Hi everyone,

I’m studying part of the 2D Swift Hohenberg model with an additive noise term, but I’m really new to the SDEProblems so I don’t know if my way to build the model is the best way to solve it.

I’ve take a look to the tutorial Stochastic Differential Equations · DifferentialEquations.jl and I’ve defined

```
function Add_noise(u,p,t)
return fill(0.5,Nx*Ny)
end
```

As the noise. Then

```
#Definition of the problem
u0= rand(Nx,Ny) |> vec
tspan = (0.0,35.0)
prob =@time SDEProblem(F_sh,Add_noise,u0,tspan,p);
```

Where F_sh is

```
#Definition of the equation
function F_sh(u, p, t)
@unpack l , L1 = p
return -L1 * u .+ (l .* u)
end
```

And L1 is the SH operator.

Then I try to solve the problem using

```
#Solution of the problem
sol =@time solve(prob,alg_hints=[:additive,:stiff],SRIW1(), save_everystep=false, save_start=false, saveat=[5,35])
```

But it seems not working very well because is slow, in particular increasing the resolution of the grid (Nx*Ny).

What kind of error I’m doing?

Thank you so much for the help, every comment is welcome!