Studying at York
(TR) Mathematics, Professional Skills & Computational Laboratories - PHY00045I
- Department: Physics
- Credit value: 20 credits
- Credit level: I
- Academic year of delivery: 2023-24
Module summary
N/A - transition module
Related modules
Pre-requisites: Mathematics, Professional Skills & Laboratories or equivalent
Prohibited Combinations: Different streams of the same module for Experimental or Introductory labs
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 1 2023-24 |
Module aims
Mathematics:
Mathematics is a fundamental tool for the study of Physics. This mathematics part of this module aims to introduce the concepts of vector and scalar fields and how to apply calculus to these fields in order to describe their behaviour and dynamics. We also study Fourier series, which leads to the concept of the ‘Fourier transform’, both of which are powerful and ubiquitous concepts in physics.
Professional Skills:
Professional skills are essential to the modern physicist. The Professional Skills component of this module is aimed at building on previous translational and employability skills learned in Stage 1 to continue the development of career preparedness and enhancing recruitability. Emphasis will be placed on the design and development of application documents including CVs and cover letters, the use of online resources to find graduate roles, and recognition of the skills, knowledge and attributes gained to make informed career choices.
Computational Laboratory:
Computational physics is the third way of studying physics and is in addition to (and complementary with) theoretical and experimental physics. Computer programs model the real world using theoretical ideas cast into mathematical form and then converted into an algorithm. This algorithm is expressed in a high level programming language, and this is then run on the computer. The analysis and development of the results is closely akin to experiment, in that input (independent) quantities may be varied and the change in the output (dependent) quantities are found. Hence a simulation is the representation of an individual experiment, and may be used to give a prediction of the results of that experiment, if the model is accurate. Such simulation may be considerably easier /quicker / cheaper to perform than the equivalent experiment, and may also yield fresh insight and understanding into the results of the experiment. That is why computational physics has become essential to many modern research fields. The techniques of computational physics embrace model design, numerical analysis, computer programming and experimentation. This laboratory is designed to help you to develop these essential skills.
Module learning outcomes
Mathematics:
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Describe the rate at which scalar and vector fields change in an arbitrary direction and use this concept to calculate the flux of fields through and around regions of space
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Define a Fourier series of any periodic function and use it to derive the Fourier transform.
Professional Skills:
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Develop, reflect on, and critically evaluate key professional attributes sought after by graduate employers.
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Enhance your employability and self-awareness, and boost application skills through effective communication of information and ideas.
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Create and implement plans to achieve key career objectives, and identify ways to make professional use of others to achieve aims and desired outcomes.
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Identify, reflect on and critically evaluate key competencies and strengths, produce a CV and application letter aligned to a potential sector.
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Make effective use of databases to identify, select, and evaluate information to enable achievement of a desired outcome.
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Respond appropriately to peer expectations.
Computational Laboratory:
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Write an appropriate computer program from a description of the core physics ideas and algorithms
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Plan and execute computational experiments, and then interpret the results
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Test and verify the correctness of a simulation
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Present and communicate computational results.
Module content
Mathematics:
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Scalar and Vector Fields: Rate of change of a scalar field, conservative fields, work done by moving through a vector field, flux of a vector field, divergence theorem, curl of a vector field, Stokes’ theorem, Laplace operator, div, grad and curl in different coordinate systems and surface integrals of vector fields
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Fourier Series: Fourier theorem and Fourier series, boundary conditions, Fourier coefficients, waveforms, Fourier transforms, reciprocal broadening.
Professional Skills:
Professional Skills: Application writing, CVs, cover letters, application forms, search engines, online resources, recognition and reflection of professional skills, peer-assessment, team activities.
Laboratories:
Lab scripts for each computational experiment will be provided.
Regular briefing sessions throughout the semester will introduce new computational tools and techniques.
Guidance for notebook keeping and formal report writing will be provided.
Of the 50% weighting for the laboratory component, 25% is attributed to the eLog laboratory notebooks and 25% to the formal report.
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 25 |
| Essay/coursework | 50 |
| Essay/coursework | 10 |
| Essay/coursework | 15 |
Special assessment rules
Other
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 25 |
| Essay/coursework | 50 |
| Essay/coursework | 15 |
Module feedback
'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.
Indicative reading
Mathematics:
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Vector Calculus Book by P. C. Matthews
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Mathematical Methods in the Physical Sciences Textbook by Mary L. Boas
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A Student's Guide to Fourier Transforms: With Applications in Physics and Engineering Book.
Professional Skills:
John M. Lannon & Laura J. Gurak: Technical Communication, Global Edition. 15th Ed 2021 (Pearson)
Laboratories:
Lab scripts and specific skills guides will be available on the VLE