Semester 1 and Semester 2.

Unit(s) of Assessment	Weighting Towards Module Mark( %)
Electromagnetic Waves Examination	17%
Additional Mechanics Examination	17%
Galaxies and Large Scale Structures Examination	17%
MCS Coursework	17%
Laboratory (Physics)	32%
Qualifying Condition(s):   University general regulations refer.

Note:  Modelling Complex Systems has no examination

Assessment Schedule

Examination Paper 4 (June):   2.5 hour (maximum) examination consisting of;   Answer 1 from 2 questions on Electromagnetic Waves   Answer 1 from 2 questions on Additional Mechanics   Answer 1 from 2 questions on Galaxies and Large Scale Structures   (weighted at 100% of the Specialist Physics A examination unit of assessment)

Coursework (Semester 2):   Modelling Complex Systems Group Presentation   Modelling Complex Systems Written Report   Note: the Group Presentation and Report marks are equally weighted.

Laboratory (Semester 1 & Semester 2):   Laboratory Diary aggregate (16%)   Laboratory Report (8%)   Laboratory Oral (8%)   Note: the weight of each Laboratory mark to the total module mark is indicated

Electromagnetic Waves, Additional Mechanics and Modelling Complex Systems:   PH1031 - Waves, Particles and Quanta Module or equivalent   PH1012 -Mathematics Module     Galaxies and Large Scale Structures:   None.     Experimentation (Physics):   PH1011 – Experimental Physics Module

Electromagnetic Waves:   To provide competence in basic electromagnetic theory and problem solving. Solution problems involving magnetic circuits.  To establish the four integral Maxwell's equations which are of fundamental importance in physics. Combine these to investigate electromagnetic wave propagation.     Additional Mechanics:   To introduce the students to analytical classical mechanics and enable students to obtain equations of motion using more powerful and elegant methods than have been available previously.     Modelling Complex Systems:   To characterize complex systems in nature and man-made systems. To introduce the student to the basic concepts behind neural networks, genetic algorithms, stochastic techniques and game theory.  To highlight the range of application of these techniques in finance and in the physical sciences.  To communicate scientific ideas orally.     Galaxies and Large Scale Structures:   To familiarise students with the main features of the formation and evolution of galaxies, galaxy clusters and superclusters, and other large scale structures.  Students will be introduced to the observational evidence and the physics implications.     Experimentation (Physics):   To build on the foundation of earlier practical classes and emphasize the motivations for performing experiments both to verify theory and to improve understanding.  The importance of keeping a laboratory notebook (diary) and the clear presentation of results will be stressed.

Electromagnetic Waves:   Students should be able to tackle problems involving magnetic circuits, understand and apply Maxwell’s equations, derive electromagnetic wave equation and apply to TEM waves.     Additional Mechanics:   At the end of the component, students should be able to   -          state, derive and use the Minimum Energy Principle, the Principle of Virtual work and D’Alembert’s Principle, as appropriate, to solve problems in classical mechanics,   -          state Lagrange’s equation and use the Lagrangian formalism to obtain equations of motion,   -          state Hamilton ’s equations and use the Hamiltonian formalism to obtain equations of motion.     Modelling Complex Systems:   At the end of the component, students should   -          be able to identify the general characteristics of a complex system.   -          be able to describe the general structure of neural networks, explain the workings of a three-layer, feed-forward, fully connected network in detail and describe how neural networks can be trained   -          be able to explain the use of the genetic algorithm for optimization problems   -          understand how pseudo-random numbers are generated by a computer and how different distributions may be generated, explain the Metropolis algorithm and the principles of importance sampling   -          be able to qualitatively explain game theory, its relationship to group interaction and company behaviour   -          be able to précis research papers and present the results orally.     Galaxies and Large Scale Structures:   Students will have an appreciation for the important large scale features of the Universe.  They will be able to describe the nature of galaxies and the way that they evolve.  They will understand how observations lead to deductions about galaxy clusters, superclusters and even larger structures in the Universe.     Experimentation (Physics):   On successful completion you will be able to perform an experiment of intermediate difficulty, either involving practical or computational skills, by following written instruction. You will be able to keep a comprehensive diary of the activity, recording results in a form useful to others, and to complete a full but selective report, based on the diary, in the style of a scientific paper. The specific practical skills gained will vary according to the choice of the experiments.

Electromagnetic Waves:   The investigates further the topics of magnetism and electromagnetic waves.     Diamagnets, Paramagnets, Ferromagnetics, Magnetisation M, Magnetisation current, Magnetic intensity H, Magnetic permeability, Magnetic susceptibility, Magnetic circuits, Reluctance, Hysteresis, Permanent magnets, Boundary conditions for B and H.     Displacement current, fourth Maxwell equation, review of vector analysis, Electromagnetic Waves, Speed, Refractive index, Attenuation, Skin depth, Uniform Plane waves, Linear Polarisation, Energy density and Power of Waves, Waves at Boundaries - reflection & refraction.     Fresnel's equations, Brewster angle, Total Internal reflection.     Additional Mechanics:   A more sophisticated treatment of classical mechanics including the concept of generalised co-ordinates and introducing the Lagrangian and Hamiltonian formulations.     Introduction and Review: Newton's Laws, motion of a system of N particles, conservation laws, energy, the Minimum Energy Principle, constraints, degrees of freedom, the Principle of Virtual work and D’Alembert’s Principle (with applications to simple systems).     Lagrangian Formulation and Applications: Generalised coordinates, velocities and forces leading to the derivation of Lagrange’s equation.  Application of the Lagrangian method to the projectile, simple pendulum, motion under the action of central forces, and motion in a rotating frame of reference (Coriolis and centrifugal forces).    Hamiltonian Formulation: Generalised momenta, derivation of Hamilton ’s equations.  Application to the simple pendulum and central forces leading to a discussion of orbits.     Modelling Complex Systems:   This module provides an introduction to some computational techniques widely used in management, finance and in the physical sciences.     Module Content:   -          Properties of complex systems; emergent behaviour, scale-invariance.   -          Artificial Neural Networks (ANN): general concepts, focus on the three-layer, feed-forward, fully connected ANN.  Training an ANN by back propagation.   -          Genetic algorithms (GA): reproduction, cross-over and mutation.  Linking GAs to ANNs.   -          Stochastic simulation and Monte Carlo methods: pseudo-random numbers, manipulating of stochastic variables, simple Monte Carlo including importance sampling and the Metropolis algorithm.   -          Game theory: non-cooperative game theory, the Prisoner’s dilemma.     Galaxies and Large Scale Structures:   This component is an introduction to the physics of galaxies and large scale structures in the Universe.  The observational evidence will be reviewed.     -          The Milky Way   -     The nature of galaxies   -     Evidence for dark matter   -     Galactic evolution   -     Galaxy clusters   -     Superclusters   -     Larger scale structures   -     The Great Attractor   -          Active Galaxies     Experimentation (Physics):   You will perform a selection of five general physics experiments of two sessions each.  You will produce 10 lab diary entries, a full report on one experiment, and make an oral presentation on one experiment.  You will receive detailed marking and feedback on how to improve the usefulness of these, to yourself and others.  Typical experiments include: Optical fibres, Vibration interferometry, Chaos, Chromatic resolving power of a spectrometer, Laser speckle, optical image processing, supernova burst decay, etc.

Electromagnetic Waves:   12 hours of lectures and tutorial periods.     Additional Mechanics:   12 hours of lecture classes.     Modelling Complex Systems:   The course is presented using uLearn, the university's e-learning system.  12 hours are scheduled for lecturer-assisted sessions.       Galaxies and Large Scale Structures:   12 hours of lectures and tutorial classes.     Experimentation (Physics):   10 four-hour laboratory sessions.

Electromagnetic Waves:   i.                Grant & Philips, Electromagnetism, Wiley.   ii.              Halliday, Resnick and Walker , Fundamentals of Physics, [Extended Fifth Edition], Wiley.     Additional Mechanics:   i.                T L Chow, Classical Mechanics, Wiley.     Modelling Complex Systems:   No single text covers all the material contained in this half-module, although many texts in the library explain the principles of one technique.  The following are suggested.     i.                Beltratti, Margarita and Terns, Neural networks for Economic and Financial Modelling, Thomson Computer Press. [for neural networks and genetic algorithms].   ii.              Frenkel and Smit, Understanding Molecular Simulation, Academic Press [for Monte Carlo Modelling].   iii.             Beale and Jackson, Neural Computing: an introduction, Institute of Physics Press   iv.            [for Neural Networks].   v.              Goldberg, Genetic Algorithms in Search, Optimisation and Machine Learning,   vi.            Addison-Wesley [for Genetic Algorithms].   vii.           Each month, the journal Physica A publishes articles using the techniques explored in this course.  Most do not require knowledge beyond an undergraduate level to be understood.   viii.         Lui Lam, Nonlinear Physics for beginners, World Scientific [for overview of typical Complex Systems and methods of their description].   ix.            Challet, Minority Games, Oxford University Press [for Game Theory].     Galaxies and Large Scale Structures:   i.                B W Carroll & D A Osterlie, An Introduction to Modern Astrophysics, Addision Wesley, 1996.     Experimentation (Physics):   Required Reading :   i.                Laboratory instruction sheets provided.   ii.               Physics Laboratory Handbook: Level 1, Physics Department.     Recommended Reading :   Squires, Practical Physics, McGraw Hill

August 2010.