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ACM30020

Academic Year 2024/2025

Applied Analysis (ACM30020)

Subject:
Applied & Computational Maths
College:
Science
School:
Mathematics & Statistics
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Assoc Professor Lennon Ó Náraigh
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

The purpose of this course is to learn a variety of mathematical methods for deriving useful approximate solutions of the differential equations and integrals found in the Mathematical Sciences. The course will be structured as follows:

1. Existence and uniqueness results for ordinary differential equations: The Lipschitz condition and Picard’s theorem. Comparison theorems.
2. Integral Equations: The Volterra integral equation and initial value problems, the Fredholm integral equation and boundary value problems.
3. Sturm-Liouville Theory: The adjoint differential operator, the Sturm-Liouville problem, basic properties of a Sturm-Liouville eigenvalue problem, unboundedness of the eigenvalues, completeness in the appropriate sense of the set of eigenfunctions
4. Theory of Infinite-dimensional vector spaces: Inner product spaces, complete metric spaces, Hilbert spaces, square summable series and square integrable functions

About this Module

Learning Outcomes:

On completion of this module students should be able to:

1. Understand conditions guaranteeing existence and uniqueness results for ordinary differential equations and recognize examples where those conditions do not hold;
2. State and prove Picard’s theorem;
3. Transform between an initial value problem and the corresponding Volterra integral equation;
4. Transform between a boundary value problem and the corresponding Fredholm integral equation;
5. State the axiomatic properties of the Green function for a second order initial value problem and boundary value problem;
6. Understand the concept of the adjoint differential operator;
7. Recognise a Sturm-Liouville eigenvalue problem and prove the basic properties of eigenvalues and eigenfunctions;
8. Understand the fundamental properties of infinite-dimensional vectors spaces;
9. Understand the application of these techniques to standard problems in Applied Mathematics.

Student Effort Hours:
Student Effort Type Hours
Lectures

36

Specified Learning Activities

24

Autonomous Student Learning

40

Total

100


Approaches to Teaching and Learning:
Lectures, tutorials, enquiry and problem-based learning.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): In-depth assignment linking lecture notes to key skills such as solving mathematical problems, proving theorems, writing up results clearly, etc. Week 10 Standard conversion grade scale 40% No
20
No
Exam (In-person): Final exam to assess all the learning outcomes of the module End of trimester
Duration:
2 hr(s)
Standard conversion grade scale 40% No
80
No

Carry forward of passed components
No
 

Resit In Terminal Exam
Autumn Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Fri 15:00 - 15:50
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Mon 13:00 - 13:50
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 32, 33 Wed 12:00 - 12:50
Spring Lecture Offering 1 Week(s) - 31 Wed 12:00 - 12:50