Accessibility statement

Mathematics, Professional Skills & Experimental Laboratories - PHY00049I

« Back to module search

  • Department: Physics
  • Module co-ordinator: Prof. Erik Wagenaars
  • Credit value: 20 credits
  • Credit level: I
  • Academic year of delivery: 2024-25

Module summary

This module is aimed at building on the skills learned in the Stage 1 laboratory modules to further develop the core experimental competencies required of a physicist. In addition, the experiments will support topics in the Stage 2 lectures, which will help to reinforce ideas presented in these modules.

A series of physics experiments and laboratory skills activities will be performed throughout the semester. One of the experiments will be written up as a formal report to develop scientific communication skills.

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.

Related modules

Prohibited Combinations: Mathematics, Professional Skills & Introduction to 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:

This module builds on the knowledge gained in the Stage 1 lectures and the skills learned in the Stage 1 laboratory. This module aims to increase the level of sophistication in the experiments, approach to data analysis, and laboratory report writing. There is emphasis on the use of and critical evaluation of modern (computer-based) instrumentation. Typical experiments will take 2 full days to complete and a series of such experiments will be undertaken throughout the semester. This is complemented with laboratory skills sessions, for instance formal report writing

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:

  • Develop, reflect on, and critically evaluate key professional attributes sought after by graduate employers.

  • Enhance your employability and self-awareness, and boost application skills through effective communication of information and ideas.

  • Create and implement plans to achieve key career objectives, and identify ways to make professional use of others to achieve aims and desired outcomes.

  • Identify, reflect on and critically evaluate key competencies and strengths, produce a CV and application letter aligned to a potential sector.

  • Make effective use of databases to identify, select, and evaluate information to enable achievement of a desired outcome.

  • Respond appropriately to peer expectations.

  • Make use of python libraries and develop algorithms in python to solve physical problems linked to Stage 2 modules.

Laboratories:

  • Plan and execute experiments over an extended time, using a range of experimental techniques and appropriate data analysis and processing methods.

  • Identify and assess experimental errors and to critically analyse and discuss experimental results.

  • Present and communicate experimental results.

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.

Laboratories:

Lab scripts for each experiment will be provided.

Guidance for notebook keeping and formal report writing will be provided.

Assessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Mathematics, Professional Skills & Experimental Laboratories		 1 hours 20
Essay/coursework
Formal Report		 N/A 20
Essay/coursework
Laboratory Notebook		 N/A 30
Essay/coursework
Maths Practice Questions		 N/A 5
Essay/coursework
Professional Skills Assignments		 N/A 15
Essay/coursework
Python Programming Assignment		 N/A 10

Special assessment rules

Non-reassessable & Non-compensatable

Reassessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Mathematics, Professional Skills & Experimental Laboratories		 1 hours 20
Essay/coursework
Laboratory Experiment		 N/A 50
Essay/coursework
Professional Skills Assignment		 N/A 15
Essay/coursework
Python Programming Assignment		 N/A 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:

  1. Introduction to Linear Algebra, 3rd Edition Textbook by Gilbert Strang

  2. 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


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.