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Computational Quantum Dynamics - Einzelansicht

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Grunddaten
Veranstaltungsart Vorlesung Langtext
Veranstaltungsnummer 220830 Kurztext
Semester WS 2023 SWS 2
Teilnehmer 1. Platzvergabe 20 Max. Teilnehmer 2. Platzvergabe 24
Rhythmus Jedes 2. Semester Studienjahr
Credits für IB und SPZ
E-Learning
Hyperlink
Sprache Englisch
Belegungsfrist Zur Zeit keine Belegung möglich
Abmeldefristen A1-Belegung ohne Abmeldung    14.08.2023 09:00:00 - 09.10.2023 08:29:59   
A2-Belegung mit Abmeldung 2 Wochen    09.10.2023 08:30:00 - 30.10.2023 23:59:59   
A3-Belegung ohne Abmeldung    31.10.2023 00:00:01 - 19.02.2024 08:29:59   
Termine Gruppe: 0-Gruppe iCalendar Export für Outlook
  Tag Zeit Rhythmus Dauer Raum Lehrperson (Zuständigkeit) Status Bemerkung fällt aus am Max. Teilnehmer 2. Platzvergabe
Einzeltermine anzeigen Mo. 14:00 bis 16:00 w. 16.10.2023 bis
09.02.2024
Extern - interner Raum   findet statt  
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Zugeordnete Person
Zugeordnete Person Zuständigkeit
Gärttner, Martin, Universitätsprofessor, Dr. verantwortlich
Zuordnung zu Einrichtungen
Physikalisch-Astronomische Fakultät
Inhalt
Kommentar

The aim of this lecture is to provide an introduction to computational methods used to model quantum mechanics problems. We will cover all aspects of the modeling process, from abstraction and representation of the wave function and exact and approximate numerical methods for solving the stationary and time-dependent Schrödinger equation to data handling and visualization of the simulation results. We will not go too deep into the subtleties of numerical methods but rather pursue a pragmatic hands-on approach guided by physical problems and how to use a high-level programming language to model them.

The programming language we use is Python. The exercises will be provided as Jupiter notebooks that may already contain code fragments that are to be edited and completed. This choice is motivated by the fact that Python Scipy modules combine all necessary tools from numerical routines to data handing and visualization on a single non-commercial platform.

Installation instructions for Python with Jupyter notebooks can be found at: https://jupyter.readthedocs.io/en/latest/install.html

Prerequisites: The course is directed at physics students from the 5th semester onward and requires an introductory Quantum theory lecture and basic programming skills, preferably in Python. However, a brief Python tutorial will be provided.

Mode of examination (to be confirmed): Students are required to complete the programming exercises and a programming project that can be done in groups of two students. This programming project will be focused and deepen one of the topics covered in the lecture and may include reproducing the results of a recent publication. Topics for the projects will be announced on the lecture homepage.

 

Literatur

Literature: There are many books on computational physics. Here are some, which I can recommend:

-          J. M. Thijssen, Computational Physics, Cambridge University Press, Cambridge, 1999

-          Nicholas J. Giordano, Computational Physics, Pearson Education (1996) ISBN 0133677230.

-          Harvey Gould and Jan Tobochnik, An Introduction to Computer Simulation Methods, 2nd edition, Addison Wesley (1996), ISBN 00201506041

-          Tao Pang, An Introduction to Computational Physics, Cambridge University Press (1997) ISBN 0521485924

Moreover, some of the topics covered in the lecture, can be found in the following lecture notes:

-          Computational quantum physics course by Matthias Troyer from ETH Zürich: http://edu.itp.phys.ethz.ch/fs09/cqp/Script1.pdf

-          Lecture notes “Numerical methods in quantum mechanics” by Paolo Giannozzi (University of Udine): https://archive.org/details/Paolo_Giannozzi___Numerical_Methods_in_Quantum_Mechanics/page/n0

Zielgruppe

Physik Studierende ab dem 5. Semester.

Strukturbaum
Keine Einordnung ins Vorlesungsverzeichnis vorhanden. Veranstaltung ist aus dem Semester WS 2023 , Aktuelles Semester: SoSe 2024

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