diff --git a/tests/test_state.py b/tests/test_state.py
index 1657b382..1b293668 100644
--- a/tests/test_state.py
+++ b/tests/test_state.py
@@ -619,3 +619,34 @@ class DerivedState(SimState):
     assert "is not allowed to be of type 'torch.Tensor | None' because torch.cat" in str(
         exc_info.value
     )
+
+
+def test_state_to_device_no_side_effects(si_sim_state: SimState) -> None:
+    """Test that SimState.to() doesn't modify the original state."""
+    # Store original values
+    original_positions = si_sim_state.positions.clone()
+    original_dtype = si_sim_state.dtype
+    original_device = si_sim_state.device
+
+    # Convert to different dtype
+    new_state = si_sim_state.to(dtype=torch.float64)
+
+    # Verify original state is unchanged
+    assert torch.allclose(si_sim_state.positions, original_positions), (
+        "Original state was modified!"
+    )
+    assert si_sim_state.dtype == original_dtype, "Original state dtype was changed!"
+    assert si_sim_state.device == original_device, "Original state device was changed!"
+    assert si_sim_state is not new_state, "New state is not a different object!"
+    assert new_state.dtype == torch.float64, "New state doesn't have correct dtype!"
+
+    # Test device conversion
+    if torch.cuda.is_available():
+        new_state_gpu = si_sim_state.to(device=torch.device("cuda"))
+        assert si_sim_state.device == original_device, (
+            "Original state device was changed!"
+        )
+        assert new_state_gpu.device.type == "cuda", (
+            "New state doesn't have correct device!"
+        )
+        assert si_sim_state is not new_state_gpu, "New state is not a different object!"
diff --git a/torch_sim/state.py b/torch_sim/state.py
index a04fa5d3..645761d6 100644
--- a/torch_sim/state.py
+++ b/torch_sim/state.py
@@ -367,7 +367,7 @@ def to(
         Returns:
             SimState: A new SimState with tensors on the specified device and dtype
         """
-        return state_to_device(self, device, dtype)
+        return _state_to_device(self, device, dtype)
 
     def __getitem__(self, system_indices: int | list[int] | slice | torch.Tensor) -> Self:
         """Enable standard Python indexing syntax for slicing batches.
@@ -552,7 +552,7 @@ def _normalize_system_indices(
     raise TypeError(f"Unsupported index type: {type(system_indices)}")
 
 
-def state_to_device[T: SimState](
+def _state_to_device[T: SimState](
     state: T, device: torch.device | None = None, dtype: torch.dtype | None = None
 ) -> T:
     """Convert the SimState to a new device and dtype.
@@ -856,7 +856,7 @@ def concatenate_states[T: SimState](  # noqa: C901
     for state in states:
         # Move state to target device if needed
         if state.device != target_device:
-            state = state_to_device(state, target_device)
+            state = state.to(target_device)
 
         # Collect per-atom properties
         for prop, val in get_attrs_for_scope(state, "per-atom"):
@@ -919,7 +919,7 @@ def initialize_state(
     # TODO: create a way to pass velocities from pmg and ase
 
     if isinstance(system, SimState):
-        return state_to_device(system, device, dtype)
+        return system.clone().to(device, dtype)
 
     if isinstance(system, list | tuple) and all(isinstance(s, SimState) for s in system):
         if not all(state.n_systems == 1 for state in system):