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Faculty of Physics and Applied Computer Science

Examination topics in the discipline:

Physical sciences

The candidate is expected to answer questions from the general list and one of the specialized list of his/her choice.

1. Fundamentals of classical and relativistic mechanics:

  • Momentum conservation principle
  • Angular momentum conservation principle
  • Energy conservation principle
  • Galileo and Lorentz transformations
  • Mass-energy equivalence, examples

2. Electromagnetism:

  • charge conservation principle
  • Electrostatic field, scalar potential
  • Magnetic field, Vector potential of magnetic field
  • Electric charge in magnetic field (examples of applications)
  • Electromagnetic wave equation
  • Plane and spherical waves
  • Interference and diffraction

3. Thermodynamics and statistical physics:

  • Maxwell distribution
  • Boltzmann distribution
  • Temperature
  • I principle of thermodynamics
  • Entropy and II principle of thermodynamics

 4. Experimental and theoretical foundations of quantum mechanics:

  • Black-body radiation
  • Photoelectric effect
  • Compton effect
  • atomic spectral lines
  • Electron diffraction on crystal (Davisson-Germer experiment)
  • Stern-Gerlach experiment, electron spin
  • Postulates of quantum mechanics
  • wave function
  • uncertainty principle

5. Structure of matter:

  • atom and its structure
  • chemical bonds
  • electron band structure of solids
  • electrical conductivity of metals, semiconductors and insulators
  • superconductivity
  • magnetism of solids
  • crystal structure

 

1. Fundamentals of biophysics

  • Synchrotron radiation – generation, properties and examples of applications in biological studies
  • Methods in surface science (for example: AES – Auger electron spectroscopy, XPS – X-ray photoelectron spectroscopy, SIMS – secondary ion mass spectrometry)
  • Spectroscopic methods in biological and medical investigations (for example: EPR,
  • NMR, Mössbauer spectroscopy, Infrared and Raman spectroscopy)
  • Microscopies of high resolution (electron microscopy, STM – scanning tunneling microscopy, AFM – atomic force microscopy, confocal microscopy)
  • Biological membranes – their structure and properties
  • Proteins and enzymatic reactions
  • Radiative and non-radiative energy transfer (Jabłoński diagram, Förster resonance energy transfer (FRET), Dexter energy transfer)
  • Electron transfer in biological systems (temperature dependent and temperature independent – tunneling)

 

2. Fundamentals of nuclear physics

  • Elementary particles – the standard model
  • Evolution of the Universe (in particular: creation of elements)
  • Properties of atomic nuclei and the methods of their investigation
  • Nuclear forces, binding energy, models of atomic nucleus
  • Radioactive transformations of atomic nuclei
  • Natural radioactivity of rocks, waters and air
  • Accelerators of charged particles
  • Nuclear reactions (in particular: fission and fusion of nuclei)
  • Interaction of charged particles, gamma radiation and neutrons with matter
  • Detection of charge particles, gamma radiation and neutrons
  • Neutron sources
  • Applications of nuclear isotopes (chosen examples)

 

3. Fundamentals of solid state physics:

  • Crystallography – basic definitions
  • Free-electron model
  • Interatomic bonds in solids
  • X-ray diffraction
  • Phonons
  • Electron band-structure
  • Semiconductors
  • Magnetic properties of matter
  • Superconductivity
  • Applications of NMR and Mössbauer Spectroscopy in Solid State Physics
  • Synchrotron radiation – generation, properties and examples of application
  • Basic ideas of new materials: quasicrystals, fullerenes, high-temperature superconductors, conducting polymers, semiconducting nanostructures

 

4. Fundamentals of theoretical and computational physics

  • Postulates of quantum mechanics – illustrated by examples
  • Physical interpretation of wave function
  • Quantum stationary states
  • Electron spin: experiment and theory
  • Quantum statistics: : bosons and fermions
  • Pauli exclusion principle
  • Exchange Interaction
  • Laplace and Poisson equations and physical processes described by these equations
  • Diffusion equation and physical processes described by this equation
  • Simple finite-difference methods of solving equations of classical dynamics
  • Physical and numerical foundations of classical molecular dynamics
  • The method of simulated annealing

 

5. Elements of  elementary particle interactions and detection techniques

  • Elementary particles – the Standard Model: matter particles and bosons mediating the interactions. Unification of electroweak interactions.
  • Relativistic momentum, kinetic energy, total energy, relativistic effects, four-vectors formalizm and relativistic invariants (e.g. CMS)
  • Feynman diagram formalism
  • Electromagnetic processes (photoeffect, Compton effect, pair production, total cross section)
  • Strong interactions (inelastic scattering)
  • Accelerators of charged particles (colliders & fixed-target, linear & circular)
  • Bethe-Bloch formula
  • Elementary principles in particle detection, spectrometry, tracking and calorimetry.
  • Fundamental concepts of collider experiments – on the example of LHC experiments (ATLAS, CMS, ALICE, LHCb)
  • The working principles of radiation detectors (gaseous detector, scintillation counter, semiconductor detector, photomultiplier)
  • Principles of operation of basic semiconductor devices: p-n junction, bipolar transistor, MOS transistor
  • Basic principles of signal processing (signal processing in spectrometer, filtering, ENC)

Information and communication technology

  • Algorithmics - definition of the algorithm, time and space complexity, classes of complexity, examples of algorithms differ in complexity classes. Asymptotic notations, running time estimation. Sorting algorithms, BFS and DFS algorithm, a minimal spanning tree of a graph, the shortest path problem and algorithms. The concept of a data structure. Different types of data structures, i.e., single-linked and double-linked lists, hash tables, binary search trees (BST), red-black trees, representations of a directed/undirected graph, and their pros and cons
  • Programming languages – procedural, object-oriented, and functional languages. Popular control structures/phrases: if, for, while, do, return, break, new, delete, super, etc. Their meaning and use. The overall structure of a program providing in object-oriented and functional languages. Effective use of data structures in various programming languages. Object-oriented programming - concepts of inheritance, polymorphism, and projection. Throwing and handling exceptions.
  • Parallel processing - the concept of a thread and a process. The idea of shared memory, mutual exclusion, thread, and processes synchronization. Synchronization errors, deadlock, and livelock issues. Models of concurrent systems: dining philosophers' problem, readers and writers, producers and consumers, etc. Synchronization mechanisms: semaphore, monitor, and CAS (compare-and-swap) mechanism. Their meaning and implementations in the contemporary programming languages.
  • Formal languages - Chomsky's taxonomy of formal languages and automata corresponding to these languages. Turing machine as a computation model. Classes of computability: NP, NP-complete, NP-hard, and others. Examples of problems belonging to these classes. Halting problem. The relationship between formal languages and programming languages.
  • Databases - types of databases. The architecture of a relational database: tables, relations, keys, indexes, views, component procedures, etc. Basics of SQL, types of queries, and their syntax. Database normalization, normal forms. Effective use of databases. Integration of programming languages and DBs.
  • Software engineering - requirements engineering, product engineering. Acquisition and analysis of requirements. Models of the software development process. Structural software analysis and modeling. ERD, DFD, STD, FHD diagrams. Object-oriented design (OOD) and analysis (OOA). The concept of object, class, method, message, pattern, encapsulation, interface. UML language - basic diagrams. Software quality - evaluation methods, software metrics, quality management in the software development process.
  • General IT knowledge - computer architecture and design. Problems and challenges of AI, Turing test vs. the Chinese room idea. Computer-aided decision-making. The idea of heuristics. Examples of heuristic algorithms. Binary arithmetic. Basics of formal logic and discrete mathematics. Examples of computer applications.

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