# Great news for Dynamics in Julia!

**URL:** <https://discourse.julialang.org/t/great-news-for-dynamics-in-julia/17321>\
**Category:** Modelling & Simulations\
**Created:** [November 8, 2018, 8:04pm UTC](https://discourse.julialang.org/t/great-news-for-dynamics-in-julia/17321 "2018-11-08T20:04:17Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Datseris](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/datseris/32/13406_2.png) [@Datseris](https://discourse.julialang.org/u/Datseris)\
**Post date:** [November 8, 2018, 8:04pm UTC](https://discourse.julialang.org/t/great-news-for-dynamics-in-julia/17321/1 "2018-11-08T20:04:17Z")

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Hello everyone,

Since I don’t have a blog, this is like an announcement of shorts for JuliaDynamics. I bear good news 🙂

# DSWeb prize

Pretty much everyone is aware of this, but I just want to apologize for not announcing it “officially” myself, and letting people just ask about it randomly on discourse e.g. [here](https://discourse.julialang.org/t/to-promote-julia-show-scientific-work-already-done/15032) and [here](https://discourse.julialang.org/t/award-for-juliadynamics/15024) (which I wasn’t even aware of 😛 ).

So yeah, we have won the recent SIAM competition:

[https://dsweb.siam.org/The-Magazine/Article/winners-of-the-dsweb-2018-software-contest](https://dsweb.siam.org/The-Magazine/Article/winners-of-the-dsweb-2018-software-contest)

# Issues with Bounties

I couldn’t think of a better way to spend the prize money than to make them bounties for GitHub issues. Each issue has 100$ bounty , but if you solve it you will only get 90$ because I am a moron and don’t know how Bountysource works. Anyway, let me give you a quick rundown of the issues:

- [Website for JuliaDynamics](https://github.com/JuliaDynamics/JuliaDynamicsDocumentation.jl/issues/24) : because we are super jealous of the website of [QuantumOptics.jl](https://qojulia.org/).

- [Minimal and dedicated integrator](https://github.com/JuliaDynamics/DynamicalSystemsBase.jl/issues/76) : we hope increase the clarity of ODE solving, increase performance and maybe along the way solve some performance issues like eg. [this](https://github.com/JuliaDiffEq/OrdinaryDiffEq.jl/issues/518) and others I have been encountering using `SMatrices`. (more details on that once work on the integrator starts)

- [Distinguishing Hard chaos from partially predictable chaos](https://github.com/JuliaDynamics/ChaosTools.jl/issues/68) is a new “bleeding edge” algorithm published recently in Scientific Reports.

- [Increasing the performance of entropy computation](https://github.com/JuliaDynamics/ChaosTools.jl/issues/58) . No new algorithms, just good old speed boost 🙂

- [Definition of Chaos (expansion entropy)](https://github.com/JuliaDynamics/ChaosTools.jl/issues/4) : Ott suggested a way to computationally define chaos (by the way “Chaos” is actually hard to define 😃 ) . Again a “bleeding” edge algorithm.

We got a lot of “basic / standard / fundamental” stuff in DynamicalSystems.jl so some bleeding edge is good 🙂

I know these bounties are tini-tiny . I wish I could put more money. I truly do. I can tell you, If we win more prizes there will be more money! 🙂

[here is a link with all bounties](https://github.com/search?utf8=%E2%9C%93&q=org%3AJuliaDynamics+is%3Aissue+label%3Abounty&type=)

# `DynamicalBilliards 3.0`

New version is out, it is very nice, very hot, and it has an even hotter new logo:

 ![DynamicalBilliards_logo_animated](https://global.discourse-cdn.com/julialang/original/3X/3/2/323d4c71721f2af985a21e6cc1a9816d980a4a64.gif)

(notice the super-hot continuous time animation? Made by a brilliant student @lhupe )

Enjoy! 🙂 Of course there is a changelog.

# An example showcasing the strength of Multiple Dispatch

Based on this billiard package and answering this post: [Idea: repository for examples highlighting Julia's strengths](https://discourse.julialang.org/t/idea-repository-for-examples-highlighting-julias-strengths/13841)

there is now a fully stand-alone example that shows why Julia **ROCKS AND KICKS ASS**. In addition to the repository in the above link, you can also find this example in the NextJournal, courtesy of @SimonDanisch

link: [Simulating billiards in Julia - Nextjournal](https://nextjournal.com/julia/billiard)

# Interactive applications for the exploration of chaos

My free time the coming semester will be devoted to developing interactive applications for the exploration of chaos and dynamical systems. This will be done with `Makie` !!! Yes! Makieeeee

we plan to use these applications to make video tutorials and apply to this contest:

[https://dsweb.siam.org/The-Magazine/Article/dsweb-2019-contest-tutorials-on-dynamical-systems-software](https://dsweb.siam.org/The-Magazine/Article/dsweb-2019-contest-tutorials-on-dynamical-systems-software)

_Any_ help will be welcomed! Please join our Slack channel or Gitter channel (they are connected) if you are interested! 🙂

# TimeseriesPrediction.jl is about to become 1.0 and is also independent from DynamicalSystems.jl

If possible, please take a look at [TimeseriesPrediction.jl](https://juliadynamics.github.io/DynamicalSystems.jl/latest/tsprediction/stexamples/)

we had a brilliant student working on it ( @JonasIsensee ) and we feel that we had made enough progress for a 1.0 release. We don’t have enough real-world testing though, so we would appreciate some help on that.

TimeseriesPrediction was bundled with DynamicalSystems, but after all these features with Spatio-Temporal timeseries we believe it has departed in functionality enough to be its own package.

# Recurrence quantification analysis to join DynamicalSystems.jl

There is a package for [Recurrence quantification analysis](https://github.com/heliosdrm/RecurrenceAnalysis.jl). I have offered the main developer to join forces with us at JuliaDynamics (since we have not only a lot of overlap but also we care about nonlinear dynamics and delay embedding).

To my understanding @heliosrdm was [happy to join](https://github.com/heliosdrm/RecurrenceAnalysis.jl/issues/8#issuecomment-436265496), which is great! This will benefit everyone! `RecurrenceAnalysis` and `DynamicalSystems` both become better _and_ the community has a unified (and stronger) framework for delay embedding!

# GAIO coming to Julia and maybe even join DynamicalSystems.jl

Prof. [Oliver Junge](https://www-m3.ma.tum.de/Allgemeines/OliverJunge) invited me to give a talk about DynamicalSystems.jl at his group. During our discussions we both agreed that the super-useful and super-feature-full [GAIO](https://dsweb.siam.org/Software/gaio-global-analysis-of-invariant-objects) must be ported to Julia!

Global Analysis of Invariant Objects allows you to do many useful things like find invariante sets and invariante measures ! There is also a relevant issue at `ChaosTools` [here](https://github.com/JuliaDynamics/ChaosTools.jl/issues/37) that has nice links to the papers, if you want to read more.

The idea is for GAIO to become a julia package exported by DynamicalSystems.jl, much like ChaosTools and the upcoming RecurrenceAnalysis, but official confirmation about this part is still pending.

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [November 8, 2018, 8:18pm UTC](https://discourse.julialang.org/t/great-news-for-dynamics-in-julia/17321/2 "2018-11-08T20:18:16Z")

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> [@Datseris](#):
>
> [Minimal and dedicated integrator](https://github.com/JuliaDynamics/DynamicalSystemsBase.jl/issues/76) : we hope increase the clarity of ODE solving, increase performance and maybe along the way solve some performance issues like eg. [this](https://github.com/JuliaDiffEq/OrdinaryDiffEq.jl/issues/518) and others I have been encountering using `SMatrices` . (more details on that once work on the integrator starts)

@YingboMa and I already started BTW (since this is part of GPU-based integrators we’re working on). [Tsit5 WIP PR](https://github.com/JuliaDiffEq/SimpleDiffEq.jl/pull/7/files). We were going to just do `solve`, but it’s actually quite simple to do solve an a simple (no event) `integrator` at the same time. So what’s this `SMatrix` problem you’re talking about?

BTW, instead of using BountySource you can just pay for lunch at the next JuliaCon 😉.