# Notebook on particle simulations

**URL:** <https://discourse.julialang.org/t/notebook-on-particle-simulations/68496>\
**Category:** Modelling & Simulations\
**Tags:** notebooks\
**Created:** [September 21, 2021, 12:03am UTC](https://discourse.julialang.org/t/notebook-on-particle-simulations/68496 "2021-09-21T00:03:44Z")\
**Posts on this page:** 1\
**Showing post:** 3

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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:** [September 21, 2021, 1:39am UTC](https://discourse.julialang.org/t/notebook-on-particle-simulations/68496/3 "2021-09-21T01:39:11Z")

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> We can differentiate everything!

Be careful with differentiating chaotic systems. This would be a good reason to use the DifferentialEquations.jl adjoints. See:

> **[Shadowing Methods for Forward and Adjoint Sensitivity Analysis of Chaotic...](https://frankschae.github.io/post/shadowing/)**
>
> In this post, we dig into sensitivity analysis of chaotic systems. Chaotic systems are dynamical, deterministic systems that are extremely sensitive to small changes in the initial state or the system parameters.

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