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.

For a more complete documentation on nonlinear solvers for steady state problems, see NonlinearSolve.jl

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 or BDF method (Rodas5 or QNDF), 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. (This method is deprecated: use NonlinearSolve.jl instead).
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 the 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)