diff --git a/artist/field/actuator.py b/artist/field/actuator.py
index ef323daa..2bb53545 100644
--- a/artist/field/actuator.py
+++ b/artist/field/actuator.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 
@@ -81,7 +83,7 @@ def __init__(
         self.phi_0 = phi_0
 
     def motor_steps_to_angles(
-        self, motor_steps: torch.Tensor, device: torch.device = "cpu"
+        self, motor_steps: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Translate motor steps to a joint angle.
@@ -90,6 +92,8 @@ def motor_steps_to_angles(
         ----------
         motor_steps : torch.Tensor
             The motor steps.
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Raises
         ------
@@ -99,7 +103,7 @@ def motor_steps_to_angles(
         raise NotImplementedError("Must be overridden!")
 
     def angles_to_motor_steps(
-        self, angles: torch.Tensor, device: torch.device = "cpu"
+        self, angles: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Translate a joint angle to motor steps.
@@ -108,6 +112,8 @@ def angles_to_motor_steps(
         ----------
         angles : torch.Tensor
             The joint angles.
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Raises
         ------
@@ -116,7 +122,9 @@ def angles_to_motor_steps(
         """
         raise NotImplementedError("Must be overridden!")
 
-    def forward(self, actuator_pos: torch.Tensor) -> torch.Tensor:
+    def forward(
+        self, actuator_pos: torch.Tensor, device: Union[torch.device, str] = "cuda"
+    ) -> torch.Tensor:
         """
         Perform forward kinematic.
 
@@ -124,6 +132,8 @@ def forward(self, actuator_pos: torch.Tensor) -> torch.Tensor:
         ----------
         actuator_pos : torch.Tensor
             The position of the actuator.
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Raises
         ------
diff --git a/artist/field/actuator_array.py b/artist/field/actuator_array.py
index 54789cec..5bb33cc7 100644
--- a/artist/field/actuator_array.py
+++ b/artist/field/actuator_array.py
@@ -1,4 +1,5 @@
 import logging
+from typing import Union
 
 import torch
 
@@ -30,7 +31,7 @@ class ActuatorArray(torch.nn.Module):
     def __init__(
         self,
         actuator_list_config: ActuatorListConfig,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> None:
         """
         Initialize the actuator array.
@@ -44,10 +45,11 @@ def __init__(
         ----------
         actuator_list_config : ActuatorListConfig
             The configuration parameters for the actuators.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
         """
         super().__init__()
+        device = torch.device(device)
         actuator_array = []
         # Iterate through each actuator configuration in the list of actuator configurations.
         for i, actuator_config in enumerate(actuator_list_config.actuator_list):
diff --git a/artist/field/actuator_ideal.py b/artist/field/actuator_ideal.py
index ebaf40a8..d9c5c5cb 100644
--- a/artist/field/actuator_ideal.py
+++ b/artist/field/actuator_ideal.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 from artist.field.actuator import (
@@ -24,7 +26,7 @@ class IdealActuator(Actuator):
     """
 
     def motor_steps_to_angles(
-        self, motor_steps: torch.Tensor, device: torch.device = "cpu"
+        self, motor_steps: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Translate motor steps to a joint angle.
@@ -33,8 +35,8 @@ def motor_steps_to_angles(
         ----------
         motor_steps : torch.Tensor
             The motor steps.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -44,7 +46,7 @@ def motor_steps_to_angles(
         return motor_steps
 
     def angles_to_motor_steps(
-        self, angles: torch.Tensor, device: torch.device = "cpu"
+        self, angles: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Translate a joint angle to motor steps.
@@ -53,8 +55,8 @@ def angles_to_motor_steps(
         ----------
         angles : torch.Tensor
             The joint angles.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -64,7 +66,7 @@ def angles_to_motor_steps(
         return angles
 
     def forward(
-        self, actuator_pos: torch.Tensor, device: torch.device = "cpu"
+        self, actuator_pos: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Perform the forward kinematic for an ideal actuator.
@@ -73,8 +75,8 @@ def forward(
         ----------
         actuator_pos : torch.Tensor
             The position of the actuator.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
diff --git a/artist/field/actuator_linear.py b/artist/field/actuator_linear.py
index e5fb24a9..966beac3 100644
--- a/artist/field/actuator_linear.py
+++ b/artist/field/actuator_linear.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 from artist.field.actuator import Actuator
@@ -120,7 +122,7 @@ def steps_to_phi(self, actuator_pos: torch.Tensor) -> torch.Tensor:
         return angle
 
     def motor_steps_to_angles(
-        self, actuator_pos: torch.Tensor, device: torch.device = "cpu"
+        self, actuator_pos: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Calculate the angles given the motor steps.
@@ -129,14 +131,15 @@ def motor_steps_to_angles(
         ----------
         actuator_pos : torch.Tensor
             The actuator (motor) position.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The angles corresponding to the motor steps.
         """
+        device = torch.device(device)
         phi = self.steps_to_phi(actuator_pos=actuator_pos)
         phi_0 = self.steps_to_phi(
             actuator_pos=torch.zeros(actuator_pos.shape, device=device)
@@ -147,7 +150,7 @@ def motor_steps_to_angles(
         return angles
 
     def angles_to_motor_steps(
-        self, angles: torch.Tensor, device: torch.device = "cpu"
+        self, angles: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Calculate the motor steps given the angles.
@@ -156,14 +159,15 @@ def angles_to_motor_steps(
         ----------
         angles : torch.Tensor
             The angles.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The motor steps.
         """
+        device = torch.device(device)
         delta_phi = angles - self.phi_0 if self.clockwise else self.phi_0 - angles
 
         phi_0 = self.steps_to_phi(
@@ -179,7 +183,7 @@ def angles_to_motor_steps(
         return actuator_steps
 
     def forward(
-        self, actuator_pos: torch.Tensor, device: torch.device = "cpu"
+        self, actuator_pos: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Perform the forward kinematic.
@@ -188,12 +192,14 @@ def forward(
         ----------
         actuator_pos : torch.Tensor
             The actuator (motor) position.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The angles.
         """
-        return self.motor_steps_to_angles(actuator_pos=actuator_pos, device=device)
+        return self.motor_steps_to_angles(
+            actuator_pos=actuator_pos, device=torch.device(device)
+        )
diff --git a/artist/field/facets_nurbs.py b/artist/field/facets_nurbs.py
index f8f9de63..b155f160 100644
--- a/artist/field/facets_nurbs.py
+++ b/artist/field/facets_nurbs.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 from artist.util.nurbs import NURBSSurface
@@ -90,20 +92,23 @@ def __init__(
         self.canting_e = canting_e
         self.canting_n = canting_n
 
-    def create_nurbs_surface(self, device: torch.device = "cpu") -> NURBSSurface:
+    def create_nurbs_surface(
+        self, device: Union[torch.device, str] = "cuda"
+    ) -> NURBSSurface:
         """
         Create a NURBS surface to model a facet.
 
         Parameters
         ----------
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         NURBSSurface
             The NURBS surface of one facet.
         """
+        device = torch.device(device)
         # Since NURBS are only defined between (0,1), a small offset is required to exclude the boundaries from the
         # defined evaluation points.
         evaluation_points_rows = torch.linspace(
diff --git a/artist/field/heliostat.py b/artist/field/heliostat.py
index 33658ffe..f4e91863 100644
--- a/artist/field/heliostat.py
+++ b/artist/field/heliostat.py
@@ -1,5 +1,5 @@
 import logging
-from typing import Optional
+from typing import Optional, Union
 
 import h5py
 import torch
@@ -70,7 +70,7 @@ def __init__(
         surface_config: SurfaceConfig,
         kinematic_config: KinematicLoadConfig,
         actuator_config: ActuatorListConfig,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> None:
         """
         Implement the behavior of a heliostat.
@@ -95,10 +95,11 @@ def __init__(
             The configuration parameters to use for the heliostat kinematic.
         actuator_config : ActuatorListConfig
             The configuration parameters to use for the list of actuators.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
         """
         super().__init__()
+        device = torch.device(device)
         self.heliostat_id = heliostat_id
         self.position = position
         self.aim_point = aim_point
@@ -130,7 +131,7 @@ def from_hdf5(
         prototype_kinematic: Optional[KinematicLoadConfig] = None,
         prototype_actuator: Optional[ActuatorListConfig] = None,
         heliostat_name: Optional[str] = None,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> Self:
         """
         Class method to initialize a heliostat from an HDF5 file.
@@ -147,8 +148,8 @@ def from_hdf5(
             An optional prototype for the actuator configuration.
         heliostat_name : str, optional
             The name of the heliostat being loaded - used for logging.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -157,6 +158,7 @@ def from_hdf5(
         """
         if heliostat_name:
             log.info(f"Loading {heliostat_name} from an HDF5 file.")
+        device = torch.device(device)
         heliostat_id = int(config_file[config_dictionary.heliostat_id][()])
         position = torch.tensor(
             config_file[config_dictionary.heliostat_position][()],
@@ -752,7 +754,9 @@ def from_hdf5(
         )
 
     def set_aligned_surface(
-        self, incident_ray_direction: torch.Tensor, device: torch.device = "cpu"
+        self,
+        incident_ray_direction: torch.Tensor,
+        device: Union[torch.device, str] = "cuda",
     ) -> None:
         """
         Compute the aligned surface points and aligned surface normals of the heliostat.
@@ -761,9 +765,11 @@ def set_aligned_surface(
         ----------
         incident_ray_direction : torch.Tensor
             The incident ray direction.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
         """
+        device = torch.device(device)
+
         surface_points, surface_normals = self.surface.get_surface_points_and_normals(
             device=device
         )
diff --git a/artist/field/heliostat_field.py b/artist/field/heliostat_field.py
index c738a50e..7bcf6d8c 100644
--- a/artist/field/heliostat_field.py
+++ b/artist/field/heliostat_field.py
@@ -1,4 +1,5 @@
 import logging
+from typing import Union
 
 import h5py
 import torch.nn
@@ -54,7 +55,7 @@ def from_hdf5(
         prototype_surface: SurfaceConfig,
         prototype_kinematic: KinematicLoadConfig,
         prototype_actuator: ActuatorListConfig,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> Self:
         """
         Load a heliostat field from an HDF5 file.
@@ -69,8 +70,8 @@ def from_hdf5(
             The prototype for the kinematic configuration to be used if the heliostat has no individual kinematic.
         prototype_actuator : ActuatorListConfig
             The prototype for the actuator configuration to be used if the heliostat has no individual actuators.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -78,6 +79,7 @@ def from_hdf5(
             The heliostat field loaded from the HDF5 file.
         """
         log.info("Loading a heliostat field from an HDF5 file.")
+        device = torch.device(device)
         heliostat_list = [
             Heliostat.from_hdf5(
                 config_file=config_file[config_dictionary.heliostat_key][
diff --git a/artist/field/kinematic_rigid_body.py b/artist/field/kinematic_rigid_body.py
index 1011c1f1..ec6a80fa 100644
--- a/artist/field/kinematic_rigid_body.py
+++ b/artist/field/kinematic_rigid_body.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 from artist.field.actuator_array import ActuatorArray
@@ -67,7 +69,7 @@ def __init__(
             concentrator_tilt_n=torch.tensor(0.0),
             concentrator_tilt_u=torch.tensor(0.0),
         ),
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> None:
         """
         Initialize the rigid body kinematic.
@@ -89,11 +91,11 @@ def __init__(
             The initial orientation offsets of the kinematic (default: 0.0 for each possible offset).
         deviation_parameters : KinematicDeviations
             The deviation parameters for the kinematic (default: 0.0 for each deviation).
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
         """
         super().__init__(position=position, aim_point=aim_point)
-
+        device = torch.device(device)
         self.deviation_parameters = deviation_parameters
         for attr_name, attr_value in self.deviation_parameters.__dict__.items():
             if isinstance(attr_value, torch.Tensor):
@@ -115,7 +117,7 @@ def align(
         incident_ray_direction: torch.Tensor,
         max_num_iterations: int = 2,
         min_eps: float = 0.0001,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> torch.Tensor:
         """
         Compute the rotation matrix to align the heliostat along a desired orientation.
@@ -128,8 +130,8 @@ def align(
             Maximum number of iterations (default: 2).
         min_eps : float
             Convergence criterion (default: 0.0001).
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -139,7 +141,7 @@ def align(
         assert (
             len(self.actuators.actuator_list) == 2
         ), "The rigid body kinematic requires exactly two actuators, please check the configuration!"
-
+        device = torch.device(device)
         actuator_steps = torch.zeros((1, 2), requires_grad=True, device=device)
         orientation = None
         last_iteration_loss = None
@@ -315,7 +317,7 @@ def align_surface(
         incident_ray_direction: torch.Tensor,
         surface_points: torch.Tensor,
         surface_normals: torch.Tensor,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> tuple[torch.Tensor, torch.Tensor]:
         """
         Align given surface points and surface normals according to a calculated orientation.
@@ -328,8 +330,8 @@ def align_surface(
             Points on the surface of the heliostat that reflect the light.
         surface_normals : torch.Tensor
             Normals to the surface points.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -338,6 +340,8 @@ def align_surface(
         torch.Tensor
             The aligned surface normals.
         """
+        device = torch.device(device)
+
         orientation = self.align(incident_ray_direction, device=device).squeeze()
 
         aligned_surface_points = (orientation @ surface_points.unsqueeze(-1)).squeeze(
diff --git a/artist/field/receiver.py b/artist/field/receiver.py
index 4774d79e..1cd64a4e 100644
--- a/artist/field/receiver.py
+++ b/artist/field/receiver.py
@@ -1,5 +1,5 @@
 import logging
-from typing import Optional
+from typing import Optional, Union
 
 import h5py
 import torch.nn
@@ -97,7 +97,7 @@ def from_hdf5(
         cls,
         config_file: h5py.File,
         receiver_name: Optional[str] = None,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> Self:
         """
         Class method that initializes a receiver from an HDF5 file.
@@ -108,8 +108,8 @@ def from_hdf5(
             The HDF5 file containing the information about the receiver.
         receiver_name : str, optional
             The name of the receiver - used for logging
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -118,6 +118,7 @@ def from_hdf5(
         """
         if receiver_name:
             log.info(f"Loading {receiver_name} from an HDF5 file.")
+        device = torch.device(device)
         receiver_type = config_file[config_dictionary.receiver_type][()].decode("utf-8")
         position_center = torch.tensor(
             config_file[config_dictionary.receiver_position_center][()],
diff --git a/artist/field/receiver_field.py b/artist/field/receiver_field.py
index bc5de819..1fda479a 100644
--- a/artist/field/receiver_field.py
+++ b/artist/field/receiver_field.py
@@ -1,4 +1,5 @@
 import logging
+from typing import Union
 
 import h5py
 import torch.nn
@@ -42,7 +43,9 @@ def __init__(self, receiver_list: list[Receiver]):
         self.receiver_list = receiver_list
 
     @classmethod
-    def from_hdf5(cls, config_file: h5py.File, device: torch.device = "cpu") -> Self:
+    def from_hdf5(
+        cls, config_file: h5py.File, device: Union[torch.device, str] = "cuda"
+    ) -> Self:
         """
         Load a receiver field from an HDF5 file.
 
@@ -50,8 +53,8 @@ def from_hdf5(cls, config_file: h5py.File, device: torch.device = "cpu") -> Self
         ----------
         config_file : h5py.File
             The HDF5 file containing the configuration to be loaded.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -59,6 +62,7 @@ def from_hdf5(cls, config_file: h5py.File, device: torch.device = "cpu") -> Self
             The receiver field loaded from the HDF5 file.
         """
         log.info("Loading a receiver field from an HDF5 file.")
+        device = torch.device(device)
         receiver_field = [
             Receiver.from_hdf5(
                 config_file=config_file[config_dictionary.receiver_key][receiver_name],
diff --git a/artist/field/surface.py b/artist/field/surface.py
index 1adfb5d0..e43204ba 100644
--- a/artist/field/surface.py
+++ b/artist/field/surface.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 from artist.field.facets_nurbs import NurbsFacet
@@ -51,15 +53,15 @@ def __init__(self, surface_config: SurfaceConfig) -> None:
         ]
 
     def get_surface_points_and_normals(
-        self, device: torch.device = "cpu"
+        self, device: Union[torch.device, str] = "cuda"
     ) -> tuple[torch.Tensor, torch.Tensor]:
         """
         Calculate all surface points and normals from all facets.
 
         Parameters
         ----------
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -68,6 +70,7 @@ def get_surface_points_and_normals(
         torch.Tensor
             The surface normals.
         """
+        device = torch.device(device)
         eval_point_per_facet = (
             self.facets[0].number_eval_points_n * self.facets[0].number_eval_points_e
         )
diff --git a/artist/raytracing/heliostat_tracing.py b/artist/raytracing/heliostat_tracing.py
index 19d52580..c6e9faf0 100644
--- a/artist/raytracing/heliostat_tracing.py
+++ b/artist/raytracing/heliostat_tracing.py
@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Union
 
 if TYPE_CHECKING:
     from artist.scenario import Scenario
@@ -190,7 +190,9 @@ def __init__(
         )
 
     def trace_rays(
-        self, incident_ray_direction: torch.Tensor, device: torch.device = "cpu"
+        self,
+        incident_ray_direction: torch.Tensor,
+        device: Union[torch.device, str] = "cuda",
     ) -> torch.Tensor:
         """
         Perform heliostat raytracing.
@@ -202,14 +204,15 @@ def trace_rays(
         ----------
         incident_ray_direction : torch.Tensor
             The direction of the incident ray as seen from the heliostat.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The resulting bitmap.
         """
+        device = torch.device(device)
         final_bitmap = torch.zeros(
             (self.receiver.resolution_e, self.receiver.resolution_u), device=device
         )
@@ -254,7 +257,7 @@ def scatter_rays(
         self,
         distortion_u: torch.Tensor,
         distortion_e: torch.Tensor,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> Rays:
         """
         Scatter the reflected rays around the preferred ray direction.
@@ -265,14 +268,15 @@ def scatter_rays(
             The distortions in up direction (angles for scattering).
         distortion_e : torch.Tensor
             The distortions in east direction (angles for scattering).
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         Rays
             Scattered rays around the preferred direction.
         """
+        device = torch.device(device)
         ray_directions = self.heliostat.preferred_reflection_direction[
             :, :, :3
         ] / torch.linalg.norm(
@@ -308,7 +312,7 @@ def sample_bitmap(
         dx_ints: torch.Tensor,
         dy_ints: torch.Tensor,
         indices: torch.Tensor,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> torch.Tensor:
         """
         Sample a bitmap (flux density distribution of the reflected rays on the receiver).
@@ -323,14 +327,16 @@ def sample_bitmap(
             the y-axis.
         indices : torch.Tensor
             Index of the pixel.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The flux density distribution of the reflected rays on the receiver.
         """
+        device = torch.device(device)
+
         x_ints = dx_ints[indices] / self.receiver.plane_e * self.receiver.resolution_e
         y_ints = dy_ints[indices] / self.receiver.plane_u * self.receiver.resolution_u
 
diff --git a/artist/scenario.py b/artist/scenario.py
index 515bbf86..55258afa 100644
--- a/artist/scenario.py
+++ b/artist/scenario.py
@@ -1,4 +1,5 @@
 import logging
+from typing import Union
 
 import h5py
 import torch
@@ -71,7 +72,7 @@ def __init__(
 
     @classmethod
     def load_scenario_from_hdf5(
-        cls, scenario_file: h5py.File, device: torch.device = "cpu"
+        cls, scenario_file: h5py.File, device: Union[torch.device, str] = "cuda"
     ) -> Self:
         """
         Class method to load the scenario from an HDF5 file.
@@ -80,8 +81,8 @@ def load_scenario_from_hdf5(
         ----------
         scenario_file : h5py.File
             The config file containing all the information about the scenario being loaded.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -91,6 +92,7 @@ def load_scenario_from_hdf5(
         log.info(
             f"Loading an ``ARTIST`` scenario HDF5 file. This scenario file is version {scenario_file.attrs['version']}."
         )
+        device = torch.device(device)
         receivers = ReceiverField.from_hdf5(config_file=scenario_file, device=device)
         light_sources = LightSourceArray.from_hdf5(
             config_file=scenario_file, device=device
diff --git a/artist/scene/light_source_array.py b/artist/scene/light_source_array.py
index dc5080f3..8ae0ce32 100644
--- a/artist/scene/light_source_array.py
+++ b/artist/scene/light_source_array.py
@@ -1,4 +1,5 @@
 import logging
+from typing import Union
 
 import h5py
 import torch.nn
@@ -47,7 +48,9 @@ def __init__(self, light_source_list: list[LightSource]):
         self.light_source_list = light_source_list
 
     @classmethod
-    def from_hdf5(cls, config_file: h5py.File, device: torch.device = "cpu") -> Self:
+    def from_hdf5(
+        cls, config_file: h5py.File, device: Union[torch.device, str] = "cuda"
+    ) -> Self:
         """
         Load a light source array from an HDF5 file.
 
@@ -55,8 +58,8 @@ def from_hdf5(cls, config_file: h5py.File, device: torch.device = "cpu") -> Self
         ----------
         config_file : h5py.File
             The HDF5 file containing the configuration to be loaded.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -64,6 +67,7 @@ def from_hdf5(cls, config_file: h5py.File, device: torch.device = "cpu") -> Self
             The light source array loaded from the HDF5 file.
         """
         log.info("Loading a light source array from an HDF5 file.")
+        device = torch.device(device)
         light_source_array = []
         # Iterate through each light source configuration in the list of light source configurations.
         for ls in config_file[config_dictionary.light_source_key].keys():
diff --git a/artist/scene/sun.py b/artist/scene/sun.py
index ea25f427..648085c2 100644
--- a/artist/scene/sun.py
+++ b/artist/scene/sun.py
@@ -1,5 +1,5 @@
 import logging
-from typing import Any, Optional
+from typing import Any, Optional, Union
 
 import h5py
 import torch
@@ -41,7 +41,7 @@ def __init__(
         distribution_parameters: dict[str, Any] = dict(
             distribution_type="normal", mean=0.0, covariance=4.3681e-06
         ),
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> None:
         """
         Initialize the sun as a light source.
@@ -57,8 +57,8 @@ def __init__(
             The number of sent-out rays sampled from the sun distribution.
         distribution_parameters
             Parameters of the distribution used to model the sun.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Raises
         ------
@@ -66,6 +66,7 @@ def __init__(
             If the specified distribution type is unknown.
         """
         super().__init__(number_of_rays=number_of_rays)
+        device = torch.device(device)
 
         self.distribution_parameters = distribution_parameters
         self.number_of_rays = number_of_rays
@@ -120,7 +121,7 @@ def from_hdf5(
         cls,
         config_file: h5py.File,
         light_source_name: Optional[str] = None,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> Self:
         """
         Class method that initializes a sun from an HDF5 file.
@@ -131,8 +132,8 @@ def from_hdf5(
             The HDF5 file containing the information about the sun.
         light_source_name : str, optional
             The name of the light source - used for logging.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -141,6 +142,8 @@ def from_hdf5(
         """
         if light_source_name:
             log.info(f"Loading {light_source_name} from an HDF5 file.")
+        device = torch.device(device)
+
         number_of_rays = int(
             config_file[config_dictionary.light_source_number_of_rays][()]
         )
diff --git a/artist/util/nurbs.py b/artist/util/nurbs.py
index ae0cccf5..393ed84b 100644
--- a/artist/util/nurbs.py
+++ b/artist/util/nurbs.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 
@@ -41,7 +43,7 @@ def __init__(
         evaluation_points_e: torch.Tensor,
         evaluation_points_n: torch.Tensor,
         control_points: torch.Tensor,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> None:
         """
         Initialize a NURBS surface.
@@ -63,10 +65,11 @@ def __init__(
             The evaluation points in north direction.
         control_points : torch.Tensor
             The control_points.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
         """
         super().__init__()
+        device = torch.device(device)
         self.degree_e = degree_e
         self.degree_n = degree_n
         self.evaluation_points_e = evaluation_points_e
@@ -75,7 +78,7 @@ def __init__(
         self.knot_vector_e, self.knot_vector_n = self.calculate_knots(device)
 
     def calculate_knots(
-        self, device: torch.device = "cpu"
+        self, device: Union[torch.device, str] = "cuda"
     ) -> tuple[torch.Tensor, torch.Tensor]:
         """
         Calculate the knot vectors in the east and north direction.
@@ -88,8 +91,8 @@ def calculate_knots(
 
         Parameters
         ----------
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -98,6 +101,8 @@ def calculate_knots(
         torch.Tensor
             The knots in north direction.
         """
+        device = torch.device(device)
+
         num_control_points_e = self.control_points.shape[0]
         num_control_points_n = self.control_points.shape[1]
 
@@ -123,7 +128,7 @@ def find_span(
         evaluation_points: torch.Tensor,
         knot_vector: torch.Tensor,
         control_points: torch.Tensor,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> torch.Tensor:
         """
         Determine the knot span index for given evaluation points.
@@ -143,14 +148,15 @@ def find_span(
             The knot vector for the NURBS surface in a single direction.
         control_points : torch.Tensor
             The control points.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The knot span index.
         """
+        device = torch.device(device)
         n = control_points.shape[1] - 1
         span_indices = torch.zeros(
             len(evaluation_points), dtype=torch.int64, device=device
@@ -182,7 +188,7 @@ def basis_function_and_derivatives(
         span: torch.Tensor,
         degree: int,
         nth_derivative: int = 1,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> torch.Tensor:
         """
         Compute the nonzero derivatives of the basis functions up to the nth-derivative.
@@ -201,14 +207,16 @@ def basis_function_and_derivatives(
             The degree of the NURBS surface in one direction.
         nth_derivative : int
             Specifies how many derivatives are calculated (default: 1).
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The derivatives of the basis function.
         """
+        device = torch.device(device)
+
         num_evaluation_points = len(evaluation_points)
 
         # Introduce `ndu` to store the basis functions (called "n" in The NURBS book) and the knot differences (du).
@@ -292,15 +300,15 @@ def basis_function_and_derivatives(
         return derivatives
 
     def calculate_surface_points_and_normals(
-        self, device: torch.device = "cpu"
+        self, device: Union[torch.device, str] = "cuda"
     ) -> tuple[torch.Tensor, torch.Tensor]:
         """
         Calculate the surface points and normals of the NURBS surface.
 
         Parameters
         ----------
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -309,6 +317,8 @@ def calculate_surface_points_and_normals(
         torch.Tensor
             The surface normals.
         """
+        device = torch.device(device)
+
         nth_derivative = 1
 
         # Find span indices x direction (based on A2.1, p. 68).
diff --git a/artist/util/stral_to_surface_converter.py b/artist/util/stral_to_surface_converter.py
index 13f79351..28d8d7f4 100644
--- a/artist/util/stral_to_surface_converter.py
+++ b/artist/util/stral_to_surface_converter.py
@@ -2,6 +2,7 @@
 import struct
 import sys
 from pathlib import Path
+from typing import Union
 
 import colorlog
 import torch
@@ -105,7 +106,7 @@ def __init__(
 
     @staticmethod
     def convert_3d_points_to_4d_format(
-        point: torch.Tensor, device: torch.device = "cpu"
+        point: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Append ones to the last dimension of a 3D point vector.
@@ -116,14 +117,15 @@ def convert_3d_points_to_4d_format(
         ----------
         point : torch.Tensor
             Input point in a 3D format.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             Point vector with ones appended at the last dimension.
         """
+        device = torch.device(device)
         assert (
             point.size(dim=-1) == 3
         ), f"Expected a 3D point but got a point of shape {point.shape}!"
@@ -134,7 +136,7 @@ def convert_3d_points_to_4d_format(
 
     @staticmethod
     def convert_3d_direction_to_4d_format(
-        direction: torch.Tensor, device: torch.device = "cpu"
+        direction: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Append zeros to the last dimension of a 3D direction vector.
@@ -145,14 +147,15 @@ def convert_3d_direction_to_4d_format(
         ----------
         direction : torch.Tensor
             Input direction in a 3D format.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             Direction vector with ones appended at the last dimension.
         """
+        device = torch.device(device)
         assert (
             direction.size(dim=-1) == 3
         ), f"Expected a 3D direction vector but got a director vector of shape {direction.shape}!"
@@ -163,7 +166,7 @@ def convert_3d_direction_to_4d_format(
 
     @staticmethod
     def nwu_to_enu(
-        nwu_tensor: torch.Tensor, device: torch.device = "cpu"
+        nwu_tensor: torch.Tensor, device: Union[torch.device, str] = "cuda"
     ) -> torch.Tensor:
         """
         Cast the coordinate system from NWU to ENU.
@@ -172,14 +175,15 @@ def nwu_to_enu(
         ----------
         nwu_tensor : torch.Tensor
             The tensor in the NWU coordinate system.
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         torch.Tensor
             The converted tensor in the ENU coordinate system.
         """
+        device = torch.device(device)
         return torch.tensor(
             [-nwu_tensor[1], nwu_tensor[0], nwu_tensor[2]],
             dtype=torch.float,
@@ -223,7 +227,7 @@ def fit_nurbs_surface(
         tolerance: float = 1e-5,
         initial_learning_rate: float = 1e-1,
         max_epoch: int = 2500,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> NURBSSurface:
         """
         Generate a NURBS surface based on ``STRAL`` data.
@@ -256,14 +260,16 @@ def fit_nurbs_surface(
             Initial learning rate for the learning rate scheduler (default: 1e-1).
         max_epoch : int, optional
             Maximum number of epochs for optimization (default: 2500).
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
         NURBSSurface
             A NURBS surface.
         """
+        device = torch.device(device)
+
         # Normalize evaluation points and shift them so that they correspond to the knots.
         evaluation_points = surface_points.clone()
         evaluation_points[:, 2] = 0
@@ -365,7 +371,7 @@ def generate_surface_config_from_stral(
         tolerance: float = 1e-5,
         initial_learning_rate: float = 1e-1,
         max_epoch: int = 10000,
-        device: torch.device = "cpu",
+        device: Union[torch.device, str] = "cuda",
     ) -> list[FacetConfig]:
         """
         Generate a surface configuration from a ``STRAL`` file.
@@ -392,8 +398,8 @@ def generate_surface_config_from_stral(
             Initial learning rate for the learning rate scheduler used when fitting NURBS surfaces (default: 1e-1).
         max_epoch : int
             Maximum number of epochs to use when fitting NURBS surfaces (default: 10000).
-        device : torch.device
-            The device on which to initialize tensors (default is CPU).
+        device : Union[torch.device, str]
+            The device on which to initialize tensors (default is cuda).
 
         Returns
         -------
@@ -403,6 +409,7 @@ def generate_surface_config_from_stral(
         log.info(
             "Beginning generation of the surface configuration based on STRAL data."
         )
+        device = torch.device(device)
 
         # Create structures for reading ``STRAL`` file correctly.
         surface_header_struct = struct.Struct(self.surface_header_name)
diff --git a/artist/util/utils.py b/artist/util/utils.py
index 90818e3a..a68446f6 100644
--- a/artist/util/utils.py
+++ b/artist/util/utils.py
@@ -1,3 +1,5 @@
+from typing import Union
+
 import torch
 
 
@@ -22,7 +24,7 @@ def batch_dot(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 def rotate_distortions(
-    e: torch.Tensor, u: torch.Tensor, device: torch.device = "cpu"
+    e: torch.Tensor, u: torch.Tensor, device: Union[torch.device, str] = "cuda"
 ) -> torch.Tensor:
     """
     Rotate the distortions for the sun.
@@ -39,8 +41,8 @@ def rotate_distortions(
         East rotation angle in radians.
     u : torch.Tensor
         Up rotation angle in radians.
-    device : torch.device
-        The device on which to initialize tensors (default is CPU).
+    device : Union[torch.device, str]
+        The device on which to initialize tensors (default is cuda).
 
     Returns
     -------
@@ -50,6 +52,7 @@ def rotate_distortions(
     assert (
         e.shape == u.shape
     ), "The two tensors containing angles for the east and up rotation must have the same shape."
+    device = torch.device(device)
 
     cos_e = torch.cos(e)
     sin_e = -torch.sin(e)  # Heliostat convention
@@ -69,7 +72,9 @@ def rotate_distortions(
     ).permute(0, 3, 4, 1, 2)
 
 
-def rotate_e(e: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
+def rotate_e(
+    e: torch.Tensor, device: Union[torch.device, str] = "cuda"
+) -> torch.Tensor:
     """
     Rotate around the east axis.
 
@@ -82,14 +87,16 @@ def rotate_e(e: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
     ----------
     e : torch.Tensor
         East rotation angle in radians.
-    device : torch.device
-        The device on which to initialize tensors (default is CPU).
+    device : Union[torch.device, str]
+        The device on which to initialize tensors (default is cuda).
 
     Returns
     -------
     torch.Tensor
         Corresponding rotation matrix.
     """
+    device = torch.device(device)
+
     cos_e = torch.cos(e)
     sin_e = -torch.sin(e)  # Heliostat convention
     zeros = torch.zeros(e.shape, device=device)
@@ -104,7 +111,9 @@ def rotate_e(e: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
     ).squeeze(-1)
 
 
-def rotate_n(n: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
+def rotate_n(
+    n: torch.Tensor, device: Union[torch.device, str] = "cuda"
+) -> torch.Tensor:
     """
     Rotate around the north axis.
 
@@ -116,14 +125,16 @@ def rotate_n(n: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
     ----------
     n : torch.Tensor
         North rotation angle in radians.
-    device : torch.device
-        The device on which to initialize tensors (default is CPU).
+    device : Union[torch.device, str]
+        The device on which to initialize tensors (default is cuda).
 
     Returns
     -------
     torch.Tensor
         Corresponding rotation matrix.
     """
+    device = torch.device(device)
+
     cos_n = torch.cos(n)
     sin_n = torch.sin(n)
     zeros = torch.zeros(n.shape, device=device)
@@ -139,7 +150,9 @@ def rotate_n(n: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
     ).squeeze(-1)
 
 
-def rotate_u(u: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
+def rotate_u(
+    u: torch.Tensor, device: Union[torch.device, str] = "cuda"
+) -> torch.Tensor:
     """
     Rotate around the up axis.
 
@@ -151,14 +164,16 @@ def rotate_u(u: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
     ----------
     u : torch.Tensor
         Up rotation angle in radians.
-    device : torch.device
-        The device on which to initialize tensors (default is CPU).
+    device : Union[torch.device, str]
+        The device on which to initialize tensors (default is cuda).
 
     Returns
     -------
     torch.Tensor
         Corresponding rotation matrix.
     """
+    device = torch.device(device)
+
     cos_u = torch.cos(u)
     sin_u = torch.sin(u)
     zeros = torch.zeros(u.shape, device=device)
@@ -175,7 +190,10 @@ def rotate_u(u: torch.Tensor, device: torch.device = "cpu") -> torch.Tensor:
 
 
 def translate_enu(
-    e: torch.Tensor, n: torch.Tensor, u: torch.Tensor, device: torch.device = "cpu"
+    e: torch.Tensor,
+    n: torch.Tensor,
+    u: torch.Tensor,
+    device: Union[torch.device, str] = "cuda",
 ) -> torch.Tensor:
     """
     Translate in all directions.
@@ -191,8 +209,8 @@ def translate_enu(
         North translation.
     u : torch.Tensor
         Up translation.
-    device : torch.device
-        The device on which to initialize tensors (default is CPU).
+    device : Union[torch.device, str]
+        The device on which to initialize tensors (default is cuda).
 
     Returns
     -------
@@ -202,6 +220,7 @@ def translate_enu(
     assert (
         e.shape == u.shape == n.shape
     ), "The three tensors containing the east, north, and up translations must have the same shape."
+    device = torch.device(device)
 
     zeros = torch.zeros(e.shape, device=device)
     ones = torch.ones(e.shape, device=device)
diff --git a/scenarios/example_generate_individual_test_scenario.py b/scenarios/example_generate_individual_test_scenario.py
index 5b3c950d..68dd2097 100644
--- a/scenarios/example_generate_individual_test_scenario.py
+++ b/scenarios/example_generate_individual_test_scenario.py
@@ -25,7 +25,7 @@
 from artist.util.scenario_generator import ScenarioGenerator
 from artist.util.stral_to_surface_converter import StralToSurfaceConverter
 
-device = torch.device("cuda:3" if torch.cuda.is_available() else "cpu")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # The following parameter is the name of the scenario.
 file_path = "test_individual_measurements_scenario"
diff --git a/scenarios/example_generate_multiple_heliostat_scenario.py b/scenarios/example_generate_multiple_heliostat_scenario.py
index 6d8dab3d..931d02a7 100644
--- a/scenarios/example_generate_multiple_heliostat_scenario.py
+++ b/scenarios/example_generate_multiple_heliostat_scenario.py
@@ -22,7 +22,7 @@
 )
 from artist.util.scenario_generator import ScenarioGenerator
 
-device = torch.device("cuda:3" if torch.cuda.is_available() else "cpu")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # The following parameter is the name of the scenario.
 file_path = "multiple_heliostat_scenario"
diff --git a/scenarios/example_generate_test_scenario.py b/scenarios/example_generate_test_scenario.py
index 7075d813..58eedf7d 100644
--- a/scenarios/example_generate_test_scenario.py
+++ b/scenarios/example_generate_test_scenario.py
@@ -22,7 +22,7 @@
 from artist.util.scenario_generator import ScenarioGenerator
 from artist.util.stral_to_surface_converter import StralToSurfaceConverter
 
-device = torch.device("cuda:3" if torch.cuda.is_available() else "cpu")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # The following parameter is the name of the scenario.
 file_path = "test_scenario"
diff --git a/tests/field/test_integration_stral_data.py b/tests/field/test_integration_stral_data.py
index b924b254..8229111e 100644
--- a/tests/field/test_integration_stral_data.py
+++ b/tests/field/test_integration_stral_data.py
@@ -33,9 +33,21 @@
     rank = 0
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
@@ -78,6 +90,11 @@ def test_compute_bitmaps(
         The name of the scenario to be loaded.
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     torch.manual_seed(7)
     torch.cuda.manual_seed(7)
diff --git a/tests/field/test_linear_actuator.py b/tests/field/test_linear_actuator.py
index f998e81d..97ebf77e 100644
--- a/tests/field/test_linear_actuator.py
+++ b/tests/field/test_linear_actuator.py
@@ -13,15 +13,39 @@
 )
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
 @pytest.fixture
-def deviation_parameters(device: torch.device):
-    """Define deviation parameters used in tests."""
+def deviation_parameters(device: torch.device) -> KinematicDeviations:
+    """
+    Define deviation parameters used in tests.
+
+    Parameters
+    ----------
+    device : torch.device
+        The device on which to initialize tensors.
+
+    Returns
+    -------
+    KinematicDeviations
+        The deviation parameters.
+    """
     deviation_parameters = KinematicDeviations(
         first_joint_translation_e=torch.tensor(0.0, device=device),
         first_joint_translation_n=torch.tensor(0.0, device=device),
@@ -46,8 +70,20 @@ def deviation_parameters(device: torch.device):
 
 
 @pytest.fixture
-def actuator_configuration(device: torch.device):
-    """Define actuator parameters used in tests as measured experimentally."""
+def actuator_configuration(device: torch.device) -> ActuatorListConfig:
+    """
+    Define actuator parameters used in tests as measured experimentally.
+
+    Parameters
+    ----------
+    device : torch.device
+        The device on which to initialize tensors.
+
+    Returns
+    -------
+    ActuatorListConfig
+        A List containing parameters for each actuator.
+    """
     actuator1_parameters = ActuatorParameters(
         increment=torch.tensor(154166.666, device=device),
         initial_stroke_length=torch.tensor(0.075, device=device),
@@ -84,7 +120,7 @@ def kinematic_model_1(
     actuator_configuration: ActuatorListConfig,
     deviation_parameters: KinematicDeviations,
     device: torch.device,
-):
+) -> RigidBody:
     """
     Create a kinematic model to use in the test.
 
@@ -96,6 +132,11 @@ def kinematic_model_1(
         The kinematic deviations.
     device : torch.device
         The device on which to initialize tensors.
+
+    Returns
+    -------
+    RigidBody
+        The kinematic model.
     """
     position = torch.tensor([0.0, 0.0, 0.0, 1.0], device=device)
     aim_point = torch.tensor([0.0, -10.0, 0.0, 1.0], device=device)
@@ -113,7 +154,7 @@ def kinematic_model_2(
     actuator_configuration: ActuatorListConfig,
     deviation_parameters: KinematicDeviations,
     device: torch.device,
-):
+) -> RigidBody:
     """
     Create a kinematic model to use in the test.
 
@@ -125,6 +166,11 @@ def kinematic_model_2(
         The kinematic deviations.
     device : torch.device
         The device on which to initialize tensors.
+
+    Returns
+    -------
+    RigidBody
+        The kinematic model.
     """
     position = torch.tensor([0.0, 1.0, 0.0, 1.0], device=device)
     aim_point = torch.tensor([0.0, -9.0, 0.0, 1.0], device=device)
@@ -220,7 +266,7 @@ def test_orientation_matrix(
     incident_ray_direction: torch.Tensor,
     expected: torch.Tensor,
     device: torch.device,
-):
+) -> None:
     """
     Test that the alignment works as desired.
 
@@ -236,6 +282,11 @@ def test_orientation_matrix(
         The expected orientation matrix.
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     orientation_matrix = request.getfixturevalue(kinematic_model_fixture).align(
         incident_ray_direction.to(device), device=device
diff --git a/tests/field/test_only_nurbs.py b/tests/field/test_only_nurbs.py
index e45f06e6..313ccb15 100644
--- a/tests/field/test_only_nurbs.py
+++ b/tests/field/test_only_nurbs.py
@@ -4,9 +4,21 @@
 from artist.util.nurbs import NURBSSurface
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
@@ -30,6 +42,8 @@ def random_surface(
         The up coordinates.
     factor : float
         Factor determining how deformed the surface is.
+    device : torch.device
+        The device on which to initialize tensors.
 
     Returns
     -------
@@ -60,6 +74,11 @@ def test_nurbs(device: torch.device) -> None:
     ----------
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     torch.manual_seed(7)
     torch.cuda.manual_seed(7)
diff --git a/tests/field/test_rigid_body.py b/tests/field/test_rigid_body.py
index a9d67b5b..47663e26 100644
--- a/tests/field/test_rigid_body.py
+++ b/tests/field/test_rigid_body.py
@@ -14,15 +14,34 @@
 )
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
 @pytest.fixture
 def actuator_configuration() -> ActuatorListConfig:
-    """Define actuator parameters used in tests."""
+    """
+    Define actuator parameters used in tests.
+
+    Returns
+    -------
+    ActuatorListConfig
+        A List containing parameters for each actuator.
+    """
     actuator1_config = ActuatorConfig(
         actuator_key="",
         actuator_type=config_dictionary.ideal_actuator_key,
@@ -37,8 +56,20 @@ def actuator_configuration() -> ActuatorListConfig:
 
 
 @pytest.fixture
-def initial_offsets_south(device) -> KinematicOffsets:
-    """Define initial offsets for a south-orientated heliostat."""
+def initial_offsets_south(device: torch.device) -> KinematicOffsets:
+    """
+    Define initial offsets for a south-orientated heliostat.
+
+    Parameters
+    ----------
+    device : torch.device
+        The device on which to initialize tensors.
+
+    Returns
+    -------
+    KinematicOffsets
+        Initial kinematic offsets for a south-orientated heliostat.
+    """
     initial_offsets = KinematicOffsets(
         kinematic_initial_orientation_offset_e=torch.tensor(0.0, device=device),
         kinematic_initial_orientation_offset_n=torch.tensor(0.0, device=device),
@@ -48,8 +79,20 @@ def initial_offsets_south(device) -> KinematicOffsets:
 
 
 @pytest.fixture
-def initial_offsets_above(device) -> KinematicOffsets:
-    """Define initial offsets for an up-orientated heliostat."""
+def initial_offsets_above(device: torch.device) -> KinematicOffsets:
+    """
+    Define initial offsets for an up-orientated heliostat.
+
+    Parameters
+    ----------
+    device : torch.device
+        The device on which to initialize tensors.
+
+    Returns
+    -------
+    KinematicOffsets
+        Initial kinematic offsets for an up-orientated heliostat.
+    """
     initial_offsets = KinematicOffsets(
         kinematic_initial_orientation_offset_e=torch.tensor(math.pi / 2, device=device),
         kinematic_initial_orientation_offset_n=torch.tensor(0.0, device=device),
@@ -75,6 +118,11 @@ def kinematic_model_1(
         The kinematic initial orientation offsets.
     device : torch.device
         The device on which to initialize tensors.
+
+    Returns
+    -------
+    RigidBody
+        The kinematic model.
     """
     position = torch.tensor([0.0, 0.0, 0.0, 1.0], device=device)
     aim_point = torch.tensor([0.0, -10.0, 0.0, 1.0], device=device)
@@ -104,6 +152,11 @@ def kinematic_model_2(
         The kinematic initial orientation offsets.
     device : torch.device
         The device on which to initialize tensors.
+
+    Returns
+    -------
+    RigidBody
+        The kinematic model.
     """
     position = torch.tensor([0.0, 1.0, 0.0, 1.0], device=device)
     aim_point = torch.tensor([0.0, -9.0, 0.0, 1.0], device=device)
@@ -133,6 +186,11 @@ def kinematic_model_3(
         The kinematic initial orientation offsets.
     device : torch.device
         The device on which to initialize tensors.
+
+    Returns
+    -------
+    RigidBody
+        The kinematic model.
     """
     position = torch.tensor([0.0, 0.0, 0.0, 1.0], device=device)
     aim_point = torch.tensor([0.0, -10.0, 0.0, 1.0], device=device)
@@ -292,6 +350,11 @@ def test_orientation_matrix(
         The expected orientation matrix.
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     orientation_matrix = request.getfixturevalue(kinematic_model_fixture).align(
         incident_ray_direction.to(device), device=device
diff --git a/tests/raytracing/test_line_plane_intersection.py b/tests/raytracing/test_line_plane_intersection.py
index 34b45ff1..b325859c 100644
--- a/tests/raytracing/test_line_plane_intersection.py
+++ b/tests/raytracing/test_line_plane_intersection.py
@@ -6,9 +6,21 @@
 from artist.raytracing import raytracing_utils
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
@@ -90,6 +102,11 @@ def test_line_plane_intersection(
         The expected intersections between the rays and the plane, or ``None`` if no intersections are expected.
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     if expected_intersections is None:
         # Check if an AssertionError is thrown as expected.
diff --git a/tests/raytracing/test_reflect.py b/tests/raytracing/test_reflect.py
index 697f51e5..245bc899 100644
--- a/tests/raytracing/test_reflect.py
+++ b/tests/raytracing/test_reflect.py
@@ -4,9 +4,21 @@
 from artist.raytracing import raytracing_utils
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
@@ -63,6 +75,11 @@ def test_reflect_function(
         The expected direction of the reflected rays.
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     reflection = raytracing_utils.reflect(
         incoming_ray_direction=incoming_ray_direction.to(device),
diff --git a/tests/scene/test_light_source.py b/tests/scene/test_light_source.py
index ddc80863..997133b7 100644
--- a/tests/scene/test_light_source.py
+++ b/tests/scene/test_light_source.py
@@ -7,9 +7,21 @@
 from artist.util import config_dictionary
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
@@ -65,7 +77,14 @@ def calculate_expected(
 
 @pytest.fixture
 def distribution_parameters_1() -> Dict[str, Any]:
-    """Fixture that returns distribution parameters for the sun."""
+    """
+    Fixture that returns distribution parameters for the sun.
+
+    Returns
+    -------
+    Dict[str, Any]
+        Distribution parameters for the sun.
+    """
     return {
         config_dictionary.light_source_distribution_type: config_dictionary.light_source_distribution_is_normal,
         config_dictionary.light_source_mean: 0,
@@ -75,7 +94,14 @@ def distribution_parameters_1() -> Dict[str, Any]:
 
 @pytest.fixture
 def distribution_parameters_2() -> Dict[str, Any]:
-    """Fixture that returns distribution parameters for the sun."""
+    """
+    Fixture that returns distribution parameters for the sun.
+
+    Returns
+    -------
+    Dict[str, Any]
+        Distribution parameters for the sun.
+    """
     return {
         config_dictionary.light_source_distribution_type: config_dictionary.light_source_distribution_is_normal,
         config_dictionary.light_source_mean: 0,
@@ -85,7 +111,14 @@ def distribution_parameters_2() -> Dict[str, Any]:
 
 @pytest.fixture
 def distribution_parameters_3() -> Dict[str, Any]:
-    """Fixture that returns distribution parameters for the sun."""
+    """
+    Fixture that returns distribution parameters for the sun.
+
+    Returns
+    -------
+    Dict[str, Any]
+        Distribution parameters for the sun.
+    """
     return {
         config_dictionary.light_source_distribution_type: config_dictionary.light_source_distribution_is_normal,
         config_dictionary.light_source_mean: 10,
@@ -95,7 +128,14 @@ def distribution_parameters_3() -> Dict[str, Any]:
 
 @pytest.fixture
 def further_parameters_1() -> Dict[str, int]:
-    """Fixture that returns further test parameters."""
+    """
+    Fixture that returns further test parameters.
+
+    Returns
+    -------
+    Dict[str, int]
+        Further test parameters.
+    """
     return {
         "num_rays": 100,
         "num_points": 50,
@@ -107,7 +147,14 @@ def further_parameters_1() -> Dict[str, int]:
 
 @pytest.fixture
 def further_parameters_2() -> Dict[str, int]:
-    """Fixture that returns further test parameters."""
+    """
+    Fixture that returns further test parameters.
+
+    Returns
+    -------
+    Dict[str, int]
+        Further test parameters.
+    """
     return {
         "num_rays": 100,
         "num_points": 50,
@@ -119,7 +166,14 @@ def further_parameters_2() -> Dict[str, int]:
 
 @pytest.fixture
 def further_parameters_3() -> Dict[str, int]:
-    """Fixture that returns further test parameters."""
+    """
+    Fixture that returns further test parameters.
+
+    Returns
+    -------
+    Dict[str, int]
+        Further test parameters.
+    """
     return {
         "num_rays": 20,
         "num_points": 300,
@@ -165,6 +219,11 @@ def test_light_sources(
         The pytest fixture containing the further test parameters.
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     # Load further params dict.
     further_params_dict = request.getfixturevalue(further_parameters_fixture)
diff --git a/tests/util/test_distortion_rotations.py b/tests/util/test_distortion_rotations.py
index b3d94333..1a604fdf 100644
--- a/tests/util/test_distortion_rotations.py
+++ b/tests/util/test_distortion_rotations.py
@@ -6,9 +6,21 @@
 from artist.util.utils import rotate_distortions
 
 
-@pytest.fixture(params=["cpu", "cuda:3"] if torch.cuda.is_available() else ["cpu"])
+@pytest.fixture(params=["cpu", "cuda"] if torch.cuda.is_available() else ["cpu"])
 def device(request: pytest.FixtureRequest) -> torch.device:
-    """Return the device on which to initialize tensors."""
+    """
+    Return the device on which to initialize tensors.
+
+    Parameters
+    ----------
+    request : pytest.FixtureRequest
+        The pytest fixture used to consider different test cases.
+
+    Returns
+    -------
+    torch.device
+        The device on which to initialize tensors.
+    """
     return torch.device(request.param)
 
 
@@ -289,6 +301,11 @@ def test_distortion_rotations(
         The expected distorted rays after rotation.
     device : torch.device
         The device on which to initialize tensors.
+
+    Raises
+    ------
+    AssertionError
+        If test does not complete as expected.
     """
     distorted_rays = (
         rotate_distortions(