Registry

Module Specifications

Archived Version 2015 - 2016

Module Title
Module Code
School
Online Module Resources
NFQ level	9	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

This module introduces research students to the concepts and techniques of computational physics, in the context of studies in physical sciences or nearby fields. In particular, students should understand that the method proceeds by (i) identifying a suitable physical model expressed in mathematical terms, (ii) finding an algorithm by which the model can be solved, (iii) implementing the solution, and (iv) calculating the desired results. In addition to this basic approach, the module will also discuss modern ideas about the challenges of establishing that the correct solution has been found, and the opportunities and difficulties of exploiting high performance computer hardware for large scale problems.

Learning Outcomes

1. Develop and articulate a systematic understanding of knowledge at, or informed by, the forefront of research both qualitatively, and quantitatively of the fundamental and underpinning elements of the computational approach
2. Demonstrate this systematic understanding by developing and articulating a mathematical model in a form suitable for computational solution
3. Select from complex and advanced techniques across this field of learning to identify suitable tools for generating the computational solution (e.g. algorithms, computer languages, hardware)
4. Demonstrate this systematic understanding and also demonstrate a critical awareness of the main issues and modern insights around establishing that the computed solutions are correct, based on modern ideas on verification and validation
5. Demonstrate a critical awareness of the challenges and opportunities of high performance computation for large scale problems

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	12	4 x 3 hour workshops
Lecture	12	12 x 1 hour meetings with supervisor to discuss critically and evaluate the approaches being taken to the various computational design and implementation assessment problems. The student will maintain a written record of these meetings and these will be submitted along with their solutions to the assessment problems.
Independent Study	101	Study for lectures (24 hours), preparation for, and documentation of, supervisor meetings (12 hours), work on design and implementation of computational solutions for assessment problems (problem 1 - 14 hours; problem 2 - 14 hours; problem 3 - 14 hours; problem 4 - 23 hours).
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Basic Concepts
General ideas on the role of computation in the physical sciences. The process of developing a computational model, from mathematical formulation to developing and testing the solution. Ideas about critical evaluation of solutions

Mathematical Models
Formulation of mathematical models, beginning with conceptualising a physical model and proceeding to a formal mathematical model, including identifying relevant boundary conditions and parameters

Computational Tools
Choosing a computational approach based on the mathematical character of the model. Algorithms for ordinary and partial differential equations. Monte Carlo methods

Software Tools
Computer languages for scientific problems. Libraries and other software packages.

Verification and Validation
Criticism of the computational approach. Recent ideas on establishing the correctness of scientific computations and physical models.

Assessment Breakdown
Continuous Assessment	%	Examination Weight	%

Type	Description	% of total	Assessment Date
Course Work Breakdown

Reassessment Requirement
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
Unavailable

Indicative Reading List

William H. Press... [et al.]: 2007, Numerical Recipes: The Art of Scientific Computing, Cambridge University Press, New York, 978-0521880688
William L. Oberkampf, Christopher J. Roy,: 2010, Verification and Validation in Scientific Computing, Cambridge, 9780521113601

Other Resources

None

Programme or List of Programmes

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