Course syllabus

Course-PM

FFR120 / FIM750 Simulation of complex systems lp2 HT22 (7.5 hp)

Course is offered by the Department of Physics

Contact details

Teacher

Main lecturer and examiner: Giovanni Volpe
Email: giovanni.volpe@physics.gu.se
Office address: Room S1019, Fysik Soliden

TAs homework correction

Aykut Argun, Agnese Callegari, Martin Selin, Harshith Bachimanchi, Vide Ramsten

Tutors projects

Martin Selin <martin.selin@physics.gu.se>, Harshith Bachimanchi <harshith.bachimanchi@physics.gu.se>, Agnese Callegari <agnese.callegari@physics.gu.se>, Vide Ramsten <vide.ramsten@physics.gu.se>

Course purpose

Much of modelling in the sciences focuses on simple models, highlighting key mechanisms using small sets of moving parts. However, in complex systems interesting features are often a direct result of having large sets of interacting particles or agents with different characteristics. This makes new tools a necessity. This course introduces simulation techniques frequently used in complex systems to handle models with many heterogeneous parts. Specifically, we will look at agent-based modelling, evolutionary game theory, cellular automata, and networks, with application to physics, biology and social sciences. We will also learn how to validate the outcomes of simulation models in order to reach scientifically sound conclusions.

Course literature

Textbook: Aykut Argun, Agnese Callegari & Giovanni Volpe. Simulation of Complex Systems. IOP Publishing, 2022.
The textbook is freely accessible in electronic format through Chalmers Library (link: https://www.lib.chalmers.se/)
Link to the IOP book webpage: https://iopscience.iop.org/book/mono/978-0-7503-3843-1 (you can download different formats: PDF, ePub3, Kindle).

Errata: http://softmatterlab.org/books/simulation-of-complex-systems/errata-book-simulation-of-complex-systems/

GitHub page: https://github.com/softmatterlab/SOCS

Course design and schedule

All lectures and homework corrections will take place in person in the respective classrooms.


Date, time & place	Topic	Readings / Materials to prepare	Additional readings
Tue Nov 1 9:00-9:45 HC2 10:00-10:45 HC4	Lecture 1 The role of simulations in the study of complex systems. Course information.
Fri Nov 4 9:00-9:45 HB1 10:00-10:45 HB1 11:00-11:45 HB1	Lecture 2 Molecular Dynamics Ising Model Questions Lecturers: Agnese Callegari, Aykut Argun	Read Chapters 1-2	Computer "Experiments" on Classical Fluids On the Theory of the Ising Model of Ferromagnetism
Fri Nov 4	Project groups announced	The project groups will be formed. You can propose your own groups with 4 or 5 students. The remaining students will be randomly assigned to groups on Fri Nov 4. Groups are strictly of 4 or 5 members, no groups of 2 or 3 students are allowed.
Tue Nov 8 9:00-9:45 HC2 10:00-10:45 HC3 11:00-11:45 HC3	Lecture 3 Forest Fires Game of Life Questions Lecturer: Agnese Callegari	Chapters 3-4	Self-organized criticality Cellular automata as models of complexity
Fri Nov 11 9:00-9:45 HB3 10:00-10:45 HA1 11:00-11:45 HA1	Lecture 4 Brownian Dynamics Anomalous Diffusion Questions Lecturer: Agnese Callegari	Chapters 5-6	Life at low Reynolds number Brownian motion in a speckle light field
Fri Nov 11 23:59	Project Proposal	Submit your project proposal by email to your tutor
~ Nov 14-21	1st meeting with tutor	Arrange a 45-minute meeting with tutor to discuss and receive feedback on the project idea and outline
Mon Nov 14 8:00-11:00 F-T7204	Exercise 1a Examination: Correction HW1.	Report HW1 Submit your Report HW1 before the correction
Tue Nov 15 9:00-9:45 HB1 10:00-10:45 HB4 11:00-11:45 HB4	Lecture 5 Multiplicative Noise Vicsek Model Questions Lecturer: Agnese Callegari	Chapter 7-8	Force measurement in the presence of Brownian noise The physics of the Vicsek model
Thu Nov 17 8:00-11:00 F-T7204	Exercise 1b Examination: Correction HW1.	Report HW1 Submit your Report HW1 before the correction
Fri Nov 18 9:00-9:45 HB1 10:00-10:45 HB1 11:00-11:45 HB1	Lecture 6 Living Crystals Sensorial Delay Questions Lecturer: Aykut Argun	Chapters 9-10	Sorting of chiral microswimmers Tuning phototactic robots with sensorial delays
Mon Nov 21 8:00-11:00 F-T7203	Exercise 2a Examination: Correction HW2.	Report HW2 Submit your Report HW2 before the correction
Tue Nov 22 9:00-9:45 HC2 10:00-10:45 HC4 11:00-11:45 HC4	Lecture 7 Disease Spreading Network Models Questions Lecturer: Agnese Callegari	Chapters 11-12	Improving epidemic testing and containment strategies using machine learning The structure and function of complex networks
Thu Nov 24 8:00-11:00 F-T7203	Exercise 2b Examination: Correction HW2.	Report HW2 Submit your Report HW2 before the correction
Fri Nov 25 9:00-9:45 HC3 10:00-10:45 HC2 11:00-11:45 HC2	Lecture 8 Evolutionary Games Ecosystems Questions Lecturer: Agnese Callegari	Chapters 13-14	The evolution of cooperation A simple, stable model of mutualism incorporating handling time
Fri Nov 25 23:59	Project report outline	Submit an outline of your project to your tutor
~ Nov 30-Dec 9	2nd meeting with tutor	Arrange a 45-minute meeting with tutor to discuss and get feedback on the progress of your project and its presentation
Mon Nov 28 8:00-11:00 F-T7203	Exercise 3a Examination: Correction HW3.	Report HW3 Submit your Report HW3 before the correction
Tue Nov 29 9:00-9:45 HC2 10:00-10:45 HC3 11:00-11:45 HC3	Lecture 9 Ant-Colony Optimization Sugarscape Questions Lecturer: Agnese Callegari	Chapters 15-16	Edge detection using ant algorithms Dynamic models of segregation
Thu Dec 1 8:00-11:00 F-T7204	Exercise 3b Examination: Correction HW3.	Report HW3 Submit your Report HW3 before the correction
Mon Dec 5 13:00-16:00 F-T7204	Exercise 4a Examination: Correction HW4.	Report HW4 Submit your Report HW4 before the correction
Thu Dec 8 8:00-11:00 F-T7204	Exercise 4b Examination: Correction HW4.	Report HW4 Submit your Report HW4 before the correction
Tue Dec 13 23:59	Project presentation	Submit your project presentation (8-minute video, format MOV)
Wed Dec 14 23:59	Draft of project report	Submit a draft of your project report to your tutor
Thu Dec 15 8:00-11:45 SB-H8 13:15:17:00 SB-H8	Project Presentation (Examination)	Presentation project Draft report project
Sun Jan 8 23:59	Project report	Submit your final project report to your tutor

Learning objectives and syllabus

Learning objectives:

-Describe the fundamental ideas behind the simulation methods discussed in the course.
-Implement simulation codes in each of the methods.
-Analyse and discuss the results of simulations.
-Plan, manage, execute and report a small-scale simulation project.

Link to the syllabus on Studieportalen:

Study plan

Link to the GU website:

https://utbildning.gu.se/kurser/kurs_information?courseid=FIM750

Examination form

There will be no written final examination in this course.

The examination consists of homework assignments and a project, each accounting for 50% of the final grade.

Homework information

The purpose of the homework problem sets is to provide you with hands-on experience of the material presented in the course. You are strongly encouraged to team up and collaborate on the homework, to ask your classmates if you are stuck at some point, and to assist classmates in need of advice. But you must write your own implementations, run your own simulations, and have your own work assessed. No late assignments will be accepted.

Grading: There are four homework sessions with each carrying a value of 25 points. A perfect score is therefore 100. The homework submissions account of 50% of your total course grade.

Note: A necessary (but not sufficient) requirement for passing grade is that 10 points are achieved in each homework.

Questions: After each lecture students have the possibility to ask questions on the homework problem set specific of that lecture. The question session will take place after each lecture.

Upload your report: You will have to upload the report for the homework before the correction. The report consists of a single PDF containing your code and the figures generated by the code. The assessment of your work happens during the lab hours.

Assessment: We will assess your work during lab hours. Be prepared for the assessment: Generate all your figures and/or videos up front. There will be no time for running simulations during assessment. Check that you have answered all questions carefully. You should be able to give reasoned answers regarding your modeling choices as well as being able to discuss the implications of your results. If you have worked together as a group, you're encouraged to have your assessment done together. You will still need to prepare your assignments individually, and will receive individual grades.

Project information

Modeling and simulation project

The purpose of the project work is to provide you with training in

Developing your own small research-style project.
Executing a collaborative project.
Presenting your independent work in writing and as a summary talk.

The deliverables are a 8 minute presentation + 10 minute questions (30% of project grade) and a written report (70% of project grade). The project will be presented to the class on Thursday December 15, 2022. The project accounts for 50% of your total course grade.

The deadline for submitting a project proposal to your tutor (see below) is by 23:59, Friday, November 11, 2022. Groups with late submission will not receive tutoring.

The draft report is due by 23:59, Wednesday, December 14, 2022. The final written report is due by 23:59, January 8, 2023. No late reports will be accepted.

General information

You will be divided into groups.

Each group will be paired with another group, and they will act as review groups for each other.
Each pair of groups gets a tutor assigned and has 2 meetings, 45 minutes each, with this tutor during the course.
The tutor’s job is to give you general advice on anything you need as best as he or she can. The tutor’s job is not to formulate your project for you, nor to debug your code.
Should you experience problems with the group assembly, you need to take this up with your tutor as soon as possible.

Your project needs two things to get started: a topic and a question (or problem formulation). A topic explains what you are going to do, a question explains why. A typical topic description could be "we want to do a agent-based simulation of a predator-prey system." A corresponding question could be "to see whether space changes the stability as compared to the behaviour in the standard ODE models.”

The first meeting with the tutor is to ensure that you’re embarking on a feasible project. Before this meeting you should:

Define your project.
Write a two paragraphs long proposal; one explaining the background of the project, possibly with references to relevant literature, and another outlining what you aim to do and why.
Discuss your project with your review group and revise your proposal accordingly.
Send the proposal to your tutor.
Prepare for the meeting; prepare questions, comments, simulations, results, or whatever is relevant for a most efficient outcome of the meeting.

The second meeting with the tutor is to ensure that you have progress and direction so that you are on course to completion. Before this meeting you should:

Have ready an implementation of your model.
Have a set of preliminary results from simulations.
Have ready the outline of a report.
Have met with your review group to discuss model, results and report outline.
Send the report outline to your tutor.
Prepare for the meeting; prepare questions, comments, simulations, results, or whatever is relevant for a most efficient outcome of the meeting.

General advice

If I had an hour to solve a problem and my life depended on it, I would use the first 55 minutes to formulate the right question because as soon as I have identified the right question I can solve the problem in less than five minutes.

—Albert Einstein

Everything takes longer time than you expect, so getting started with your model implementation is essential for a successful project. Do not interpret the time ratio in the quote too literally; the moral is that you need to have a question you want to answer with your model. This provides the project with direction and makes navigating it much easier. But research (as much else) is a highly iterative process, so don’t expect a perfect question from the start. If you realise your question didn't make sense half-way through your project, take the time to try and formulate a new one. In a lot of real research the question at the end of a project ends up being quite different from the one that started the project (similarly among start-ups, many end up with a completely different product than their initial idea).

Start simple. It is fine to have a grand idea, but make sure the steps to the goal have some value in themselves. Not only does this prevent you from being stuck with nothing to show at the end of the course, it also gives you feedback on your big idea as early as possible. Start with a small question and iterate it towards greatness.

If there is a simpler model of what you are trying to do that shows some of its interesting features, at the very least think about how they compare. Ideally, implement both and do a careful comparison. You can often get great project ideas out of thinking about what you lose when you remove features.

It's OK to fail. Research has a large portion of luck involved. If you have a good idea that don't work out, analyse why and we'll be all happy.

Presentation

The presentation of the project should take maximum 8 minutes and be prerecorded (MOV format), with an additional 10 minutes for questions and discussion.

Put the emphasis on what your problem formulation is, a general discussion about how you tackled it, what problems you had, and what your conclusions are.

Report

The report should be written in RevTex 4.2 (see https://journals.aps.org/revtex), using the format of Physical Review X with a limit of 8 pages in double-column reprint format (including pictures and references). If needed, you can have an extra document containing an unlimited amount of Supplementary Materials.

Structure your report like a scientific article, with an abstract summarising the rationale and results of the project; an introduction shortly explaining its background and motivating why the question is interesting; methods and/or results section(s) describing your model and what you do with it; a discussion section; and ending with a conclusion. Put some work into the discussion and conclusion sections. This is where you demonstrate that you truly understand the implications of your work, including shortcomings and uncertainties. It is important that the discussion does not fall out as a simple summary of what the figures show.

Write in plain language and write enough to say what you need to say. Don't think "the report feels short, better throw in some extra figures." If you can say the same thing in fewer words, do so.

Be sure to reference any source you use. The report should be readable and understandable on its own, but there is no need to reproduce for example derivations of equations from your sources; a citation is enough.

Figures are an important part of the report, but only those that substantially contribute to your analysis should be included. Make sure that each figure is well designed with informative captions (not just "Fig. X shows how quantity A depends on quantity B"). If you find it hard to do this, you probably are not clear on why you include an figure, so cut it out.

Most importantly, use your own judgement and try to write a report you would like to read.

Evaluation criteria for report

Criteria that will be considered are:

Structure: Is the project report well structured (see above)?
Motivation: Does the project have a clear research question?
Originality: How original is the research question?
Background: Is the background of the research question well explained, including references to the literature?
Methods: Are the methods and analysis appropriate for convincingly answering the research question?
Execution: Does the project answer the initial or iterated research question?
Figures: Are the figures included informative with descriptive captions?
Format: Is the format of the report as required?
Outlook: Are the implications of the results clearly stated?
Contributions: Is there a contributions statement in the report?

Note that the research question does not have to be answered in the affirmative. A negative result is equally valid as long as an analysis is carried out that properly explains the negative result and what eventually would work better.

Evaluation criteria for presentation