Course syllabus
Course-PM
FFR120 / FIM750 Simulation of complex systems lp2 HT19 (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
Tutors
Aykut Argun, Giovanni Volpe
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.
Schedule
Course literature
There is no single book that covers all the topics in the course so we have no required books. However, we provide a set of compulsory (and additional) readings assigned to each lecture that covers and perhaps broadens the content of the lectures.
Course design
| Date, time & place | Topic |
Readings / Materials to prepare |
Additional readings |
| Tue Nov 5 10:00-11:45 KB |
Lecture 1 The role of simulations in the study of complex systems. Course information. |
Resource letter CS-1: |
Methods and techniques of complex systems science: An overview Excellence in computer simulation Evolutionary phenomena in simple dynamics |
| Thu Nov 7 8:00-11:45 F-T7203 |
Exercise 1 Help for HW1. |
Code HW 1 |
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Fri Nov 8 10:00-11:45 KB |
Lecture 2 Agent-based models. SIR model of disease spreading. Vicsek model and agent-based models. |
Agent-based models The SIR model and the foundations of public health Modelling to prevent pandemics Novel type of phase transition in a system of self-driven particles |
Meltdown modelling The economy needs agent-based modelling Novel type of phase transition in a system of self-driven particles |
|
Fri Nov 8 |
Project groups announced |
The project groups will be formed randomly. If, for a very good reasons, this is not optimal for you, inform the instructor before Thu Nov 8. |
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Tue Nov 12 |
Lecture 3 by Aykut Argun Active matter and nonequilibrium systems. |
Simulation of the active Brownian motion of a microswimmer Metastable clusters and channels formed by active particles with aligning interactions. |
Active particles in complex and crowded environments |
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Wed Nov 13 |
Project Proposal |
Submit your project proposal by email to your tutor |
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~ Nov 14-27 |
1st meeting with tutor |
Arrange a 45-minute meeting with tutor |
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Thu Nov 14 |
Exercise 2 Examination: Correction HW1. Help for HW2. |
Report HW1 Code HW2 |
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Fri Nov 15 |
Lecture 4 Introduction to cellular automata. Cellular automata as modeling technique. |
Cellular automata as models of complexity Cellular automata: A discrete view of the world |
Statistical mechanics of cellular automata |
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Tue Nov 19 |
Lecture 5 Examples of networks and properties of networks. Random models of networks. |
The structure and function of complex networks (pages 1-37) |
Network science |
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Thu Nov 21 |
Exercise 3 Examination: Correction HW2. Help for HW3. |
Report HW2 Code HW3 |
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Tue Nov 26 |
Lecture 6 by Mite Mijalkov Brain connectivity and its application to medical diagnostics. |
BRAPH: A graph theory software for the analysis of brain connectivity |
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Thu Nov 28 |
Exercise 4 Examination: Correction HW3. Help for HW4. |
Report HW3 Code HW4 |
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Fri Nov 29 |
Project report scheme |
Submit a scheme of your project by email to your tutor | |
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~ Dec 2-13 |
2nd meeting with tutor | Arrange a 45-minute meeting with tutor | |
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Tue Dec 3 |
Lecture 7 Modularity of networks and processes on networks. |
The structure and function of complex networks (pages 37-48) |
The anatomy of a large-scale hypertextual web search engine Network: An Introduction, MEJ Newman, Oxford University Press, March 2010 |
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Thu Dec 5 |
Exercise 5 Examination: Correction HW4. |
Report HW4 |
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Mon Dec 9 |
Exercise 5 Q&A session |
- | |
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Tue Dec 10 |
Lecture 8 Random walks and diffusion. |
Simulation of a Brownian particle in an optical trap |
Notes on random walks by Aaron Clauset 1, 2 & 3 Investigations on the theory of the Brownian movement |
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Wed Dec 18 |
Draft of project report |
Send a draft of your project report by email to your tutor | |
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Thu Dec 19 |
Project Presentation |
Presentation project Draft report project |
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Sun Jan 12 |
Project report |
Send your project report by email to your tutor |
Learning objectives and syllabus
Learning objectives:
-Describe the fundamental ideas behind the simulation methods discussed in the course, in particular agent based modelling and networks.
-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:
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 counting 50% of the final grade.
Homework information
The purpose of the 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 problem sets available, each accounting for 25 points. A perfect score is therefore 100. The problem sets account for 50% of your total course grade.
The grade limits will be 50 points for grade 3, 70 points for grade 4, and 90 points for grade 5.
For GU the limits will be 50 points for G and 80 for VG.
Note: A necessary (but not sufficient) requirement for passing grade is that 10 points are achieved in each homework.
Computer labs: The computer lab sessions serve two purposes: 1) To get help if you are stuck in a problem set (and have not managed to get unstuck by consulting some of your classmates); and 2) To have your homework graded. The time we have available for computer lab is limited, so it is essential that you come prepared to the lab, with specific questions you need to have answered. Everyone involved will appreciate the reduced queue times.
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 10 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 20. The project accounts for 50% of your total course grade.
The grade limits will be 50 points for grade 3, 70 points for grade 4, and 90 points for grade 5.
For GU the limits will be 50 points for G and 80 for VG.
The deadline for submitting a project proposal via email to your tutor (see below) is by 23:59, Wednesday, November 13, 2017. Groups with late submission will not receive tutoring.
The project will be presented to the class on Thursday December 19. The draft report is due by 23:59, December 18. The final written report is due (via email to your tutor) by 23:59, January 12, 2020. No late reports will be accepted.
General information
You will be randomly divided into groups (exceptions are possible for very good reasons). The reason for this is twofold; it will assure a broad distribution of skills and interest; it is a realistic scenario for later work in academia or industry.
- 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 it be so that 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 15 minutes, with an additional 5 minutes for questions and discussion. The timing will be enforced, so make sure you go through the presentation beforehand and check its duration. You decide whether and how to divide the material between yourselves.
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
You are free to chose your own format for the report. But restrict yourself to 10 pages maximum!
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:
- Is the project report well structured (see above)?
- Does the project have a clear research question?
- Does the project answer the initial or iterated research question?
- Are the methods and analysis appropriate for convincingly answering the research question?
- Is there a clear coupling between the model, the research question, and conclusions?
- Are the figures included informative with descriptive captions?
- Is the length of the report appropriate for the story it tells?
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
Criteria that will be considered are:
- Is the presentation well structured for a 10-minute presentation?
- Is it clear from the presentation what is being investigated?
- Is it clear from the presentation what model choices were made?
- Is it clear from the presentation how the model works?
- Is it clear from the presentation how the results are analysed?
- Is it clear from the presentation what the outcome of the project is?
Course summary:
| Date | Details | Due |
|---|---|---|