diff --git a/chirho/dynamical/handlers/trace.py b/chirho/dynamical/handlers/trace.py
index ece0c9c2..a31f7bb0 100644
--- a/chirho/dynamical/handlers/trace.py
+++ b/chirho/dynamical/handlers/trace.py
@@ -1,3 +1,4 @@
+import functools
 from typing import Generic, TypeVar
 
 import pyro
@@ -9,7 +10,43 @@
 T = TypeVar("T")
 
 
+@functools.singledispatch
+def append(fst, rest: T) -> T:
+    raise NotImplementedError(f"append not implemented for type {type(fst)}.")
+
+
+@append.register(Trajectory)
+def append_trajectory(traj1: Trajectory[T], traj2: Trajectory[T]) -> Trajectory[T]:
+    if len(traj1.keys) == 0:
+        return traj2
+
+    if len(traj2.keys) == 0:
+        return traj1
+
+    if traj1.keys != traj2.keys:
+        raise ValueError(
+            f"Trajectories must have the same keys to be appended, but got {traj1.keys} and {traj2.keys}."
+        )
+
+    result: Trajectory[T] = Trajectory()
+    for k in traj1.keys:
+        setattr(result, k, append(getattr(traj1, k), getattr(traj2, k)))
+
+    return result
+
+
+@append.register(torch.Tensor)
+def append_tensor(prev_v: torch.Tensor, curr_v: torch.Tensor) -> torch.Tensor:
+    time_dim = -1  # TODO generalize to nontrivial event_shape
+    batch_shape = torch.broadcast_shapes(prev_v.shape[:-1], curr_v.shape[:-1])
+    prev_v = prev_v.expand(*batch_shape, *prev_v.shape[-1:])
+    curr_v = curr_v.expand(*batch_shape, *curr_v.shape[-1:])
+    return torch.cat([prev_v, curr_v], dim=time_dim)
+
+
 class DynamicTrace(Generic[T], pyro.poutine.messenger.Messenger):
+    trace: Trajectory[T]
+
     def __init__(self, logging_times: torch.Tensor, epsilon: float = 1e-6):
         # Adding epsilon to the logging times to avoid collision issues with the logging times being exactly on the
         #  boundaries of the simulation times. This is a hack, but it's a hack that should work for now.
@@ -23,8 +60,8 @@ def __init__(self, logging_times: torch.Tensor, epsilon: float = 1e-6):
 
         super().__init__()
 
-    def _reset(self):
-        self.trace = Trajectory()
+    def _reset(self) -> None:
+        self.trace: Trajectory[T] = Trajectory()
 
     def _pyro_simulate(self, msg) -> None:
         msg["done"] = True
@@ -51,7 +88,7 @@ def _pyro_post_simulate(self, msg) -> None:
             initial_state,
             timespan,
         )
-        self.trace.append(trajectory[..., 1:-1])
+        self.trace: Trajectory[T] = append(self.trace, trajectory[..., 1:-1])
         if len(self.trace) > len(self.logging_times):
             raise ValueError(
                 "Multiple simulates were used with a single DynamicTrace handler."
diff --git a/chirho/dynamical/ops/dynamical.py b/chirho/dynamical/ops/dynamical.py
index 1e23b562..ea98c0ab 100644
--- a/chirho/dynamical/ops/dynamical.py
+++ b/chirho/dynamical/ops/dynamical.py
@@ -120,10 +120,6 @@ def _getitem_torchmask(self, key: torch.Tensor) -> "Trajectory[T]":
 
         return self._getitem(key)
 
-    @functools.singledispatchmethod
-    def append(self, other: T):
-        raise NotImplementedError(f"append not implemented for type {type(other)}")
-
     def to_state(self) -> State[T]:
         ret: State[T] = State(
             # TODO support event_dim > 0
@@ -132,34 +128,6 @@ def to_state(self) -> State[T]:
         return ret
 
 
-# TODO: figure out parameteric types of Trajectory.
-# This used torch methods in supposedly generic class.
-@Trajectory.append.register(Trajectory)  # type: ignore
-def _append_trajectory(self, other: Trajectory):
-    # If self is empty, just copy other.
-    if len(self.keys) == 0:
-        for k in other.keys:
-            setattr(self, k, getattr(other, k))
-        return
-
-    if self.keys != other.keys:
-        raise ValueError(
-            f"Trajectories must have the same keys to be appended, but got {self.keys} and {other.keys}."
-        )
-    for k in self.keys:
-        prev_v = getattr(self, k)
-        curr_v = getattr(other, k)
-        time_dim = -1  # TODO generalize to nontrivial event_shape
-        batch_shape = torch.broadcast_shapes(prev_v.shape[:-1], curr_v.shape[:-1])
-        prev_v = prev_v.expand(*batch_shape, *prev_v.shape[-1:])
-        curr_v = curr_v.expand(*batch_shape, *curr_v.shape[-1:])
-        setattr(
-            self,
-            k,
-            torch.cat([prev_v, curr_v], dim=time_dim),
-        )
-
-
 @runtime_checkable
 class Dynamics(Protocol[S, T]):
     diff: Callable[[State[S], State[S]], T]
diff --git a/tests/dynamical/test_state_trajectory.py b/tests/dynamical/test_state_trajectory.py
index ed8f2293..3065a3a4 100644
--- a/tests/dynamical/test_state_trajectory.py
+++ b/tests/dynamical/test_state_trajectory.py
@@ -2,6 +2,7 @@
 
 import torch
 
+from chirho.dynamical.handlers.trace import append
 from chirho.dynamical.ops import Trajectory
 
 logger = logging.getLogger(__name__)
@@ -16,7 +17,7 @@ def test_trajectory_methods():
 def test_append():
     trajectory1 = Trajectory(S=torch.tensor([1.0, 2.0, 3.0]))
     trajectory2 = Trajectory(S=torch.tensor([4.0, 5.0, 6.0]))
-    trajectory1.append(trajectory2)
+    trajectory = append(trajectory1, trajectory2)
     assert torch.allclose(
-        trajectory1.S, torch.tensor([1.0, 2.0, 3.0, 4.0, 5.0, 6.0])
-    ), "Trajectory.append() failed to append a trajectory"
+        trajectory.S, torch.tensor([1.0, 2.0, 3.0, 4.0, 5.0, 6.0])
+    ), "append() failed to append a trajectory"