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DRPS : Course Catalogue : School of Physics and Astronomy : Undergraduate (School of Physics and Astronomy)

Undergraduate Course: Statistical Physics (PHYS11024)

Course Outline
SchoolSchool of Physics and Astronomy CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Year 4 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis is a course on the statistical physics of interacting particles. We begin by reviewing the fundamental assumptions of equilibrium statistical mechanics focussing on the relation between missing information (or entropy) and probability. We then consider the statistical mechanics of interacting particles and develop important approximation schemes. This leads us to review phase transitions and the unifying phenomenology. We study in detail a simple, microscopic model for phase transitions: the Ising model. We then consider a general theoretical framework known as
Landau Theory. Finally we discuss the issue of dynamics: how does a system approach and explore the state of thermal equilibrium? How does one reconcile microscopic time reversibility with the macroscopic arrow of time?
Course description I Derivation of Statistical Ensembles
Maximising the missing information or Gibbs entropy
Derivation of the principal ensembles: microcanonical; canonical; grand canonical
Quantum systems: Fermi-Dirac, Bose-Einstein, classical limit
Bose-Einstein Condensation

II The Many-Body Problem
Interacting systems
Phonons and the Debye theory of specific heat of solids
Perturbation theory and cluster expansion
Breakdown of perturbation theory
Non-perturbative ideas: Debye-H\"uckel Theory

III Transitions
Phenomenology of phase transitions
The Ising Model
Solution in one dimension
Correlation functions and correlation length
Mean-field theory
long range order in two dimensions, lack of in one dimension
Landau Theory
Order Parameter
Critical exponents and Universality

IV The Arrow of Time
Hamiltonian dynamics and phase space
Liouville's theorem
Coarse graining
The master equation
Random walks and the diffusion equation
Detailed balance
Brownian motion and the Langevin equation
Dynamics of fluctuations
Fluctuation-dissipation relations and Linear Response

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements At least 80 credit points accrued in courses of SCQF Level 9 or 10 drawn from Schedule Q.
Information for Visiting Students
Pre-requisitesNone
Course Delivery Information
Academic year 2014/15, Available to all students (SV1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Supervised Practical/Workshop/Studio Hours 11, Summative Assessment Hours 2, Revision Session Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 61 )
Assessment (Further Info) Written Exam 100 %, Coursework 0 %, Practical Exam 0 %
Additional Information (Assessment) Degree Examination, 100%
Visiting Student Variant Assessment
Degree Examination, 100%
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)Statistical Physics2:00
Learning Outcomes
Upon successful completion of this course it is intended that a student will be able to:

1) Define and distinguish between the Boltzmann and Gibbs
entropies

2) Derive the principal ensembles of Statistical Physics
by using the method of Lagrange multipliers to maximise the Gibbs entropy

3) Discuss the many-body problem and be able to formulate and motivate various approximation schemes.

4) Describe the phenomenology of phase transitions
in particular Bose-Einstein condensation, liquid-gas transition and ferromagnetic ordering.

5) Formulate the Ising model of phase transitions and be able to motivate and work out various mean-field theories

6) Articulate the paradox of the arrow of time.

7) Formulate mathematical descriptions of dynamics such as Fermi's master equation, Langevin equations and the diffusion equation; solve simple examples of such descriptions such as random walks and Brownian motion

8) Discuss and formulate fluctuation-dissipation relations and linear correlation and response theory
Reading List
None
Additional Information
Course URL http://www2.ph.ed.ac.uk/teaching/course-notes/notes/list/70
Graduate Attributes and Skills Not entered
KeywordsStatP
Contacts
Course organiserProf Arjun Berera
Tel: (0131 6)50 5246
Email: ab@ph.ed.ac.uk
Course secretaryMs Rebecca Thomas
Tel: (0131 6)50 7218
Email: R.Thomas@ed.ac.uk
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