The Advanced Computational Laboratory runs in Semester 1 of each academic cycle. It trains students at solving advanced computational problems based on current research areas including ‘hot-topics’. It consists of 3 experiments through which the students extend their computational modelling skills and apply their problem-solving skills to the computational and scientific challenges each experiment contains. Experiments have guiding scripts, but are all open-ended leaving students with the possibility of pursuing their own scientific curiosity. Challenges include mastering the given software and or writing own codes to solve the problems proposed; learning to professionally keep laboratory log books; understanding of mathematical models; writing a full-fledged report in the style of a scientific article.
All experiments require to design, perform and analyse computational experiments. Previous computational experience is necessary for this course together with an appropriate level of knowledge of a computational language. No computational language or coding basics is taught during this course.
Pre-requisite modules
- None
Co-requisite modules
- None
Prohibited combinations
Prereqs: (New modules) Advanced Mechanics, Computational Laboratories & Skills or equivalent
Occurrence | Teaching period |
---|---|
A | Semester 1 2024-25 |
The Advanced Computational Laboratory runs in Semester 1 of each academic cycle. It trains students at solving advanced computational problems based on current research areas including ‘hot-topic’. It consists of 3 experiments through which the students extend their computational modelling skills and apply their problem-solving skills to the computational and scientific challenges each experiment contains. Experiments have guiding scripts, but are all open-ended leaving students with the possibility of pursuing their own scientific curiosity. Currently, one of the experiments sees the students working in small groups to solve a material design problem using an existing materials simulation programme. Challenges include mastering the given software to address the physical problem and writing a mini-report in the style of a long scientific abstract. The other two experiments are pursued individually: solving the two-dimensional Ising model and a machine-learning problem. Challenges include writing own codes to solve the problems proposed and learning to professionally keep laboratory log books. In one of the experiment students will learn to use a mathematical model, the tight-binding model, to model graphene nanoribbons. Challenges include the study and understanding of this mathematical model, coding, and writing a full-fledged report in the style of a scientific article.
All experiments require to design, perform and analyse computational experiments. Previous computational experience is necessary for this course together with an appropriate level of knowledge of a computational language. No computational language or coding basics is taught during this course.
Task | % of module mark |
---|---|
Essay/coursework | 40 |
Essay/coursework | 15 |
Essay/coursework | 45 |
Non-compensatable
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.
Task | % of module mark |
---|---|
Essay/coursework | 40 |
Essay/coursework | 45 |
'Feedback’ at a university level can be understood as any part of the learning process which is designed to guide your progress through your degree programme. We aim to help you reflect on your own learning and help you feel more clear about your progress through clarifying what is expected of you in both formative and summative assessments.
A comprehensive guide to feedback and to forms of feedback is available in the Guide to Assessment Standards, Marking and Feedback. This can be found at: https://www.york.ac.uk/students/studying/assessment-and-examination/guide-to-assessment/
The School of Physics, Engineering & Technology aims to provide some form of feedback on all formative and summative assessments that are carried out during the degree programme. In general, feedback on any written work/assignments undertaken will be sufficient so as to indicate the nature of the changes needed in order to improve the work. Students are provided with their examination results within 25 working days of the end of any given examination period. The School will also endeavour to return all coursework feedback within 25 working days of the submission deadline. The School would normally expect to adhere to the times given, however, it is possible that exceptional circumstances may delay feedback. The School will endeavour to keep such delays to a minimum. Please note that any marks released are subject to ratification by the Board of Examiners and Senate. Meetings at the start/end of each semester provide you with an opportunity to discuss and reflect with your supervisor on your overall performance to date.
Our policy on how you receive feedback for formative and summative purposes is contained in our Physics at York Taught Student Handbook.
Laboratory Manual; Laboratory Scripts; Scientific literature as appropriate to the proposed experiments