# Add a multi-dimensional state variable

Just like normal JuMP variables, it is possible to create containers of state variables.

```
julia> model = SDDP.LinearPolicyGraph(
stages=1, lower_bound = 0, optimizer = HiGHS.Optimizer
) do subproblem, t
# A scalar state variable.
@variable(subproblem, x >= 0, SDDP.State, initial_value = 0)
println("Lower bound of outgoing x is: ", JuMP.lower_bound(x.out))
# A vector of state variables.
@variable(subproblem, y[i = 1:2] >= i, SDDP.State, initial_value = i)
println("Lower bound of outgoing y[1] is: ", JuMP.lower_bound(y[1].out))
# A JuMP.Containers.DenseAxisArray of state variables.
@variable(subproblem,
z[i = 3:4, j = [:A, :B]] >= i, SDDP.State, initial_value = i)
println("Lower bound of outgoing z[3, :B] is: ", JuMP.lower_bound(z[3, :B].out))
end;
Lower bound of outgoing x is: 0.0
Lower bound of outgoing y[1] is: 1.0
Lower bound of outgoing z[3, :B] is: 3.0
```