Add support for allocating qubits in decompose to cirq.unitary

cirq-core/cirq/protocols/apply_unitary_protocol.py

@@ -133,6 +133,33 @@ def default(
         state = qis.one_hot(index=(0,) * num_qubits, shape=qid_shape, dtype=np.complex128)
         return ApplyUnitaryArgs(state, np.empty_like(state), range(num_qubits))
 
+    @classmethod
+    def for_unitary(
+        cls, num_qubits: Optional[int] = None, *, qid_shape: Optional[Tuple[int, ...]] = None
+    ) -> 'ApplyUnitaryArgs':
+        """A default instance corresponding to an identity matrix.
+
+        Specify exactly one argument.
+
+        Args:
+            num_qubits: The number of qubits to make space for in the state.
+            qid_shape: A tuple representing the number of quantum levels of each
+                qubit the identity matrix applies to. `qid_shape` is (2, 2, 2) for
+                a three-qubit identity operation tensor.
+
+        Raises:
+            TypeError: If exactly neither `num_qubits` or `qid_shape` is provided or
+                both are provided.
+        """
+        if (num_qubits is None) == (qid_shape is None):
+            raise TypeError('Specify exactly one of num_qubits or qid_shape.')
+        if num_qubits is not None:
+            qid_shape = (2,) * num_qubits
+        qid_shape = cast(Tuple[int, ...], qid_shape)  # Satisfy mypy
+        num_qubits = len(qid_shape)
+        state = qis.eye_tensor(qid_shape, dtype=np.complex128)
+        return ApplyUnitaryArgs(state, np.empty_like(state), range(num_qubits))
+
     def with_axes_transposed_to_start(self) -> 'ApplyUnitaryArgs':
         """Returns a transposed view of the same arguments.
 
@@ -409,19 +436,7 @@ def _strat_apply_unitary_from_apply_unitary(
     return _incorporate_result_into_target(args, sub_args, sub_result)
 
 
-def _strat_apply_unitary_from_unitary(
-    unitary_value: Any, args: ApplyUnitaryArgs
-) -> Optional[np.ndarray]:
-    # Check for magic method.
-    method = getattr(unitary_value, '_unitary_', None)
-    if method is None:
-        return NotImplemented
-
-    # Attempt to get the unitary matrix.
-    matrix = method()
-    if matrix is NotImplemented or matrix is None:
-        return matrix
-
+def _apply_unitary_from_matrix(matrix: np.ndarray, unitary_value: Any, args: ApplyUnitaryArgs):
     if args.slices is None:
         val_qid_shape = qid_shape_protocol.qid_shape(unitary_value, default=(2,) * len(args.axes))
         slices = tuple(slice(0, size) for size in val_qid_shape)
@@ -450,11 +465,42 @@ def _strat_apply_unitary_from_unitary(
     return _incorporate_result_into_target(args, sub_args, sub_result)
 
 
+def _strat_apply_unitary_from_unitary(
+    unitary_value: Any, args: ApplyUnitaryArgs
+) -> Optional[np.ndarray]:
+    # Check for magic method.
+    method = getattr(unitary_value, '_unitary_', None)
+    if method is None:
+        return NotImplemented
+
+    # Attempt to get the unitary matrix.
+    matrix = method()
+    if matrix is NotImplemented or matrix is None:
+        return matrix
+
+    return _apply_unitary_from_matrix(matrix, unitary_value, args)
+
+
 def _strat_apply_unitary_from_decompose(val: Any, args: ApplyUnitaryArgs) -> Optional[np.ndarray]:
     operations, qubits, _ = _try_decompose_into_operations_and_qubits(val)
     if operations is None:
         return NotImplemented
-    return apply_unitaries(operations, qubits, args, None)
+    all_qubits = frozenset([q for op in operations for q in op.qubits])
+    ancilla = tuple(sorted(all_qubits.difference(qubits)))
+    if not len(ancilla):
+        return apply_unitaries(operations, qubits, args, None)
+    ordered_qubits = ancilla + tuple(qubits)
+    all_qid_shapes = qid_shape_protocol.qid_shape(ordered_qubits)
+    result = apply_unitaries(
+        operations, ordered_qubits, ApplyUnitaryArgs.for_unitary(qid_shape=all_qid_shapes), None
+    )
+    if result is None or result is NotImplemented:
+        return result
+    result = result.reshape((np.prod(all_qid_shapes, dtype=np.int64), -1))
+    val_qid_shape = qid_shape_protocol.qid_shape(qubits)
+    state_vec_length = np.prod(val_qid_shape, dtype=np.int64)
+    result = result[:state_vec_length, :state_vec_length]
+    return _apply_unitary_from_matrix(result, val, args)
 
 
 def apply_unitaries(

cirq-core/cirq/protocols/apply_unitary_protocol_test.py

@@ -717,3 +717,53 @@ def test_cast_to_complex():
         np.ComplexWarning, match='Casting complex values to real discards the imaginary part'
     ):
         cirq.apply_unitary(y0, args)
+
+
+class NotDecomposableGate(cirq.Gate):
+    def num_qubits(self):
+        return 1
+
+
+class DecomposableGate(cirq.Gate):
+    def __init__(self, sub_gate: cirq.Gate, allocate_ancilla: bool) -> None:
+        super().__init__()
+        self._sub_gate = sub_gate
+        self._allocate_ancilla = allocate_ancilla
+
+    def num_qubits(self):
+        return 1
+
+    def _decompose_(self, qubits):
+        if self._allocate_ancilla:
+            yield cirq.Z(cirq.NamedQubit('DecomposableGateQubit'))
+        yield self._sub_gate(qubits[0])
+
+
+def test_strat_apply_unitary_from_decompose():
+    state = np.eye(2, dtype=np.complex128)
+    args = cirq.ApplyUnitaryArgs(
+        target_tensor=state, available_buffer=np.zeros_like(state), axes=(0,)
+    )
+    np.testing.assert_allclose(
+        cirq.apply_unitaries(
+            [DecomposableGate(cirq.X, False)(cirq.LineQubit(0))], [cirq.LineQubit(0)], args
+        ),
+        [[0, 1], [1, 0]],
+    )
+
+    with pytest.raises(TypeError):
+        _ = cirq.apply_unitaries(
+            [DecomposableGate(NotDecomposableGate(), True)(cirq.LineQubit(0))],
+            [cirq.LineQubit(0)],
+            args,
+        )
+
+
+def test_unitary_construction():
+    with pytest.raises(TypeError):
+        _ = cirq.ApplyUnitaryArgs.for_unitary()
+
+    np.testing.assert_allclose(
+        cirq.ApplyUnitaryArgs.for_unitary(num_qubits=3).target_tensor,
+        cirq.eye_tensor((2,) * 3, dtype=np.complex128),
+    )

cirq-core/cirq/protocols/unitary_protocol.py

@@ -17,7 +17,6 @@
 import numpy as np
 from typing_extensions import Protocol
 
-from cirq import qis
 from cirq._doc import doc_private
 from cirq.protocols import qid_shape_protocol
 from cirq.protocols.apply_unitary_protocol import ApplyUnitaryArgs, apply_unitaries
@@ -162,9 +161,7 @@ def _strat_unitary_from_apply_unitary(val: Any) -> Optional[np.ndarray]:
         return NotImplemented
 
     # Apply unitary effect to an identity matrix.
-    state = qis.eye_tensor(val_qid_shape, dtype=np.complex128)
-    buffer = np.empty_like(state)
-    result = method(ApplyUnitaryArgs(state, buffer, range(len(val_qid_shape))))
+    result = method(ApplyUnitaryArgs.for_unitary(qid_shape=val_qid_shape))
 
     if result is NotImplemented or result is None:
         return result
@@ -179,15 +176,26 @@ def _strat_unitary_from_decompose(val: Any) -> Optional[np.ndarray]:
     if operations is None:
         return NotImplemented
 
+    all_qubits = frozenset(q for op in operations for q in op.qubits)
+    work_qubits = frozenset(qubits)
+    ancillas = tuple(sorted(all_qubits.difference(work_qubits)))
+
+    ordered_qubits = ancillas + tuple(qubits)
+    val_qid_shape = qid_shape_protocol.qid_shape(ancillas) + val_qid_shape
+
     # Apply sub-operations' unitary effects to an identity matrix.
-    state = qis.eye_tensor(val_qid_shape, dtype=np.complex128)
-    buffer = np.empty_like(state)
     result = apply_unitaries(
-        operations, qubits, ApplyUnitaryArgs(state, buffer, range(len(val_qid_shape))), None
+        operations, ordered_qubits, ApplyUnitaryArgs.for_unitary(qid_shape=val_qid_shape), None
     )
 
     # Package result.
     if result is None:
         return None
+
     state_len = np.prod(val_qid_shape, dtype=np.int64)
-    return result.reshape((state_len, state_len))
+    result = result.reshape((state_len, state_len))
+    # Assuming borrowable qubits are restored to their original state and
+    # clean qubits restord to the zero state then the desired unitary is
+    # the upper left square.
+    work_state_len = np.prod(val_qid_shape[len(ancillas) :], dtype=np.int64)
+    return result[:work_state_len, :work_state_len]

cirq-core/cirq/protocols/unitary_protocol_test.py

@@ -17,6 +17,7 @@
 import pytest
 
 import cirq
+from cirq import testing
 
 m0: np.ndarray = np.array([])
 # yapf: disable
@@ -188,6 +189,42 @@ def test_has_unitary():
     assert not cirq.has_unitary(FullyImplemented(False))
 
 
+def _test_gate_that_allocates_qubits(gate):
+    from cirq.protocols.unitary_protocol import _strat_unitary_from_decompose
+
+    op = gate.on(*cirq.LineQubit.range(cirq.num_qubits(gate)))
+    moment = cirq.Moment(op)
+    circuit = cirq.FrozenCircuit(op)
+    circuit_op = cirq.CircuitOperation(circuit)
+    for val in [gate, op, moment, circuit, circuit_op]:
+        unitary_from_strat = _strat_unitary_from_decompose(val)
+        assert unitary_from_strat is not None
+        np.testing.assert_allclose(unitary_from_strat, gate.narrow_unitary())
+
+
+@pytest.mark.parametrize('theta', np.linspace(0, 2 * np.pi, 10))
+@pytest.mark.parametrize('phase_state', [0, 1])
+@pytest.mark.parametrize('target_bitsize', [1, 2, 3])
+@pytest.mark.parametrize('ancilla_bitsize', [1, 4])
+def test_decompose_gate_that_allocates_clean_qubits(
+    theta: float, phase_state: int, target_bitsize: int, ancilla_bitsize: int
+):
+
+    gate = testing.PhaseUsingCleanAncilla(theta, phase_state, target_bitsize, ancilla_bitsize)
+    _test_gate_that_allocates_qubits(gate)
+
+
+@pytest.mark.parametrize('phase_state', [0, 1])
+@pytest.mark.parametrize('target_bitsize', [1, 2, 3])
+@pytest.mark.parametrize('ancilla_bitsize', [1, 4])
+def test_decompose_gate_that_allocates_dirty_qubits(
+    phase_state: int, target_bitsize: int, ancilla_bitsize: int
+):
+
+    gate = testing.PhaseUsingDirtyAncilla(phase_state, target_bitsize, ancilla_bitsize)
+    _test_gate_that_allocates_qubits(gate)
+
+
 def test_decompose_and_get_unitary():
     from cirq.protocols.unitary_protocol import _strat_unitary_from_decompose
 

cirq-core/cirq/testing/__init__.py

@@ -107,3 +107,5 @@
 )
 
 from cirq.testing.sample_circuits import nonoptimal_toffoli_circuit
+
+from cirq.testing.sample_gates import PhaseUsingCleanAncilla, PhaseUsingDirtyAncilla

cirq-core/cirq/testing/sample_gates.py

@@ -0,0 +1,79 @@
+# Copyright 2023 The Cirq Developers
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import dataclasses
+
+import cirq
+import numpy as np
+from cirq import ops, qis
+
+
+def _matrix_for_phasing_state(num_qubits, phase_state, phase):
+    matrix = qis.eye_tensor((2,) * num_qubits, dtype=np.complex128)
+    matrix = matrix.reshape((2**num_qubits, 2**num_qubits))
+    matrix[phase_state, phase_state] = phase
+    print(num_qubits, phase_state, phase)
+    print(matrix)
+    return matrix
+
+
+@dataclasses.dataclass(frozen=True)
+class PhaseUsingCleanAncilla(ops.Gate):
+    r"""Phases the state $|phase_state>$ by $\exp(1j * \pi * \theta)$ using one clean ancilla."""
+
+    theta: float
+    phase_state: int = 1
+    target_bitsize: int = 1
+    ancilla_bitsize: int = 1
+
+    def _num_qubits_(self):
+        return self.target_bitsize
+
+    def _decompose_(self, qubits):
+        anc = ops.NamedQubit.range(self.ancilla_bitsize, prefix="anc")
+        cv = [int(x) for x in f'{self.phase_state:0{self.target_bitsize}b}']
+        cnot_ladder = [cirq.CNOT(anc[i - 1], anc[i]) for i in range(1, self.ancilla_bitsize)]
+
+        yield ops.X(anc[0]).controlled_by(*qubits, control_values=cv)
+        yield [cnot_ladder, ops.Z(anc[-1]) ** self.theta, reversed(cnot_ladder)]
+        yield ops.X(anc[0]).controlled_by(*qubits, control_values=cv)
+
+    def narrow_unitary(self) -> np.ndarray:
+        """Narrowed unitary corresponding to the unitary effect applied on target qubits."""
+        phase = np.exp(1j * np.pi * self.theta)
+        return _matrix_for_phasing_state(self.target_bitsize, self.phase_state, phase)
+
+
+@dataclasses.dataclass(frozen=True)
+class PhaseUsingDirtyAncilla(ops.Gate):
+    r"""Phases the state $|phase_state>$ by -1 using one dirty ancilla."""
+
+    phase_state: int = 1
+    target_bitsize: int = 1
+    ancilla_bitsize: int = 1
+
+    def _num_qubits_(self):
+        return self.target_bitsize
+
+    def _decompose_(self, qubits):
+        anc = ops.NamedQubit.range(self.ancilla_bitsize, prefix="anc")
+        cv = [int(x) for x in f'{self.phase_state:0{self.target_bitsize}b}']
+        cnot_ladder = [cirq.CNOT(anc[i - 1], anc[i]) for i in range(1, self.ancilla_bitsize)]
+        yield ops.X(anc[0]).controlled_by(*qubits, control_values=cv)
+        yield [cnot_ladder, ops.Z(anc[-1]), reversed(cnot_ladder)]
+        yield ops.X(anc[0]).controlled_by(*qubits, control_values=cv)
+        yield [cnot_ladder, ops.Z(anc[-1]), reversed(cnot_ladder)]
+
+    def narrow_unitary(self) -> np.ndarray:
+        """Narrowed unitary corresponding to the unitary effect applied on target qubits."""
+        return _matrix_for_phasing_state(self.target_bitsize, self.phase_state, -1)

cirq-core/cirq/testing/sample_gates_test.py

@@ -0,0 +1,59 @@
+# Copyright 2023 The Cirq Developers
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pytest
+
+import numpy as np
+from cirq.testing import sample_gates
+import cirq
+
+
+@pytest.mark.parametrize('theta', np.linspace(0, 2 * np.pi, 20))
+def test_phase_using_clean_ancilla(theta: float):
+    g = sample_gates.PhaseUsingCleanAncilla(theta)
+    q = cirq.LineQubit(0)
+    qubit_order = cirq.QubitOrder.explicit([q], fallback=cirq.QubitOrder.DEFAULT)
+    decomposed_unitary = cirq.Circuit(cirq.decompose_once(g.on(q))).unitary(qubit_order=qubit_order)
+    phase = np.exp(1j * np.pi * theta)
+    np.testing.assert_allclose(g.narrow_unitary(), np.array([[1, 0], [0, phase]]))
+    np.testing.assert_allclose(
+        decomposed_unitary,
+        # fmt: off
+        np.array(
+            [
+                [1 , 0    , 0    , 0],
+                [0 , phase, 0    , 0],
+                [0 , 0    , phase, 0],
+                [0 , 0    , 0    , 1],
+            ]
+        ),
+        # fmt: on
+    )
+
+
+@pytest.mark.parametrize(
+    'target_bitsize, phase_state', [(1, 0), (1, 1), (2, 0), (2, 1), (2, 2), (2, 3)]
+)
+@pytest.mark.parametrize('ancilla_bitsize', [1, 4])
+def test_phase_using_dirty_ancilla(target_bitsize, phase_state, ancilla_bitsize):
+    g = sample_gates.PhaseUsingDirtyAncilla(phase_state, target_bitsize, ancilla_bitsize)
+    q = cirq.LineQubit.range(target_bitsize)
+    qubit_order = cirq.QubitOrder.explicit(q, fallback=cirq.QubitOrder.DEFAULT)
+    decomposed_circuit = cirq.Circuit(cirq.decompose_once(g.on(*q)))
+    decomposed_unitary = decomposed_circuit.unitary(qubit_order=qubit_order)
+    phase_matrix = np.eye(2**target_bitsize)
+    phase_matrix[phase_state, phase_state] = -1
+    np.testing.assert_allclose(g.narrow_unitary(), phase_matrix)
+    np.testing.assert_allclose(
+        decomposed_unitary, np.kron(phase_matrix, np.eye(2**ancilla_bitsize)), atol=1e-5
+    )