diff --git a/pySDC/implementations/sweeper_classes/ParaDiagSweepers.py b/pySDC/implementations/sweeper_classes/ParaDiagSweepers.py
index b9c1be53cb..c5d406133f 100644
--- a/pySDC/implementations/sweeper_classes/ParaDiagSweepers.py
+++ b/pySDC/implementations/sweeper_classes/ParaDiagSweepers.py
@@ -25,19 +25,20 @@ class QDiagonalization(generic_implicit):
     parameters if you want to use this sweeper in SDC.
     """
 
-    def __init__(self, params):
+    def __init__(self, params, level):
         """
         Initialization routine for the custom sweeper
 
         Args:
             params: parameters for the sweeper
+            level (pySDC.Level.level): the level that uses this sweeper
         """
         if 'G_inv' not in params.keys():
             params['G_inv'] = np.eye(params['num_nodes'])
         params['update_f_evals'] = params.get('update_f_evals', False)
         params['ignore_ic'] = params.get('ignore_ic', True)
 
-        super().__init__(params)
+        super().__init__(params, level)
 
         self.set_G_inv(self.params.G_inv)
 
diff --git a/pySDC/tutorial/step_9/A_paradiag_for_linear_problems.py b/pySDC/tutorial/step_9/A_paradiag_for_linear_problems.py
index bacfe8e5fd..fb0d678f84 100644
--- a/pySDC/tutorial/step_9/A_paradiag_for_linear_problems.py
+++ b/pySDC/tutorial/step_9/A_paradiag_for_linear_problems.py
@@ -35,7 +35,7 @@ def my_print(*args, **kwargs):
 # setup pySDC infrastructure for Dahlquist problem and quadrature
 prob = problem_class(lambdas=-1.0 * np.ones(shape=(N)), u0=1.0)
 sweeper_params = params = {'num_nodes': M, 'quad_type': 'RADAU-RIGHT'}
-sweep = generic_implicit(sweeper_params)
+sweep = generic_implicit(sweeper_params, None)
 
 # Setup a global NumPy array and insert initial conditions in the first step
 u = np.zeros((L, M, N), dtype=complex)
@@ -235,7 +235,7 @@ def residual(_u, u0):
 """
 G = [(D_alpha_diag_vals[l] * H_M + I_M).tocsc() for l in range(L)]  # MxM
 G_inv = [sp.linalg.inv(_G).toarray() for _G in G]  # MxM
-sweepers = [QDiagonalization(params={**sweeper_params, 'G_inv': _G_inv}) for _G_inv in G_inv]
+sweepers = [QDiagonalization(params={**sweeper_params, 'G_inv': _G_inv}, level=None) for _G_inv in G_inv]
 
 
 sol_ParaDiag = u.copy().astype(complex)
diff --git a/pySDC/tutorial/step_9/B_paradiag_for_nonlinear_problems.py b/pySDC/tutorial/step_9/B_paradiag_for_nonlinear_problems.py
index 70a24a8a02..64525566bc 100644
--- a/pySDC/tutorial/step_9/B_paradiag_for_nonlinear_problems.py
+++ b/pySDC/tutorial/step_9/B_paradiag_for_nonlinear_problems.py
@@ -58,7 +58,7 @@ def my_print(*args, **kwargs):
 u = np.zeros((L, M, N), dtype=complex)
 
 # setup collocation problem
-sweep = sweeper_class({'num_nodes': M, 'quad_type': 'RADAU-RIGHT'})
+sweep = sweeper_class({'num_nodes': M, 'quad_type': 'RADAU-RIGHT'}, None)
 
 # initial conditions
 u[0, :, :] = prob.u_exact(t=0)