PHYS4015: Semester 2, 2025

Units PHYS4015 Semester 2 2025 [Normal day]

Unit outline_

PHYS4015: The Physics of Complex Systems

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Complex systems are pivotal in understanding phenomena that transcend the capabilities of their individual components. This field studies diverse systems characterized by intricate interactions and dependencies, leading to novel behaviours such as self-organization and emergence. These phenomena are not predictable by examining the components alone. This unit offers a deep dive into the fundamental physics of complex systems, focusing on their dynamics, structure, and the governing principles of their behaviour. It provides a thorough introduction to key concepts in complex systems, including chaos, self-organized criticality, synchronization, and pattern formation outside of equilibrium. These concepts are crucial for understanding the complex and emergent behaviours observed across various systems. Additionally, this course applies complex systems theory to two cutting-edge fields: neuroscience and artificial intelligence (AI). In neuroscience, modelling the brain's complex systems enhances our understanding of how perception and cognition emerge from neural circuits. In AI, applying principles of complex systems can improve our understanding and enhance the efficacy of deep learning networks. Students in this course will develop skills in modelling, quantitative analysis, and critical thinking. These skills are vital for dissecting complex systems in both academic research and practical applications, preparing students to address challenges in advanced scientific and technological fields.

Unit details and rules

Academic unit	Physics Academic Operations
Credit points	6
Prerequisites ?	144 credit points of units including (MATH1X01 or MATH1X21 or MATH1906 or MATH1931) and MATH1X02
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	First- and second-year physics
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Pulin Gong, pulin.gong@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Out-of-class quiz	Final exam B “Record+” Taken online	50%	Formal exam period	2 hours	AI allowed
Outcomes assessed:
Out-of-class quiz	mid-semester test 48 hours includes reading time Upload time not included in reading	10%	Week 08 Due date: 26 Sep 2025 at 18:00	2 hours	AI allowed
Outcomes assessed:
Written work	Project Assignment This is a project-based exam and students need to write a report.	40%	Week 10 Due date: 18 Oct 2025 at 18:00 Closing date: 01 Nov 2025	4000 words.	AI allowed
Outcomes assessed:

Assessment summary

The final exam is worth 50% and tests all basic concepts and models covered in the lectures. The project assignment is worth 40%; students need to work on a research project and write a report. The mid-semester test is worth 10% and tests models of neural dynamics. Detailed information for each assessment can be found on Canvas.

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.

The final exam is compulsory. Failure to submit will result in an absent fail grade (AF) for the unit.

Assessment criteria

Project Assignment 40%

Mid-semester test 10%

Final exam 50%

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 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. 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)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity	Learning outcomes
Weekly	Basic models of neural dynamics and functions. Neural oscillations and synchronization. Models of synaptic dynamics.	Lecture (2 hr)

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.

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.

Outcomes
Graduate qualities

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

LO1. Demonstrate an understanding of key concepts in neural dynamics and computation.
LO2. Apply these concepts to develop models, and to solve qualitative and quantitative problems in scientific contexts, using appropriate mathematical and computing techniques as necessary.
LO3. Design brain-inspired algorithms to solve problems.
LO4. Develop models to explain neurophysiological and/or psychophysical data.
LO5. Communicate scientific information appropriately, through written work.
LO6. Analyse the dynamical process of brain functions such as decision making and develop appropriate quantitative methods for solving them.
LO7. Demonstrate a sense of responsibility, ethical behaviour, and independence as a learner and as a scientist.

Graduate qualities

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

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

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

No changes have been made since this unit was last offered.

Additional information

EQUITY, ACCESS AND DIVERSITY STATEMENT

The School of Physics recognises that biases, bullying and discrimination, including but not limited to those based on gender, race, sexual orientation, gender identity, religion and age, continue to impact parts of our community disproportionately. Consequently, the School is strongly committed to taking effective steps to make our environment supportive and inclusive and one that provides equity of access and opportunity for everyone.

The School has three Equity Officers as a point of contact for students who may have a query or concern about any issues relating to equity, access and diversity. If you feel you have been treated unfairly, discriminated against, bullied or disadvantaged in any way, you are encouraged to talk to one of the Equity Officers or any member of the Physics staff.

More information can be found at https://sydney.edu.au/science/schools/school-of-physics/equity-access-diversity.html

Any student who feels they may need a special accommodation based on the impact of a disability should contact Disability
Services: https://sydney.edu.au/study/academic-support/disability-support.html who can help arrange support.

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
Closed-toe shoes are mandatory
Follow safety instructions in your manual, posted in laboratories, and from staff.
In case of fire, follow instructions posted outside the laboratory door
First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory
As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

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Useful links