metric in curved spacetime
Geodesic equation, Tracing photon trajectories
Tracing photon trajectories
Midterm exam
Van der Waals force interactions
Van der Waals force interactions, Graphene layers
Graphene layers
Ionizing radiation shields. Gamma radiation inside shields.
Neutron transport equations and applications.
Neutron transport equations and applications.
Final exam

Study Programmes

University undergraduate

[FER3-HR] Computing - study

Elective Courses (6. semester)

[FER3-HR] Electrical Engineering and Information Technology - study

Elective Courses (6. semester)