# \[ANN\] SIAMFANLEquations.jl: Nonlinear solvers and book project

**URL:** https://discourse.julialang.org/t/ann-siamfanlequations-jl-nonlinear-solvers-and-book-project/51196
**Category:** Package Announcements
**Tags:** numerics
**Created:** [December 3, 2020, 2:20pm UTC](https://discourse.julialang.org/t/ann-siamfanlequations-jl-nonlinear-solvers-and-book-project/51196 "2020-12-03T14:20:01Z")
**Posts on this page:** 1
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### Author: ![ctkelley](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ctkelley/32/10684_2.png) [@ctkelley](https://discourse.julialang.org/u/ctkelley)
#### Post date: [November 30, 2021, 5:06pm UTC](https://discourse.julialang.org/t/ann-siamfanlequations-jl-nonlinear-solvers-and-book-project/51196/22 "2021-11-30T17:06:25Z")

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I’ve just tagged v0.4.3 of SIAMFANLEquations.jl. This is a suite of nonlinear solvers, test problems, and examples. Chapter 4 is Anderson acceleration, which is the new material since v0.3.3.

This package supports my book project

**Solving Nonlinear Equations with Iterative Methods:**  
**Solvers and Examples in Julia**

which will be published by SIAM in 2022.

The solvers are documented with Documenter.jl on the github repo and with a collection of IJulia notebooks at

> **[GitHub - ctkelley/NotebookSIAMFANL: Notebook for my new solver book](https://github.com/ctkelley/NotebookSIAMFANL)**
>
> Notebook for my new solver book. Contribute to ctkelley/NotebookSIAMFANL development by creating an account on GitHub.

The notebooks are a faithful reproduction of the entire book.

This version includes the draft of Chapter 4: Fixed Point Problems and Anderson Acceleration

I have decided to take my own advice from the middle of the discussion in

> [@Quasi-newton nonlinear solver for sparse jacobian](https://discourse.julialang.org/t/quasi-newton-nonlinear-solver-for-sparse-jacobian/57672/8):
>
> BFGS is not a nonlinear solver method. It seeks to maintain a SPD Hessian for optimization. The thing to remember is that optimization and nonlinear solvers are not the same thing. Using an algorithm desinged for one of them to solve the other is a bad, bad, bad idea. Broyden looks for a general low-rank change to an approximate Jacobian and is designed for nonlinear solver applications. Broyden needs a good preconditioner to perform well and has fallen out of favor in the last few decades. New…

and leave Broyden’s method out. So, the solvers are done.

The last chapter will be Chapter 5: Case Studies.

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