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Unit information: Statistical Mechanics 34 in 2020/21

Unit name Statistical Mechanics 34
Unit code MATHM4500
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Wiesner
Open unit status Not open
Pre-requisites

MATH11009 Mechanics 1

Some of the concepts introduced in the course will be more familiar to those who have taken MATH21900 Mechanics 2 and MATH35500 Quantum Mechanics but these are not required

MATH21900 Mechanics 2 or MATH31910 Mechanics 23

Co-requisites

None

School/department School of Mathematics
Faculty Faculty of Science

Description

Unit Aims

Introduction to the mathematical foundations of thermodynamics and statistical mechanics.

Unit Description

The unit begins with a discussion of thermodynamics, the macroscopic (large scale) laws of heat. In contrast to mechanical systems, thermodynamics is fundamentally irreversible, so for example processes like thermal equilibration, combustion, and mixing can occur spontaneously, but the reverse processes never occur without external input. This leads to fixed constraints on the capabilities of (for example) engines, fridges and living organisms.

The remainder of the unit ("statistical mechanics") deals with the microscopic basis for thermodynamics, that is, explaining large scale properties from properties of individual molecules. Although the dynamical equations can be solved exactly in only a very few cases, the very large number of particles means that statistical assumptions are often justified, making a strongly predictive and irreversible theory from reversible mechanics. Both equilibrium and non-equilibrium situations will be covered, ending with a brief discussion of numerical simulation methods.

Relation to Other Units

Statistical mechanics is a branch of mathematical physics, along with mechanics, quantum mechanics and relativity. Its molecular treatment of fluids is complementary to the continuum approaches in the fluids units. There are also connections with information theory and chaotic dynamics. Connections with probability and statistics exist, but are not strong. Some parts of the unit are similar to Thermal Physics and Condensed Matter and Statistical Mechanics offered in physics; the approach here is more mathematical, and more directed towards research interests of the department, including fluids, dynamical systems, biological physics, nonequilibrium systems and computational methods.

This is a double-badged version of the Level 6 Mathematics unit MATH34300 Statistical Mechanics 3, sharing the lectures but with differentiated problems and exam. Students may not take both units.

Intended learning outcomes

Learning Objectives

By the end of the unit the students should be familiar with the main concepts of thermodynamics, equilibrium and nonequilibrium statistical mechanics, understand thermodynamic limitations of systems, and be able to derive thermodynamic properties of systems of weakly interacting particles.

Transferable Skills

Clear, logical thinking and an ability to comprehend and solve problems of mathematical physics.

Teaching details

The unit will be taught through a combination of

  • synchronous online and, if subsequently possible, face-to-face lectures
  • asynchronous online materials, including narrated presentations and worked examples
  • guided asynchronous independent activities such as problem sheets and/or other exercises
  • synchronous weekly group problem/example classes, workshops and/or tutorials
  • synchronous weekly group tutorials
  • synchronous weekly office hours

Assessment Details

90% Timed, open-book examination 10% Coursework

Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.

If you fail this unit and are required to resit, reassessment is by a written examination in the August/September Resit and Supplementary exam period.

Reading and References

Recommended

  • C.J. Adkins, Equilibrium Thermodynamics, Cambridge 1983
  • David Chandler, Introduction to Modern Statistical Mechanics, Oxford 1987
  • J.R. Doffman, An Introduction to Chaos in Non-equilibrium Statistical Mechanics, Cambridge University Press, 1999
  • Mehran Kardar, Statistical Physics of Particles, Cambridge University Press, 2007
  • Michel LeBellac, Fabrice Mortessagne and G. George Batronni, Equilibrium and Non-equilibrium Statistical Thermodynamics, Cambridge University Press, 2004
  • R.K. Pathria, Statistical Mechanics, Elsevier, 2005

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