COMPUTATIONAL QUANTUM PHYSICS
| Title | ΥΠΟΛΟΓΙΣΤΙΚΗ ΚΒΑΝΤΙΚΗ ΦΥΣΙΚΗ / COMPUTATIONAL QUANTUM PHYSICS |
| Code | ΥΦΥ205 |
| Faculty | Sciences |
| School | Physics |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter/Spring |
| Coordinator | Charalampos Moustakidis |
| Common | No |
| Status | Active |
| Course ID | 600027785 |
Programme of Study: PMS YPOLOGISTIKĪ FYSIKĪ 2025
Registered students: 0
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Elective Courses belonging to the selected specialization | 2 | 1 | 7.5 |
| Academic Year | 2025 – 2026 |
| Class Period | Spring |
| Faculty Instructors | |
| Class ID | 600286363
|
Type Of Offer
- Disciplinary Course
Course Type 2021
Specialization / Direction
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600286363
- At the Website of the School: https://pms.physics.auth.gr/comphys/lessons/ypologistiki-kvantiki-fysiki-kai-efarmoges/
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basic knowledge of undergraduate level Quantum Mechanics topics
Learning Outcomes
Understanding of theoretical foundations: Students will be able to analyze and interpret the fundamental principles of quantum mechanics and the computational models that describe them.
Use of numerical methods: They will be able to apply advanced computational techniques (e.g., Monte Carlo methods, discretization of Schrödinger’s equation) to solve quantum systems.
Familiarity with specialized software: They will be able to use modern computational tools and programming languages (e.g., Python, Fortran, MATLAB) for simulations and analysis of quantum phenomena.
Modeling and simulation: They will be able to develop models of quantum systems and simulate them on classical and quantum computers, assessing the accuracy and limitations of each method.
Interdisciplinary applications: They will understand and examine practical applications of computational quantum physics in materials science, nanotechnology, chemistry, and quantum information.
Research and critical skills: They will develop independent research abilities, critically evaluate scientific literature, and present their results effectively.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work in an interdisciplinary team
- Generate new research ideas
Course Content (Syllabus)
A1. NUMERICAL METHODS FOR QUANTUM PHYSICS PROBLEMS
Root finding
Differentiation and initial value problems
Numerical integration
Eigenvalue problems
Fourier transform
A2. SOLVING THE SCHRÖDINGER EQUATION
One-dimensional problems
Multi-dimensional problems
Time propagation
Central potential
Many-electron systems
B. APPLICATIONS OF MACHINE LEARNING IN QUANTUM PHYSICS
Introduction to Machine Learning
Kernel methods and applications
FermiNet (Quantum Physics and Chemistry from First Principles)
C. Optional
Solving advanced topics in Quantum Physics
Educational Material Types
- Notes
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 120 | ||||
| Laboratory Work | 50 | ||||
| Reading Assigment | 32 | ||||
| Written assigments | 20 | ||||
| Exams | 3 | ||||
| Total | 225 |
Student Assessment
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Problem Solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
ΚΒΑΝΤΙΚΗ ΜΗΧΑΝΙΚΗ
Κωδικός Βιβλίου στον Εύδοξο: 122090349
Έκδοση: 1η/2024
Συγγραφείς: ZETTILI NOUREDINE
ISBN: 9789606330704
Τύπος: Σύγγραμμα
Διαθέτης (Εκδότης): "σοφία" Ανώνυμη Εκδοτική & Εμπορική Εταιρεία
Last Update
02-10-2025
