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samu-sys · Jun 1, 2024 · 0cddc5f · 0cddc5f
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diff --git a/src/steadystate.jl b/src/steadystate.jl
@@ -185,7 +185,7 @@ In the case of `SSFloquetEffectiveLiouvillian`, instead, the effective Liouvilli
 !!! note "different return"
     The two solvers returns different objects. The `SSFloquetLinearSystem` returns a list of `QuantumObject`, containing the density matrices for each Fourier component (`\hat{\rho}_{-n}`, with `n` from `0` to `n_max`), while the `SSFloquetEffectiveLiouvillian` returns only `\hat{\rho}_0`. 
 
-# Arguments
+## Arguments
 - `H_0::QuantumObject`: The Hamiltonian or the Liouvillian of the undriven system.
 - `H_p::QuantumObject`: The Hamiltonian or the Liouvillian of the part of the drive that oscillates as ``e^{i \\omega t}``.
 - `H_m::QuantumObject`: The Hamiltonian or the Liouvillian of the part of the drive that oscillates as ``e^{-i \\omega t}``.
@@ -204,7 +204,7 @@ function steadystate_floquet(
     c_ops::AbstractVector = QuantumObject{MT,OpType1}[];
     n_max::Integer = 2,
     tol::R = 1e-8,
-    solver::FSolver = SSFloquetLinearSystem,
+    solver::FSolver = SSFloquetLinearSystem(),
     kwargs...,
 ) where {
     MT<:AbstractArray,
@@ -221,15 +221,15 @@ function steadystate_floquet(
 end
 
 function _steadystate_floquet(
-    L_0::QuantumObject{<:AbstractArray{T1},OpType},
-    L_p::QuantumObject{<:AbstractArray{T2},OpType},
-    L_m::QuantumObject{<:AbstractArray{T3},OpType},
+    L_0::QuantumObject{<:AbstractArray{T1},SuperOperatorQuantumObject},
+    L_p::QuantumObject{<:AbstractArray{T2},SuperOperatorQuantumObject},
+    L_m::QuantumObject{<:AbstractArray{T3},SuperOperatorQuantumObject},
     ωd::Number,
     solver::SSFloquetLinearSystem;
     n_max::Integer = 1,
     tol::R = 1e-8,
     kwargs...,
-) where {T1,T2,T3,OpType<:SuperOperatorQuantumObject,R<:Real}
+) where {T1,T2,T3,R<:Real}
     T = promote_type(T1, T2, T3)
 
     L_0_mat = get_data(L_0)
@@ -279,19 +279,19 @@ function _steadystate_floquet(
 end
 
 function _steadystate_floquet(
-    L_0::QuantumObject{<:AbstractArray{T1},OpType},
-    L_p::QuantumObject{<:AbstractArray{T2},OpType},
-    L_m::QuantumObject{<:AbstractArray{T3},OpType},
+    L_0::QuantumObject{<:AbstractArray,SuperOperatorQuantumObject},
+    L_p::QuantumObject{<:AbstractArray,SuperOperatorQuantumObject},
+    L_m::QuantumObject{<:AbstractArray,SuperOperatorQuantumObject},
     ωd::Number,
     solver::SSFloquetEffectiveLiouvillian;
     n_max::Integer = 1,
     tol::R = 1e-8,
     kwargs...,
-) where {T1,T2,T3,OpType<:SuperOperatorQuantumObject,R<:Real}
+) where {R<:Real}
     ((L_0.dims == L_p.dims) && (L_0.dims == L_m.dims)) ||
         throw(ErrorException("The operators are not of the same Hilbert dimension."))
 
-    L_eff = liouvillian_floquet(L_0, L_p, L_m, ωd, n_max; tol = tol, kwargs...)
+    L_eff = liouvillian_floquet(L_0, L_p, L_m, ωd; n_max = n_max, tol = tol)
 
     return steadystate(L_eff; solver = solver.steadystate_solver, kwargs...)
 end
diff --git a/test/steady_state.jl b/test/steady_state.jl
@@ -34,11 +34,10 @@
     t_l = LinRange(0, 100 * 2π, 1000)
     H_t_f = TimeDependentOperatorSum([(t, p) -> sin(t)], [liouvillian(H_t)])
     sol_me = mesolve(H, psi0, t_l, c_ops, e_ops = e_ops, H_t = H_t_f, alg = Vern7(), progress_bar = false)
-    ρ_ss1 = steadystate_floquet(H, -1im * 0.5 * H_t, 1im * 0.5 * H_t, 1, c_ops, solver=SSFloquetLinearSystem())[1]
-    ρ_ss2 = steadystate_floquet(H, -1im * 0.5 * H_t, 1im * 0.5 * H_t, 1, c_ops, solver=SSFloquetEffectiveLiouvillian())
+    ρ_ss1 = steadystate_floquet(H, -1im * 0.5 * H_t, 1im * 0.5 * H_t, 1, c_ops, solver = SSFloquetLinearSystem())[1]
+    ρ_ss2 =
+        steadystate_floquet(H, -1im * 0.5 * H_t, 1im * 0.5 * H_t, 1, c_ops, solver = SSFloquetEffectiveLiouvillian())
 
-    @test tracedist(sol_me.states[end], ρ_ss1) < 1e-4
-    @test tracedist(sol_me.states[end], ρ_ss2) < 1e-4
-
-    # @test abs(sum(sol_me.expect[1, end-100:end]) / 101 - expect(e_ops[1], ρ_ss)) < 1e-2
+    @test abs(sum(sol_me.expect[1, end-100:end]) / 101 - expect(e_ops[1], ρ_ss1)) < 1e-3
+    @test abs(sum(sol_me.expect[1, end-100:end]) / 101 - expect(e_ops[1], ρ_ss2)) < 1e-3
 end