Unit outline_

# MATH2921: Vector Calculus and Differential Eqs (Adv)

## Overview

This is the advanced version of MATH2021, with more emphasis on the underlying concepts and mathematical rigour. The vector calculus component of the course includes: parametrised curves and surfaces, vector fields, div, grad and curl, gradient fields and potential functions, Lagrange Multiplier Method, line integrals of different types (arc length, work, etc.), conservative fields, double and triple integrals, change of variable formulas, polar, cylindrical and spherical coordinates, areas, volumes and mass, flux integrals, and Green's Gauss' and Stokes' Theorems. The Differential Equations component of the course focuses on ordinary and partial differential equations (ODEs and PDEs) with applications with more complexity and depth. It provides a more thorough grounding in these techniques to enable students to build on the concepts in their subsequent courses. The main topics are: first and second order ODEs (including inhomogeneous equations), series solutions near a regular point, higher order ODEs and systems of first order equations, matrix equations, various methods (variation of parameters, undetermined coefficients, reduction of order), an introduction to PDEs, and first methods of solutions (including separation of variables, and Fourier Series). It could extend to the Laplace and Fourier Transform and elementary Sturm-Liouville Theory.

### Unit details and rules

Academic unit Mathematics and Statistics Academic Operations 6 ([(MATH1961 or MATH1971 or (a mark of 65 or above in MATH1061)) and (MATH1962 or MATH1972 or (a mark of 65 or above in MATH1062))]) or ([(MATH1921 or MATH1931 or MATH1901 or MATH1906) or (a mark of 65 or above in MATH1021 or MATH1001)] and [MATH1902 or (a mark of 65 or above in MATH1002)] and [(MATH1923 or MATH1933 or MATH1903 or MATH1907) or (a mark of 65 or above in MATH1023 or MATH1003)]) None MATH2021 or MATH2065 or MATH2965 or (MATH2061 and MATH2022) or (MATH2061 and MATH2922) or (MATH2961 and MATH2022) or (MATH2961 and MATH2922) or MATH2067 None Yes

### Teaching staff

Coordinator Zhou Zhang, zhou.zhang@sydney.edu.au Zhou Zhang

## Assessment

The census date for this unit availability is 2 April 2024
Type Description Weight Due Length
Supervised exam

Final Exam
Supervised exam
50% Formal exam period 2 hours
Outcomes assessed:
Online Canvas Quiz in Weeks 2, 4, 6, 9 and 12 with 3% for each.
15% Multiple weeks 30 minutes
Outcomes assessed:
Assignment Assignment
10% Week 05
Due date: 24 Mar 2024 at 23:59
2 weeks
Outcomes assessed:
Small test Quiz 1
Quiz in Practice Class
10% Week 07
Due date: 11 Apr 2024 at 13:00
40 minutes
Outcomes assessed:
Small test Quiz 2
Quiz in Practice Class
10% Week 11
Due date: 09 May 2024 at 13:00
40 minutes
Outcomes assessed:
Attendance Tutorial Attendance
0.5 mark for every tutorial class attendance, up to 5 marks (for 10 times)
5% Weekly Weeks 2-13
Outcomes assessed:

### Assessment summary

Assignment: require students to integrate information from lectures and practice classes to create a concise written argument. Test your understanding of material covered in the vector calculus and differential equations components of the course.

Final Exam: cover all material in the unit from lectures, tutorials and practice classes. The final exam os compulsary. Not attending the final exam will result in an absent fail (AF) grade.

Replacement Final Exam: if a second replacement exam is required, this exam may be delivered via an alternative assessment method, such as a viva voce (oral exam). The alternative assessment will meet the same learning outcomes as the original exam. The format of the alternative assessment will be determined by the unit coordinator.

### Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

Representing complete or close to complete mastery of the material

Distinction

75 - 84

Representing excellence, but substantially less than complete mastery

Credit

65 - 74

Representing a creditable performance that goes beyond routine knowledge and understanding, but less than excellence

Pass

50 - 64

Representing at least routine knowledge and understanding over a spectrum of topics and important ideas and concepts in the course.

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

### Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

• Deduction of 5% of the maximum mark for each calendar day after the due date.
• After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Assignment: for late submission, every day (after due time) costs 20% of the original weight. In-Class and canvas Quizzes: no late submission or replacement quiz will be accommodated. The weight can be moved to Final Exam after successful application through the University. Final Exam: subject to the university policy.

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

## Learning support

### Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

### Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

### Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

### Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)

## Weekly schedule

WK Topic Learning activity Learning outcomes
Multiple weeks Review of partial differentiation techniques. Gradients, maxima, and minima, curves in space and the plane and the chain rule Lecture and tutorial (8 hr)
Multiple integration and their computation both in Euclidean and transcribed coordinates. Lecture and tutorial (8 hr)
Line integration and the main theorems of vector calculus Lecture and tutorial (8 hr)
Review of linear second order ordinary differential equations, methods for solving them and their applications Lecture and tutorial (8 hr)
Generalisation of the methods from second order linear equations to higher order equations. Lecture and tutorial (8 hr)
Advanced methods for solving linear ODEs. Lecture and tutorial (8 hr)
Fourier Series and applications to solving classical boundary value problems and PDEs Lecture and tutorial (8 hr)
Weekly Demonstration of interesting problems relating to the course material using the computer software package Mathematica Lecture and tutorial (11 hr)

### Attendance and class requirements

Lecture/practice class attendance is strongly recommended but not counted directly in marks.

Tutorial class attendance is part of the assessment.

### Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

The unit will be based on a mixture of typed and (in-class) handwritten lecture notes provided throughout the semester. All lecture notes from Year 2022 will be provided at the beginning of the semester.

The following references are recommended but not required. All references for this unit can be accessed through the Library eReserve, available on Canvas.

• Textbook: Calculus III, by Jerrold Marsden and Alan Weinstein. Undergraduate Texts in Mathematics. Springer-Verlag, New York. 1985.
• Textbook: Elementary Differential Equations with Boundary Value Problems, by William F. Trench. Free Online edition 1.01 December 2013.

## Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

• LO1. Demonstrate a conceptual understanding of vector-valued functions, partial derivatives, curves and integration over a region, volume and surface as well as solving basic differential equations with a background in a variet of techniques and applications of mathematical analysis.
• LO2. Understand the definitions, main theorems, propositions, lemmata and corollaries for multivariate calculus as well as their applications to science. Also understand and the main theorems and methods of solving elementary linear differential equations as well as the applications.
• LO3. Be fluent in the computation of integrals via substitution and coordinate transform methods.
• LO4. Develop an appreciation and strong working knowledge of the theory and applications of elementary vector analysis and differential equations.
• LO5. Be fluent with important examples, theorems and applications and able to implement these in some computational supporting tool.
• LO6. Present complete and mathematically rigorous solutions for problems in vector calculus and differential equations that include appropriate justification for their reasoning.
• LO7. Recognise problems in mathematics and other areas of science and engineering that are amenable to mathematical analysis, and to apply the techniques of mathematical analysis in solving them.

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

 GQ1 Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline. GQ2 Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem. GQ3 Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context. GQ4 Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies. GQ5 Inventiveness Generating novel ideas and solutions. GQ6 Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues. GQ7 Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries. GQ8 Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context. GQ9 Influence Engaging others in a process, idea or vision.

### Outcome map

GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

## Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

The assessment structure remains the same, with name and type revised according to university/faculty policy. It might be considered as "minor change".

### Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

General Laboratory Safety Rules

• No eating or drinking is allowed in any laboratory under any circumstances
• A laboratory coat and closed-toe shoes are mandatory