The ** Bucket List** below contains a few ideas on models and systems that are on the agenda for implementation.

If you have ideas about models or systems that are suitable for this site or that are missing contact me and I’ll try to implement them.

## Ideas and Future Explorables

### Stochastic “Kill the Winner” Model

Phys. Rev. Lett. 119, 268101 pointed out by Manlio. Great pick.

### Space-Filling Curves

- Peano, Hilbert etc.

### Chemotaxis

This one is at the top of the list because I’m working on it at the moment and it’s an important process in biology, e.g. in the aggregation of *Dictyostelium*. The plan is to implement the model proposed in this 1993 seminal paper by David Kessler and Herbert Levine:

- Pattern formation in Dictyostelium via the dynamics of cooperative biological entities, Phys. Rev. E 48, 4801 – Published 1 December 1993

### Lenia - Artificial Life

Lenia is an artifical life system that produces amazing patterns. Lenia’s inventor Bert Wang-Chak Chan (@BertChakovsky) and I are planning to implement a complexity explorable version. Check this out.

### Schelling’s segregation model

Pointed out to me by Avy Faingezicht, should be straightforward to implement.

### Tiebout sorting

Also pointed out by Avy.

### Epidemics on Adaptive Networks

This explorable is going to implement the model first discussed in:

- Thilo Gross, Carlos J. Dommar D’Lima, and Bernd Blasius, Epidemic Dynamics on an Adaptive Network, PRL 96, 208701 (2006)

one of the first papers in which network topology changes over time in ways determined by the dynamics that is evolving on the network.

### Random Boolean Networks

I’ve got thoughts about making an explorable about random boolean networks and visualizing their attractors.

### Flockworks

This one is about a set of models for temporal networks that naturally lead to group / cluster formation.

### The CHKNS model

This is a network model (as Steve Strogatz pointed out to me, it’ sometimes refered to as the chickens model) with an interesting phase transition.

This is the paper:

- D S.
**C**allaway, J. E.**H**opcroft, J. M.**K**leinberg,**N**ewman, and S. H.**S**trogatz,*Are randomly grown graphs really random?*, PHYSICAL REVIEW E, VOLUME 64, 041902

and here’s a great Observable Notebook by @blockspins

### Subordinated Random Walks

Subordinated random walks are random walks that evolve on the trajectory on another random walk. Depending on the setup one can generate anomalous diffusion this way.

- Aleksei V. Chechkin, Flavio Seno, Ralf Metzler, and Igor M. Sokolov,
*Brownian yet Non-Gaussian Diffusion: From Superstatistics to Subordination of Diffusing Diffusivities*, Phys. Rev. X 7, 021002 – Published 5 April 2017

### Zombie Epidemic Model

I want to make an agent based zombie epidemic explorable, there are many interesting papers on the arxiv, like this one.

### Hele Shaw Flow

This was proposed by Jonny Nono. Should be straightforward to implement.

## Let’s do one together!

We can also collaborate on an implementation, e.g. the explorables Hopfed Turingles, Surfing a Gene Pool, and Ride my Kuramotocycle! are all team work efforts.

Ideas for new explorables need to fit in to some extent. The requirements are somewhat loose:

- Explorables must be fairly straightforward to explain in words, without too much math.
- the explanation should fit into about one page.
- the system should have some parameters, so the user / student can observe how a system reacts to parameter changes using sliders, toggles etc.
- the system should be amenable to visual representation
- The system should not be too demanding numerically

If you are up for it just get in touch.