Statistical Mechanics B(2.0 credits)
|Course Type||:||Specialized Courses|
|Course Name||:||Applied Physics|
|Starts 1||:||3 the latter term|
|Lecturer||:||TAKENAKA Koshi Professor|
|From the introduction of quantum statistical mechanics and its several practical applications, students learn the fundamental concepts and the mathematical techniques in statistical mechanics.
1. Understanding the quantum statistical mechanics and calculation and the use of Fermi statistics and Bose statistics
2. Understanding and exploiting basic ideas in statistical mechanics
|Thermodynamics, Statistical Mechanics A, Quantum Mechanics A|
|This class consists of the following seven contents:
(1) Review of classical mechanics and quantum mechanics
(2) Classical statistical mechanics and quantum statistical mechanics
(3) Fermi statistics and Bose statistics
(4) Application of Fermi statistics
(5) Application of Bose statistics
(6) Systems with strong interactions
(7) Brownian motion
Read in advance the materials to be distributed and the corresponding sections in the textbook. You will be required to complete and submit nine reports during class.
|Y. Nagaoka, Statistical Physics (Iwanami)
In addition to the above, materials are distributed in advance.
|R. Kubo et ai., Statistical Mechanics (North-Holland Personal Library)|
|(Evaluation method) In addition to the mid-term exam (full score: 50) and the final exam (full score: 100), the evaluation will be based on nine reports (full score: 10x9) that are imposed during class. 80% exams, 20% reports.
(Evaluation criteria) Passing grade: 60 points out of 100
|This course is based on the three subjects of Thermodynamics, Statistical Mechanics A, and Quantum Mechanics A specified in the background courses, as well as the mathematics and basic physics required to acquire these subjects. You can take the course even if you do not have the credits of the above three classes.
* Please note that this lecture will be conducted as follows from the viewpoint of coronavirus infection prevention:
Lectures will be held online. Lecture notes and other materials will be uploaded to NUCT. Please download and self-learn. Homework will be also uploaded to NUCT as appropriate, so please work and submit as instructed.
|Questions are welcome within or after each lecture.