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Advanced Computational Laboratory - PHY00029H

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  • Department: Physics
  • Module co-ordinator: Dr. Matt Hodgson
  • Credit value: 20 credits
  • Credit level: H
  • Academic year of delivery: 2022-23

Related modules

Pre-requisite modules

Co-requisite modules

  • None

Prohibited combinations


Module will run

Occurrence Teaching period
A Autumn Term 2022-23 to Summer Term 2022-23

Module aims

The Advanced Computational Laboratory

The Advanced Computational Laboratory runs in the Autumn, Spring and Summer terms. The laboratory gives students experience at solving advanced, research-style, computational problems based on current, hot-topic research areas and to extend their skills in computational modelling. In first part of the Autumn term, students will work in groups (of at least 3 students) to solve a larger computational challenge. They will be given an existing materials simulation program and will be required to use it to solve a materials design problem. They will need to determine how to use the capabilities of the software to address the physical problem, including possible extensions to the functionality of the simulation software, and design, perform and analyse appropriate computational experiments. Each student within the group will have their own task to accomplish, and the final stage of the project is writing a mini-report in the style of a short scientific paper and a brief presentation on the group's findings.

In the Spring term, students will work on a computational assignment (the 2D Ising model) and become familiar with this style of advanced computational experiment.

In the Summer term, the students will further develop their skills in advanced computational modelling with two experiments; the the tight-binding model applied to nanographene, and an experiment in another field of computational interest, such as machine learning.

Module learning outcomes

Advanced Computational Laboratory (Autumn and Spring terms)

The assessed component of the laboratory provides skills in

  • the design and successful coding of computer simulations based on advanced theoretical models and complex physical systems, such as the 2D Ising model, graphene nanostructures and in other systems, such as plasma simulation
  • analytical skills pertaining to the physical interpretation and validation of numerical results, i.e., accuracy, correctness and limitations of the simulation model
  • the use of external libraries, such as the LAPACK library eigensolver, and other advanced simulations codes (such as molecular dynamics simulations)
  • the testing of code within computational and numerical approximations, e.g., the application of the unit-cell approximation in numerical simulations and study of finite size effects, etc.
  • the study of physical phenomena within computational simulation, such as phase transitions, band gap formation, etc.
  • an introduction to the required formalism and methods for computational study of the systems, such as quantum mechanics to generate eigensolutions, and application of methods such as importance sampling and the Metropolis algorithm for studying stochastic processes
  • the design of experiments to investigate particular physics phenomena in computational simulation, such as in materials modelling
  • the design of the workflow and optimisation in the use of available resources
  • the analysis, design and interfacing of new and old code
  • the development of group-work skills pertaining to modern software development practices, including unit testing, integration testing and the use of version control software.
  • keeping a 'working' laboratory logbook, which is updated concurrently as the laboratory progresses (individually and as part of a group project)
  • extended, scientific report writing, literature research/comparison and critical assessment of the literature

For the Advanced Computational Laboratory, further information will be available in the laboratory handbook, and experiment scripts, provided on the VLE.

Module content

Please note, if students have not taken PHY00030I - Mathematics II, they should have taken an equivalent mathematics module.

Advanced Computational Laboratory (Autumn Term)

During the first part of the term, the students will work individually on the 2D Ising model experiment. From mid-term, the students will work in small groups on an extended simulation project.

The laboratory log-book will be assessed after the completion of each computational experiment (mid-term for the individual log-book, and end-of-term for the group log-book).

For the group component, there is also an extended abstract, which will be submitted for assessment at the end of the term.

For both experiments (individual and group work), the developed software (code) and associated software documentation will also be assessed.

Advanced Computational Laboratory (Spring Term)

Students will work individually on two experiments (nanographene tight-binding model and an experiment from another research area, such as plasma simulation).

The laboratory log-book will be assessed after the completion of each computational experiment (mid-term and end-of-term).

Students choose one of the computational experiments to write-up in the form of a laboratory dissertation (formal report) at the end of the term for assessment. The choice of experiment for the write-up can be the Ising Model from the Autumn term, or one of the two experiments from the Spring term [nanographene tight-binding model and the experiment from another research area, such as plasma simulation)].

For both experiments (individual and group work), the developed software (code) and associated software documentation will also be assessed.

For the Advanced Computational Laboratory, further information pertaining to the running of the laboratory and assessments will be made available in the laboratory handbook, experiment scripts, and assessment pro forma provided on the VLE.

Assessment

Task Length % of module mark
Essay/coursework
Dissertation		 N/A 40
Essay/coursework
Extended Abstract		 N/A 15
Essay/coursework
Log Book Marks		 N/A 45

Special assessment rules

Non-compensatable

Additional assessment information

For the Advanced Computational Laboratory, further information pertaining to assessments will be made available in the laboratory handbook, and assessment pro forma provided on the VLE, including the assessment breakdown for each lab-related assessment component, assessment criteria, as well as the submission/return-of-assessment deadlines within the laboratory timetable.

Reassessment

Task Length % of module mark
Essay/coursework
Dissertation		 N/A 40
Essay/coursework
Extended Abstract		 N/A 15
Essay/coursework
Log Book Marks		 N/A 45

Module feedback

Our policy on how you receive feedback for formative and summative purposes is contained in our Department Handbook.

Indicative reading

Reading list will be provided with the laboratory scripts at the point of starting each experiment.


The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.