FÄ°Z606 - RELATIVISTIC QUANTUM MECHANICS
Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
---|---|---|---|---|---|---|
RELATIVISTIC QUANTUM MECHANICS | FÄ°Z606 | Any Semester/Year | 3 | 0 | 3 | 6 |
Prequisites | ||||||
Course language | Turkish | |||||
Course type | Elective | |||||
Mode of Delivery | Face-to-Face | |||||
Learning and teaching strategies | Lecture Discussion | |||||
Instructor (s) | To be determined by the Department of Physics Engineering. | |||||
Course objective | Einstein?s special theory of relativity (which extends Newtonian mechanics to high speeds) and non relativistic quantum mechanics (which extends Newtonian mechanics to atomic distances) must be unified as the relativistic quantum mechanics. Because the entities in the atomic scale move with relatively high speed. Therefore, the principle aim of this course is to acquaint the students, particulary those who would be undertaking research requiring this formalism. | |||||
Learning outcomes |
| |||||
Course Content | Brief Review of Special Theory of Relativity: Special Relativity of Einstein, Lorentz Group Introduction to Relativistic Quantum Mechanics: Probability Conservation, Klein Gordon equation, the inconsitency of the Klein.Gordon equation with the probabilistic interpretation. The construction of the Dirac equation and the properties:,the classical limit, derivation of the classical relativistic force equations using the Heisenberg picture(or the Ehrenfest theorem) for the charged Dirac system, Non relativistic limit for the charged particle in an external electromagnetic field: Pure Magnetic Field (g=2), The Fine Structure of Hydrogen: Solution of the Dirac equation in a Coulomb potential(pure Coulomb field). Covariance and symmetry properties of the Dirac equation; Covariant Form of the Dirac equation, algebra of the gamma matrices, bilinear covariants, space reflection Free particle solutions of the Dirac equation: coprojection operators for energy and spin, | |||||
References | * Relativistic Quantum Mechanics, J. D. Bjorken and S.Drell, * Relativistic Quantum Mechanics, W.Greiner and D.A. Bromley |
Course outline weekly
Weeks | Topics |
---|---|
Week 1 | Brief Review of Special Theory of Relativity: Special Relativity of Einstein, Lorentz Group |
Week 2 | Introduction to Relativistic Quantum Mechanics: Probability Conservation, Klein Gordon equation, the inconsistency of the Klein.Gordon equation with the probabilistic interpretation |
Week 3 | The construction of the Dirac equation and the properties:,the classical limit, derivation of the classical relativistic force equations using the Heisenberg picture(or the Ehrenfest theorem) for the charged Dirac system |
Week 4 | Non relativistic limit for the charged particle in an external electromagnetic field: Pure Magnetic Field (g=2), |
Week 5 | The Fine Structure of Hydrogen: Solution of the Dirac equation in a Coulomb potential(pure Coulomb field). |
Week 6 | Mid-Term |
Week 7 | Covariance and symmetry properties of the Dirac equation; Covariant Form of the Dirac equation, algebra of the gamma matrices, bilinear covariants, space reflection |
Week 8 | Free particle solutions of the Dirac equation: coprojection operators for energy and spin, construction of free Dirac spinors through the boosting |
Week 9 | Physical Interpretation of Free Particle Solutions: Klein Paradox |
Week 10 | Zitterbewung and Negative Energy Solutions, Hole Theory, Charge Conjugation |
Week 11 | Mid-Term |
Week 12 | Antiparticles, time Reversal and other symmetries |
Week 13 | The Foldy Wouthysen Transformation: Free Particle Transformation, General Transformation, Hydrogen Atom |
Week 14 | Feynman Propagator Theory |
Assesment methods
Course activities | Number | Percentage |
---|---|---|
Attendance | 0 | 0 |
Laboratory | 0 | 0 |
Application | 0 | 0 |
Field activities | 0 | 0 |
Specific practical training | 0 | 0 |
Assignments | 0 | 0 |
Presentation | 0 | 0 |
Project | 0 | 0 |
Seminar | 0 | 0 |
Midterms | 2 | 50 |
Final exam | 1 | 50 |
Total | 100 | |
Percentage of semester activities contributing grade succes | 0 | 50 |
Percentage of final exam contributing grade succes | 0 | 50 |
Total | 100 |
WORKLOAD AND ECTS CALCULATION
Activities | Number | Duration (hour) | Total Work Load |
---|---|---|---|
Course Duration (x14) | 14 | 3 | 42 |
Laboratory | 0 | 0 | 0 |
Application | 0 | 0 | 0 |
Specific practical training | 0 | 0 | 0 |
Field activities | 0 | 0 | 0 |
Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 3 | 42 |
Presentation / Seminar Preparation | 0 | 0 | 0 |
Project | 0 | 0 | 0 |
Homework assignment | 2 | 13 | 26 |
Midterms (Study duration) | 2 | 30 | 60 |
Final Exam (Study duration) | 1 | 10 | 10 |
Total Workload | 33 | 59 | 180 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
D.9. Key Learning Outcomes | Contrubition level* | ||||
---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | |
1. Combines mathematics, science and engineering knowledge in a multidisciplinary manner and implement into modern technological and scientific advanced research. | X | ||||
2. Accesses, interprets, and implements information by doing in depth applied research for technological applications. | X | ||||
3. Develops original models and designs methods to solve problems by using relevant software, hardware, and modern measurement tools. | X | ||||
4. Accesses information by doing research in certain fields, share knowledge and opinions in multidisciplinary work teams. | X | ||||
5. Implements modeling and experimental research; solves encountered complex problems. | |||||
6. Knows and follows recent improvements in the field, utilize new information to solve technological complex problems. Develops and plans methods to solve technological problems in an innovative manner. | |||||
7. Follows recent studies in the field, presents results in national and international meetings. | X | ||||
8. Knows advanced level Turkish and at least one foreign language to be able to present recent results. | |||||
9. Uses advanced communication tools related to technological methods and software. | X | ||||
10. Protects social, scientific, and ethical values while collecting and implementing, data and presenting results in scientific meetings. | X |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest