Studying at York
Mathematics, Professional Skills & Introduction to Laboratories - PHY00050I
- Department: Physics
- Credit value: 20 credits
- Credit level: I
- Academic year of delivery: 2024-25
Module summary
The mathematics part of this module builds on your knowledge from Stage 1. Mathematics is an essential tool for any physicist; in this course you will learn advanced linear algebra in its matrix form, which will allow you to solve advanced problems in quantum mechanics and beyond.
The accompanying laboratory sessions will build your practical experimental skills as well as help you understand how data analysis and record-keeping can aid your growth as a professional physicist
Related modules
Prohibited Combinations: Mathematics, Professional Skills & Experimental Laboratories and Mathematics, Professional Skills & Computational Laboratories
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 1 2024-25 |
Module aims
Mathematics:
Mathematics is a fundamental tool for studying and understanding Physics. The aim of the mathematics part of this module is to introduce linear algebra in its matrix form, which can be used to solve complex problems in an elegant and efficient way, e.g. in quantum mechanics.
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.
The python programming skills learned in Stage 1 will be used to further develop programming techniques and these will be applied to physical problems linked to the core modules in Stage 2.
Laboratories:
The introductory laboratory course is aimed at building on the skills learned at school or college by developing the core experimental competencies required of a physicist. In addition, the experiments will support topics discussed in lectures, which will help to reinforce ideas presented in these modules. You will learn how to use equipment which plays a key role in a wide range of experiments.
Module learning outcomes
Mathematics:
-
Apply linear algebra in its matrix form to solve a range of problems, from simultaneous equations to determining eigenvectors and eigenvalues.
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.
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Make use of python libraries and develop algorithms in python to solve physical problems linked to Stage 2 modules.
Laboratories:
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Demonstrate effective experimental practice, including the planning, execution, recording, appraisal and discussion of the data
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Identify, assess, analyse, and decrease experimental uncertainties, applying the properties of the normal distributions where appropriate
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Write a scientific report using the accepted structure and style
Module content
Mathematics:
Linear Algebra: Matrix algebra and solving simultaneous equations. Rank, ill-conditioning, linear dependence, diagonalisation, eigenvectors and eigenvalues, Hermitian, Unitary and Normal matrices, transformation matrices.
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. Programming in python, making use of python libraries and packages.
Laboratory:
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Methods for plotting experimental data
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Properties of Normal distributions and the standard error
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Identification, analysis and minimisation of experimental uncertainties
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Experimental activities based around provided laboratory scripts
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Maintenance of a laboratory notebook
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Scientific report writing
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 20 |
| Essay/coursework | 0 |
| Essay/coursework | 50 |
| Essay/coursework | 5 |
| Essay/coursework | 15 |
| Essay/coursework | 10 |
Special assessment rules
Other
Additional assessment information
Our accreditation by the Institute of Physics requires that students demonstrate a minimum standard of laboratory work. Therefore the laboratory component mark cannot be compensated by the marks achieved in other components. If a pass is not achieved at the first attempt, a resit lab must be attended; a new experiment will be undertaken, both the lab notebook and formal report must be repeated and a pass achieved in order to meet the progression requirements.
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 20 |
| Essay/coursework | 0 |
| Essay/coursework | 50 |
| Essay/coursework | 15 |
| Essay/coursework | 10 |
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:
-
Introduction to Linear Algebra, 3rd Edition Textbook by Gilbert Strang
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Mathematical Methods in the Physical Sciences Textbook by Mary L. Boas
Professional Skills:
John M. Lannon & Laura J. Gurak: Technical Communication, Global Edition. 15th Ed 2021 (Pearson)
Laboratories:
Lab scripts - available on the VLE