# Steady State Solvers

`solve(prob::SteadyStateProblem,alg;kwargs)`

Solves for the steady states in the problem defined by `prob`

using the algorithm `alg`

. If no algorithm is given, a default algorithm will be chosen.

## Recommended Methods

`DynamicSS`

is a good choice if you think you may have multiple steady states or a bad initial guess. `SSRootfind`

can be faster if you have a good initial guess. For `DynamicSS`

, in many cases an adaptive stiff solver, like a Rosenbrock method (`Rodas5`

or `CVODE_BDF`

), is a good way to allow for very large time steps as the steady state approaches. Note that if you use `CVODE_BDF`

you may need to give a starting `dt`

via `dt=....`

.

## Full List of Methods

### SteadyStateDiffEq.jl

`SSRootfind`

: Uses a rootfinding algorithm to find a steady state. Defaults to using NLsolve.jl. A different algorithm can be specified via the`nlsolve`

keyword argument.`DynamicSS`

: Uses an ODE solver to find the steady state. Automatically terminates when close to the steady state.`DynamicSS(alg;abstol=1e-8,reltol=1e-6,tspan=Inf)`

requires that an ODE algorithm is given as the first argument. The absolute and relative tolerances specify the termination conditions on the derivative's closeness to zero. This internally uses the`TerminateSteadyState`

callback from the Callback Library. The simulated time for which given ODE is solved can be limited by`tspan`

. If`tspan`

is a number, it is equivalent to passing`(zero(tspan), tspan)`

.

Example usage:

```
sol = solve(prob,SSRootfind())
sol = solve(prob,DynamicSS(Tsit5()))
using Sundials
sol = solve(prob,DynamicSS(CVODE_BDF()),dt=1.0)
```