Support ZZPowGate when lowering from cirq

src/bloqade/cirq_utils/lowering.py

@@ -169,7 +169,6 @@ def main():
     | cirq.CSwapGate
     | cirq.XXPowGate
     | cirq.YYPowGate
-    | cirq.ZZPowGate
     | cirq.CCXPowGate
     | cirq.CCZPowGate
 )
@@ -523,6 +522,27 @@ def visit_CZPowGate(
             gate.stmts.CZ(controls=control_qarg, targets=target_qarg)
         )
 
+    def visit_ZZPowGate(
+        self, state: lowering.State[cirq.Circuit], node: cirq.GateOperation
+    ):
+        if node.gate.exponent % 2 == 0:
+            return
+
+        qubit1, qubit2 = node.qubits
+        qarg1 = self.lower_qubit_getindices(state, (qubit1,))
+        qarg2 = self.lower_qubit_getindices(state, (qubit2,))
+
+        if node.gate.exponent % 2 == 1:
+            state.current_frame.push(gate.stmts.X(qarg1))
+            state.current_frame.push(gate.stmts.X(qarg2))
+            return
+
+        # NOTE: arbitrary exponent, write as CX * Rz * CX (up to global phase)
+        state.current_frame.push(gate.stmts.CX(qarg1, qarg2))
+        angle = state.current_frame.push(py.Constant(0.5 * node.gate.exponent))
+        state.current_frame.push(gate.stmts.Rz(angle.result, qarg2))
+        state.current_frame.push(gate.stmts.CX(qarg1, qarg2))
+
     def visit_ControlledOperation(
         self, state: lowering.State[cirq.Circuit], node: cirq.ControlledOperation
     ):

test/cirq_utils/test_cirq_to_squin.py

@@ -1,6 +1,7 @@
 import math
 
 import cirq
+import numpy as np
 import pytest
 from kirin import types
 from kirin.passes import inline
@@ -414,3 +415,47 @@ def multi_arg(n: int, p: float):
 @pytest.mark.xfail
 def test_amplitude_damping():
     test_circuit(amplitude_damping)
+
+
+def test_trotter():
+
+    # NOTE: stolen from jonathan's tutorial
+    def trotter_layer(
+        qubits, dt: float = 0.01, J: float = 1, h: float = 1
+    ) -> cirq.Circuit:
+        """
+        Cirq builder function that returns a circuit of
+        a Trotter step of the 1D transverse Ising model
+        """
+        op_zz = cirq.ZZ ** (dt * J / math.pi)
+        op_x = cirq.X ** (dt * h / math.pi)
+        circuit = cirq.Circuit()
+        for i in range(0, len(qubits) - 1, 2):
+            circuit.append(op_zz.on(qubits[i], qubits[i + 1]))
+        for i in range(1, len(qubits) - 1, 2):
+            circuit.append(op_zz.on(qubits[i], qubits[i + 1]))
+        for i in range(len(qubits)):
+            circuit.append(op_x.on(qubits[i]))
+        return circuit
+
+    N = 4
+    steps = 10
+    dt = 0.01
+    J = 1
+    h = 1
+
+    qubits = cirq.LineQubit.range(N)
+    circuit = cirq.Circuit()
+    for _ in range(steps):
+        circuit += trotter_layer(qubits, dt, J, h)
+
+    main = load_circuit(circuit)
+
+    # actually run
+    cirq_statevector = cirq.Simulator().simulate(circuit).state_vector()
+    sim = DynamicMemorySimulator()
+    ket = sim.state_vector(main)
+
+    assert math.isclose(
+        np.abs(np.dot(np.conj(ket), cirq_statevector)) ** 2, 1.0, abs_tol=1e-3
+    )