Provide option to assume zero initial state in ansatz generation

qiskit_addon_aqc_tensor/ansatz_generation.py

@@ -118,7 +118,12 @@ def _nonidle_qubits(qc: QuantumCircuit, /):
     }
 
 
-def generate_ansatz_from_circuit(qc: QuantumCircuit, /) -> tuple[QuantumCircuit, list[float]]:
+def generate_ansatz_from_circuit(
+    qc: QuantumCircuit,
+    /,
+    *,
+    qubits_initially_zero=False,
+) -> tuple[QuantumCircuit, list[float]]:
     """Generate an ansatz from the two-qubit connectivity structure of a circuit."""
     # FIXME: handle classical bits, measurements, resets, and barriers.  maybe
     # conditions too?
@@ -138,7 +143,14 @@ def set_zxz_params_from_mat(q: int, mat) -> None:
         # Following the variable convention at
         # https://docs.quantum.ibm.com/api/qiskit/qiskit.synthesis.OneQubitEulerDecomposer
         theta, phi, lamb = decomposer.angles(mat)
-        for j, r in zip(free_params[q], (lamb, theta, phi)):
+        fp = free_params[q]
+        values: tuple[float, ...] = lamb, theta, phi
+        if len(fp) == 2:
+            # Must be initial gate, where the Z rotation has been dropped.
+            # This makes sense if we assume the input state to this ZXZ block
+            # is |0>.
+            values = values[1:]
+        for j, r in zip(fp, values):
             initial_params[j] = r
 
     def perform_separation(q0: int, q1: int):
@@ -164,8 +176,10 @@ def perform_separation(q0: int, q1: int):
 
     active_qubits = sorted([qc.find_bit(q)[0] for q in _nonidle_qubits(qc)])
     for q in active_qubits:
-        params, free_params[q] = _allocate_parameters(param_vec, 3)
-        initial_params.extend([np.nan] * 3)
+        params, free_params[q] = _allocate_parameters(param_vec, 2 if qubits_initially_zero else 3)
+        initial_params.extend([np.nan] * len(params))
+        if qubits_initially_zero:
+            params.insert(0, 0.0)
         ansatz.append(ZXZ(params), (q,))
         singles[q] = []
 

test/test_ansatz_generation.py

@@ -14,20 +14,28 @@
 import pytest
 from qiskit.circuit import QuantumCircuit
 from qiskit.circuit.random import random_circuit
-from qiskit.quantum_info import Operator, process_fidelity
+from qiskit.quantum_info import Operator, Statevector, process_fidelity, state_fidelity
 
 from qiskit_addon_aqc_tensor import generate_ansatz_from_circuit
 from qiskit_addon_aqc_tensor.ansatz_generation import KAK
 
 
-def test_ansatz_from_random_circuit():
+def test_ansatz_from_random_circuit_process_fidelity():
     qc = random_circuit(6, 4, max_operands=2)
     ansatz, initial_params = generate_ansatz_from_circuit(qc)
     ansatz.assign_parameters(initial_params, inplace=True)
     fidelity = process_fidelity(Operator(ansatz), Operator(qc))
     assert fidelity == pytest.approx(1)
 
 
+def test_ansatz_from_random_circuit_state_fidelity():
+    qc = random_circuit(6, 4, max_operands=2)
+    ansatz, initial_params = generate_ansatz_from_circuit(qc, qubits_initially_zero=True)
+    ansatz.assign_parameters(initial_params, inplace=True)
+    fidelity = state_fidelity(Statevector(ansatz), Statevector(qc))
+    assert fidelity == pytest.approx(1)
+
+
 def test_ansatz_fails_given_three_qubit_gate():
     qc = QuantumCircuit(3)
     qc.h(0)

test/test_aqc_workflows.py

@@ -52,7 +52,9 @@ def test_basic_workflow(available_backend_fixture, circuit_pair):
     target_mps = tensornetwork_from_circuit(target_circuit, simulator_settings)
     good_mps = tensornetwork_from_circuit(good_circuit, simulator_settings)
     initial_fidelity = abs(compute_overlap(good_mps, target_mps)) ** 2
-    ansatz, initial_parameters = generate_ansatz_from_circuit(good_circuit)
+    ansatz, initial_parameters = generate_ansatz_from_circuit(
+        good_circuit, qubits_initially_zero=True
+    )
     objective = OneMinusFidelity(target_mps, ansatz, simulator_settings)
     result = minimize(
         objective,