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Advanced Mechanics, Computational Laboratories & Skills - PHY00052I

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

Module summary

Advanced Mechanics:

Classical mechanics describes the universe on a scale ranging from the motion of galaxies to the trajectories of atoms. In the advanced mechanics part of this module, we introduce the Lagranigian approach to classical mechanics, which allows a system’s equations of motion to be determined entirely from its kinetic and potential energies via ‘the principle of least action’ – arguably the most fundamental law of physics.

Computational Laboratory

This module builds on the skills acquired in the “Mathematics, Professional Skills & Laboratories for TP” to further develop the core competencies required of a theoretical physicist. In addition, the experiments will support topics in the Stage 2 lectures, which will help to reinforce ideas presented in these modules. More advanced simulation techniques and tools will be introduced during this semester. One of the experiments will be written up as a formal report to further develop scientific communication skills.

Professional Skills:

The Professional Skills component of the module is aimed at building on previous translational and employability skills learned in Stages 1 and 2, to continue the development of career preparedness and enhancing recruitability.

Related modules

Pre-requisites: Mathematics, Professional Skills & Computational Laboratories or equivalent and Mathematical, Computational & Professional Skills 2 or equivalent

Co-requisites: Prohibited Combinations: Advanced Mechanics, Physics Laboratories & Skills, Advanced Mechanics, Astrophysical Laboratories & Skills

Module will run

Occurrence Teaching period
A Semester 2 2024-25

Module aims

Advanced Mechanics:

The aim of the advanced mechanics part of this module is to provide an introduction to more advanced approaches to classical mechanics. Via the Lagrangian approach, we consider the dynamics of rigid bodies, building on material covered in Stage 1, and we derive Kepler’s laws. We will study Hamilton’s principle and link the concepts introduced to the Hamiltonian (central to quantum mechanics).

Professional Skills:

The aim of the Professional Skills part of this module is to continue the development of career preparedness and enhance recruitability skills. Emphasis will be placed on group-based work, understanding recruitment processes, and developing interview skills and techniques. The python programming skills learned in Stage 1 and in the first semester of Stage 2 will be used to solve and model physical systems linked to content in the Stage 2 core modules.

Computational Laboratory:

Computational physics is the third way of studying physics and is in addition to (and complementary with) theoretical and experimental physics. In this part of the module, you will develop the skills learned in “Mathematics, Professional Skills & Laboratories for TP” to study more demanding physics situations. You will also learn more advanced coding techniques, and how to use more advanced computational physics tools.

Module learning outcomes

Advanced Mechanics:

  • Derive Lagrange’s equations via the principle of least action (Hamilton’s principle) and use them to describe a range of physical systems

  • Understand how conservation laws are derived and used within Lagrangian mechanics, such as the conservation of total energy via the Hamiltonian.

Professional Skills:

  • Understand the steps involved in a recruitment process, and know how to prepare for and conduct effective interviews.

  • Absorb, organise and synthesise information from different fields and use critical skills to provide coherent answers to open-ended and general questions.

  • Construct coherent arguments and discussions of broad questions supported by fact, theory and speculation.

  • Select and adapt communication styles to convey information and ideas in an appropriate way.

  • Create and implement plans to achieve key career objectives.

  • Write and develop mathematical algorithms in python to model and solve physical problems linked to Stage 2 modules.

Computational Laboratory:

  • Write an appropriate computer program to simulate a physical system

  • Plan and execute computational experiments, and then interpret and critically assess the results

  • Test and verify the accuracy and correctness of a simulation

  • Use 3rd party libraries to extend the functionality and efficiency of a program

  • Present and communicate computational results.

Module content

Advanced Mechanics:

  • The Lagrangian is defined and used to derive Lagrange’s equations for any coordinate system via the principle of least action (Hamilton’s Principle)

  • A general approach to determining conserved physical quantities is studied (Noether’s theorem)

  • The Lagrangian approach to classical mechanics is applied to a range of physical scenarios utilising conserved quantities to find a description of the system’s dynamics.

Professional Skills:

Career preparedness, recruitability, interview skills and techniques, recruitment processes and team activities. Programming in python, making use of python libraries and packages.

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.

Assessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Advanced Mechanics, Computational Laboratories & Skills		 1 hours 20
Essay/coursework
Python Programming Assignment		 N/A 10
Essay/coursework
Advanced Mechanics Practice Questions		 N/A 5
Essay/coursework
Formal Report		 N/A 25
Essay/coursework
Laboratory ELOG		 N/A 25
Essay/coursework
Skills Assignment		 N/A 15

Special assessment rules

Non-reassessable & Non-compensatable

Reassessment

Task Length % of module mark
Closed/in-person Exam (Centrally scheduled)
Advanced Mechanics, Computational Laboratories & Skills		 1 hours 20
Essay/coursework
Professional Skills Assignments		 N/A 15
Essay/coursework
Python Programming Assignment		 N/A 10
Essay/coursework
Single Experiment with ELOG and Formal Report		 N/A 50

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

Advanced Mechanics

  1. Classical Mechanics: The Theoretical Minimum Book by George Hrabovsky and Leonard Susskind

  2. Foundations of mechanics Book by Ralph Abraham

  3. Mechanics Book by Lev Landau

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


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.