diff --git a/pennylane/devices/qubit/apply_operation.py b/pennylane/devices/qubit/apply_operation.py
index 6526bc22771..1fd21dfaee4 100644
--- a/pennylane/devices/qubit/apply_operation.py
+++ b/pennylane/devices/qubit/apply_operation.py
@@ -403,10 +403,16 @@ def apply_pauliz(op: qml.Z, state, is_state_batched: bool = False, debugger=None
 def apply_phaseshift(op: qml.PhaseShift, state, is_state_batched: bool = False, debugger=None, **_):
     """Apply PhaseShift to state."""
 
-    params = op.parameters[0]
+    axis = op.wires[0] + is_state_batched
+    n_dim = math.ndim(state)
+
+    if n_dim >= 9 and math.get_interface(state) == "tensorflow":
+        return apply_operation_tensordot(op, state, is_state_batched=is_state_batched)
+
+    params = qml.math.atleast_1d(op.parameters[0])
     if is_state_batched or (op.batch_size is not None and len(params) > 1):
         slices = []
-        for i, p in enumerate(op.parameters[0]):
+        for i, p in enumerate(params):
             slices.append(
                 apply_phaseshift(
                     qml.PhaseShift(p, wires=op.wires),
@@ -416,17 +422,11 @@ def apply_phaseshift(op: qml.PhaseShift, state, is_state_batched: bool = False,
             )
         return math.stack(slices, axis=0)
 
-    axis = op.wires[0] + is_state_batched
-    n_dim = math.ndim(state)
-
-    if n_dim >= 9 and math.get_interface(state) == "tensorflow":
-        return apply_operation_tensordot(op, state, is_state_batched=is_state_batched)
-
     sl_0 = _get_slice(0, axis, n_dim)
     sl_1 = _get_slice(1, axis, n_dim)
 
     # must be first state and then -1 because it breaks otherwise
-    state1 = math.multiply(state[sl_1], math.exp(1j * op.parameters[0]))
+    state1 = math.cast(state[sl_1], dtype=complex) * math.exp(1.0j * params)
     state = math.stack([state[sl_0], state1], axis=axis)
     if op.batch_size == 1:
         state = math.stack([state], axis=0)