Minor changes

src/qobj/quantum_object_evo.jl

@@ -92,12 +92,9 @@ end
 
 # Make the QuantumObjectEvolution, with the option to pre-multiply by a scalar
 function QuantumObjectEvolution(op_func_list::Tuple, α = true)
-    op = _get_op_func_first(op_func_list)
+    op, data = _generate_data(op_func_list, α)
     dims = op.dims
     type = op.type
-    T = eltype(op)
-
-    data = _generate_data(T, op_func_list, α)
 
     # Preallocate the SciMLOperator cache using a dense vector as a reference
     v0 = sparse_to_dense(similar(op.data, size(op, 1)))
@@ -109,12 +106,14 @@ end
 QuantumObjectEvolution(op::QuantumObject, α = true) =
     QuantumObjectEvolution(MatrixOperator(α * op.data), op.type, op.dims)
 
-@generated function _get_op_func_first(op_func_list::Tuple)
+@generated function _generate_data(op_func_list::Tuple, α)
     op_func_list_types = op_func_list.parameters
     N = length(op_func_list_types)
-    T = ()
+
     dims_expr = ()
     first_op = nothing
+    data_expr = :(0)
+
     for i in 1:N
         op_func_type = op_func_list_types[i]
         if op_func_type <: Tuple
@@ -126,8 +125,8 @@ QuantumObjectEvolution(op::QuantumObject, α = true) =
                     "The first element must be a Operator or SuperOperator, and the second element must be a function.",
                 ),
             )
+
             data_type = op_type.parameters[1]
-            T = (T..., eltype(data_type))
             dims_expr = (dims_expr..., :(op_func_list[$i][1].dims))
             if i == 1
                 first_op = :(op_func_list[$i][1])
@@ -136,47 +135,34 @@ QuantumObjectEvolution(op::QuantumObject, α = true) =
             op_type = op_func_type
             (isoper(op_type) || issuper(op_type)) ||
                 throw(ArgumentError("The element must be a Operator or SuperOperator."))
+
             data_type = op_type.parameters[1]
-            T = (T..., eltype(data_type))
             dims_expr = (dims_expr..., :(op_func_list[$i].dims))
+
             if i == 1
                 first_op = :(op_func_list[$i])
             end
         end
+        data_expr = :($data_expr + _make_SciMLOperator(op_func_list[$i], α))
     end
 
-    length(unique(T)) == 1 || throw(ArgumentError("The types of the operators must be the same."))
-
     quote
         dims = tuple($(dims_expr...))
 
         length(unique(dims)) == 1 || throw(ArgumentError("The dimensions of the operators must be the same."))
 
-        return $first_op
+        return $first_op, $data_expr
     end
 end
 
-@generated function _generate_data(T, op_func_list::Tuple, α)
-    op_func_list_types = op_func_list.parameters
-    N = length(op_func_list_types)
-    data_expr = :(0)
-    for i in 1:N
-        op_func_type = op_func_list_types[i]
-        if op_func_type <: Tuple
-            data_expr = :(
-                $data_expr +
-                ScalarOperator(zero(T), op_func_list[$i][2]) * MatrixOperator(α * op_func_list[$i][1].data)
-            )
-        else
-            data_expr = :($data_expr + MatrixOperator(α * op_func_list[$i].data))
-        end
-    end
-
-    quote
-        return $data_expr
-    end
+function _make_SciMLOperator(op_func::Tuple, α)
+    T = eltype(op_func[1])
+    update_func = (a, u, p, t) -> op_func[2](p, t)
+    return ScalarOperator(zero(T), update_func) * MatrixOperator(α * op_func[1].data)
 end
 
+_make_SciMLOperator(op::QuantumObject, α) = MatrixOperator(α * op.data)
+
 function (QO::QuantumObjectEvolution)(p, t)
     # We put 0 in the place of `u` because the time-dependence doesn't depend on the state
     update_coefficients!(QO.data, 0, p, t)

src/time_evolution/sesolve.jl

@@ -4,7 +4,7 @@ function _save_func_sesolve(integrator)
     internal_params = integrator.p
     progr = internal_params.progr
 
-    if internal_params.is_empty_e_ops
+    if !internal_params.is_empty_e_ops
         e_ops = internal_params.e_ops
         expvals = internal_params.expvals
 
@@ -16,13 +16,6 @@ function _save_func_sesolve(integrator)
     return u_modified!(integrator, false)
 end
 
-sesolve_ti_dudt!(du, u, p, t) = mul!(du, p.U, u)
-function sesolve_td_dudt!(du, u, p, t)
-    mul!(du, p.U, u)
-    H_t = p.H_t(t, p)
-    return mul!(du, H_t, u, -1im, 1)
-end
-
 function _generate_sesolve_kwargs_with_callback(t_l, kwargs)
     cb1 = PresetTimeCallback(t_l, _save_func_sesolve, save_positions = (false, false))
     kwargs2 =
@@ -132,7 +125,7 @@ function sesolveProblem(
     kwargs3 = _generate_sesolve_kwargs(e_ops, makeVal(progress_bar), t_l, kwargs2)
 
     tspan = (t_l[1], t_l[end])
-    return ODEProblem{true}(U, ϕ0, tspan, p; kwargs3...)
+    return ODEProblem{true,FullSpecialize}(U, ϕ0, tspan, p; kwargs3...)
 end
 
 @doc raw"""