Dr. Sasha Dukan
Please respect this schedule and make an appointment to see me at other times.
1. Daniel V. Schroeder: An Introduction to Thermal Physics, Addison-Wesley, 2000.
2. Kittel and Kroemer: Thermal Physics, Freeman and Co. Publishing, 2nd edition.
3. F. Reif: Fundamentals of statistical and thermal physics, McGraw Hill
4. F. Reif: Statistical Physics, Berkley Physics Course-Volume 5
5. K. Huang, Introduction to Statistical Physics, Taylor and Francis, 2001
· Course Description
Statistical Physics and Thermodynamics is a course designed for physics majors and minors and upper-level chemistry majors. Statistical Physics (together with the Quantum Physics) is one of the fundamental disciplines on which modern physics research (in condensed matter physics, nuclear physics, astrophysics, biophysics, physical chemistry, materials science and engineering) relies. This course is devoted to the discussions of some of the basic physical concepts and methods appropriate for description of the systems involving very many particles (gases, liquids, crystals). It is intended, in particular, to present thermodynamics and statistical physics from unified and modern point of view.
Substantial amount of time will be devoted to the problem solving sessions and discussions. Students will be asked to present on various topics during a course of the semester. Occasionally, computer simulations will be used to aid in understanding of concepts.
· Instructional Methods
Students have an opportunity to learn in depth the undergraduate-level quantum mechanics from a variety of sources during the semester, including:
Ž Assigned textbook readings
Ž Classroom lectures and discussions
Ž Occasional computer demonstrations and simulations
Ž Homework assignments and GoucherLearn presentation of solutions
Ž In-class problem solving exercises
Ž Computational problems and projects
Ž Take-home tests
Ž Discussions with me outside of the class
Classroom time will be mostly centered around the discussions and student participation is required.
· Responsibilities of Students
In order to get the most out of this course:
Ž Attend each class, arrive on time and come prepared . Read an assigned sections of the textbook before coming to the class to familiarize yourself with notation and topic. Read the relevant section of the textbook with comprehension before attempting to solve homework problems.
Ž Participate in class by paying close attention to what is presented and offering suggestions or corrections when you think something that is presented is incorrect or confusing.
Ž Work on and try to complete all homework problems on time. You are encouraged to discuss problems with your peers but, if at all possible, complete these problems without assistance from anyone else. This way you will truly understand the problem and will be prepared for the exams.
Ž Read the homework solutions and use the opportunity to improve your homework grade by presenting a correct solution orally.
Ž Make your work neat and carefully organized. If I can’t follow your solution then you will not receive a full credit.
Ž Come talk to me outside of the class frequently. Asking for help or hints with solving problems, or asking for clarification of the lectures or the textbook demonstrates your interest in the subject.
Homework assignment of about ten problems will be assigned every Monday and will be due at beginning of a class a next Monday. All the work has to be done analytically except for the problems marked with words “use MatLab”. Otherwise, MatLab/Mathematica/Maple/Wolfram Alpha or any other symbolic/numerical software package can be used only to check a solution. No late homework will be accepted. You are encouraged to work on the homework assignments with other students, but this does not mean distributing work load or copying. Main purpose of homework is to give you practice in solving problems and prepare you for exams. Solving problems is the most important part of a learning process in this course. Students can improve a homework grade, within one week after the homework solutions have been posted, by demonstrating an understanding of a correct solution on a whiteboard in my office. Use of the solution sets that might be available on internet is not allowed. All students are bound by the standards of the Academic Honor Code and violators will be send to the Honors Board.
There will be three take-home exams. Tentative dates which may be adjusted according to rate at which material is being covered are listed in the class schedule. Exams will handed out on Fridays and will be due on Wednesdays a following week. You are allowed to use the textbook, your class-notes and the homework solutions only . You are not allowed to use any other material or discuss exams with anyone except your instructor. I reserve right to discuss your exam with you to examine your understanding of solved problems.
· Final Project
Your final project should illustrate experimental applications of the concepts discussed in lecture and/or further developments of theoretical ideas introduced. Suggested topics are:
Your grade will be based upon exams, homework and presentation. Grade breakdown is as follows:
· Homework: 20%
· Three exams: 45%
· Presentation: 15%
· Final Exam 20%
The grade distribution will be as follows:
· numerical grade larger than 90.1% is A
· numerical grade between 87.1% and 90% is A-
· numerical grade between 83.1% and 87% is B+
· numerical grade between 73.1% and 83% is B
· numerical grade between 70.1% and 73% is B-
· numerical grade between 67.1% and 70% is C+
· numerical grade between 63.1% and 67% is C
· numerical grade between 60.1% and 63% is C-
· numerical grade between 57.1% and 60% is D+
· numerical grade between 53.1% and 57% is D
· numerical grade between 50.1% and 53% is D-
· numerical grade below 50% is F
· Academic Ethics
All students are bound by the standards of the Academic Honor Code, found at