Set default unitary precision np.complex64 (quantumlib#5426)

Author: dabacon

cirq-core/cirq/circuits/circuit.py

@@ -998,7 +998,7 @@ def unitary(
         qubit_order: 'cirq.QubitOrderOrList' = ops.QubitOrder.DEFAULT,
         qubits_that_should_be_present: Iterable['cirq.Qid'] = (),
         ignore_terminal_measurements: bool = True,
-        dtype: Type[np.number] = np.complex128,
+        dtype: Type[np.number] = np.complex64,
     ) -> np.ndarray:
         """Converts the circuit into a unitary matrix, if possible.
 
@@ -1013,11 +1013,10 @@ def unitary(
             ignore_terminal_measurements: When set, measurements at the end of
                 the circuit are ignored instead of causing the method to
                 fail.
-            dtype: The numpy dtype for the returned unitary. Defaults to
-                np.complex128. Specifying np.complex64 will run faster at the
-                cost of precision. `dtype` must be a complex np.dtype, unless
-                all operations in the circuit have unitary matrices with
-                exclusively real coefficients (e.g. an H + TOFFOLI circuit).
+            dtype: The numpy dtype for the returned unitary. `dtype` must be
+                a complex np.dtype, unless all operations in the circuit have
+                unitary matrices with exclusively real coefficients
+                (e.g. an H + TOFFOLI circuit).
 
         Returns:
             A (possibly gigantic) 2d numpy array corresponding to a matrix

cirq-core/cirq/contrib/acquaintance/executor_test.py

@@ -119,7 +119,9 @@ def test_executor_random(
     circuit.append(cca.LinearPermutationGate(num_qubits, permutation)(*qubits))
     actual_unitary = circuit.unitary()
 
-    np.testing.assert_allclose(actual=actual_unitary, desired=expected_unitary, verbose=True)
+    np.testing.assert_allclose(
+        actual=actual_unitary, desired=expected_unitary, verbose=True, atol=1e-6
+    )
 
 
 def test_acquaintance_operation():

cirq-core/cirq/contrib/paulistring/clifford_optimize_test.py

@@ -121,4 +121,4 @@ def test_optimize_large_circuit():
 
     c_opt = clifford_optimized_circuit(c_orig)
 
-    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-7)
+    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-6)

cirq-core/cirq/contrib/paulistring/convert_gate_set.py

@@ -21,8 +21,7 @@ def converted_gate_set(
     circuit: circuits.Circuit, no_clifford_gates: bool = False, atol: float = 1e-8
 ) -> circuits.Circuit:
     """Returns a new, equivalent circuit using the gate set
-    {SingleQubitCliffordGate,
-    CZ/PauliInteractionGate, PauliStringPhasor}.
+    {SingleQubitCliffordGate, CZ/PauliInteractionGate, PauliStringPhasor}.
     """
     conv_circuit = transformers.optimize_for_target_gateset(
         circuit, gateset=transformers.CZTargetGateset()

cirq-core/cirq/contrib/paulistring/optimize_test.py

@@ -48,7 +48,7 @@ def test_optimize():
 
     c_opt = optimized_circuit(c_orig)
 
-    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-7)
+    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-6)
 
     cirq.testing.assert_has_diagram(
         c_opt,
@@ -68,7 +68,7 @@ def test_optimize_large_circuit():
 
     c_opt = optimized_circuit(c_orig)
 
-    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-7)
+    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-6)
 
     assert (
         sum(
@@ -86,7 +86,7 @@ def test_repeat_limit():
 
     c_opt = optimized_circuit(c_orig, repeat=1)
 
-    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-7)
+    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-6)
 
     assert (
         sum(

cirq-core/cirq/contrib/paulistring/pauli_string_dag_test.py

@@ -26,5 +26,5 @@ def test_pauli_string_dag_from_circuit():
     c_left_reordered = c_left_dag.to_circuit()
 
     cirq.testing.assert_allclose_up_to_global_phase(
-        c_left.unitary(), c_left_reordered.unitary(), atol=1e-7
+        c_left.unitary(), c_left_reordered.unitary(), atol=1e-6
     )

cirq-core/cirq/contrib/paulistring/pauli_string_optimize_test.py

@@ -36,9 +36,9 @@ def test_optimize():
 
     c_opt = pauli_string_optimized_circuit(c_orig)
 
-    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-7)
-
-    assert c_opt == c_expected
+    cirq.testing.assert_allclose_up_to_global_phase(
+        c_orig.unitary(), c_expected.unitary(), atol=1e-6
+    )
 
     cirq.testing.assert_has_diagram(
         c_opt,
@@ -81,4 +81,4 @@ def test_optimize_large_circuit():
 
     c_opt = pauli_string_optimized_circuit(c_orig)
 
-    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-7)
+    cirq.testing.assert_allclose_up_to_global_phase(c_orig.unitary(), c_opt.unitary(), atol=1e-6)

cirq-core/cirq/contrib/paulistring/separate_test.py

@@ -23,7 +23,7 @@ def test_toffoli_separate():
     c_left, c_right = convert_and_separate_circuit(circuit)
 
     cirq.testing.assert_allclose_up_to_global_phase(
-        circuit.unitary(), (c_left + c_right).unitary(), atol=1e-7
+        circuit.unitary(), (c_left + c_right).unitary(), atol=1e-6
     )
 
     assert all(isinstance(op, cirq.PauliStringPhasor) for op in c_left.all_operations())

cirq-core/cirq/contrib/qasm_import/qasm_test.py

@@ -51,6 +51,6 @@ def test_consistency_with_qasm_output_and_qiskit():
     circuit2 = circuit_from_qasm(qasm)
 
     cirq_unitary = cirq.unitary(circuit2)
-    ct.assert_allclose_up_to_global_phase(cirq_unitary, cirq.unitary(circuit1), atol=1e-8)
+    ct.assert_allclose_up_to_global_phase(cirq_unitary, cirq.unitary(circuit1), atol=1e-6)
 
     cq.assert_qiskit_parsed_qasm_consistent_with_unitary(qasm, cirq_unitary)

cirq-core/cirq/ion/convert_to_ion_gates_test.py

@@ -71,7 +71,7 @@ def test_convert_to_ion_gates():
         atol=1e-4,
     )
     assert cirq.allclose_up_to_global_phase(
-        cirq.unitary(cirq.Circuit(rcnot)), cirq.unitary(OtherCNOT().on(q0, q1))
+        cirq.unitary(cirq.Circuit(rcnot)), cirq.unitary(OtherCNOT().on(q0, q1)), atol=1e-6
     )
 
 

cirq-core/cirq/linalg/decompositions.py

@@ -549,6 +549,8 @@ def scatter_plot_normalized_kak_interaction_coefficients(
     *,
     include_frame: bool = True,
     ax: Optional[plt.Axes] = None,
+    rtol: float = 1e-5,
+    atol: float = 1e-6,
     **kwargs,
 ):
     r"""Plots the interaction coefficients of many two-qubit operations.
@@ -590,6 +592,13 @@ def scatter_plot_normalized_kak_interaction_coefficients(
             wireframe. Defaults to `True`.
         ax: A matplotlib 3d axes object to plot into. If not specified, a new
             figure is created, plotted, and shown.
+        rtol: Per-matrix-entry relative tolerance on equality used if the
+            kak decomposition is calculated from the `interactions`.
+        atol: Per-matrix-entry absolute tolerance on equality used if the
+            kak decomposition is calculated from the `interaction`s. T
+            This determines how close $k_x$  must be to π/4 to guarantee
+            $k_z$ ≥ 0. Must be non-negative.
+
         **kwargs: Arguments forwarded into the call to `scatter` that plots the
             points. Working arguments include color `c='blue'`, scale `s=2`,
             labelling `label="theta=pi/4"`, etc. For reference see the
@@ -662,7 +671,7 @@ def coord_transform(
     else:
         interactions_extracted = [interactions]
 
-    points = kak_vector(interactions_extracted) * 4 / np.pi
+    points = kak_vector(interactions_extracted, rtol=rtol, atol=atol) * 4 / np.pi
 
     ax.scatter(*coord_transform(points), **kwargs)
     ax.set_xlim(0, +1)
@@ -810,7 +819,7 @@ def kak_decomposition(
     ],
     *,
     rtol: float = 1e-5,
-    atol: float = 1e-8,
+    atol: float = 1e-6,
     check_preconditions: bool = True,
 ) -> KakDecomposition:
     """Decomposes a 2-qubit unitary into 1-qubit ops and XX/YY/ZZ interactions.
@@ -848,9 +857,7 @@ def kak_decomposition(
     if check_preconditions and (
         mat.shape != (4, 4) or not predicates.is_unitary(mat, rtol=rtol, atol=atol)
     ):
-        raise ValueError(
-            'Input must correspond to a 4x4 unitary matrix. Received matrix:\n' + str(mat)
-        )
+        raise ValueError(f'Input must correspond to a 4x4 unitary matrix. Received matrix:\n{mat}')
 
     # Diagonalize in magic basis.
     left, d, right = diagonalize.bidiagonalize_unitary_with_special_orthogonals(
@@ -948,7 +955,7 @@ def kak_vector(
 
     if check_preconditions:
         actual = np.einsum('...ba,...bc', unitary.conj(), unitary) - np.eye(4)
-        if not np.allclose(actual, np.zeros_like(actual), rtol, atol):
+        if not np.allclose(np.zeros_like(actual), actual, rtol=rtol, atol=atol):
             raise ValueError(
                 'Input must correspond to a 4x4 unitary matrix or tensor of '
                 f'unitary matrices. Received input:\n{unitary}'

cirq-core/cirq/linalg/decompositions_test.py

@@ -738,15 +738,17 @@ def test_kak_vector_input_not_unitary():
 def test_kak_decompose(unitary: np.ndarray):
     kak = cirq.kak_decomposition(unitary)
     circuit = cirq.Circuit(kak._decompose_(cirq.LineQubit.range(2)))
-    np.testing.assert_allclose(cirq.unitary(circuit), unitary, atol=1e-8)
+    np.testing.assert_allclose(cirq.unitary(circuit), unitary, atol=1e-6)
     assert len(circuit) == 5
     assert len(list(circuit.all_operations())) == 8
 
 
 def test_num_two_qubit_gates_required():
     for i in range(4):
         assert (
-            cirq.num_cnots_required(cirq.testing.random_two_qubit_circuit_with_czs(i).unitary())
+            cirq.num_cnots_required(
+                cirq.testing.random_two_qubit_circuit_with_czs(i).unitary(), atol=1e-6
+            )
             == i
         )
 
@@ -759,7 +761,7 @@ def test_num_two_qubit_gates_required_invalid():
 
 
 @pytest.mark.parametrize(
-    "U",
+    "u",
     [
         cirq.testing.random_two_qubit_circuit_with_czs(3).unitary(),
         # an example where gamma(special(u))=I, so the denominator becomes 0
@@ -776,8 +778,8 @@ def test_num_two_qubit_gates_required_invalid():
         ),
     ],
 )
-def test_extract_right_diag(U):
-    assert cirq.num_cnots_required(U) == 3
-    diag = cirq.linalg.extract_right_diag(U)
+def test_extract_right_diag(u):
+    assert cirq.num_cnots_required(u) == 3
+    diag = cirq.linalg.extract_right_diag(u)
     assert cirq.is_diagonal(diag)
-    assert cirq.num_cnots_required(U @ diag) == 2
+    assert cirq.num_cnots_required(u @ diag, atol=1e-6) == 2

cirq-core/cirq/ops/diagonal_gate_test.py

@@ -52,7 +52,9 @@ def test_decomposition_unitary(n):
     expected_f = [np.exp(1j * angle) for angle in diagonal_angles]
     decomposed_f = cirq.unitary(decomposed_circ).diagonal()
 
-    np.testing.assert_allclose(decomposed_f, expected_f)
+    # For large qubit counts, the decomposed circuit is rather large, so we lose a lot of
+    # precision.
+    np.testing.assert_allclose(decomposed_f, expected_f, atol=5e-6)
 
 
 @pytest.mark.parametrize('n', [1, 2, 3, 4])
@@ -63,7 +65,7 @@ def test_diagonal_exponent(n):
     sqrt_diagonal_gate = diagonal_gate**0.5
 
     expected_angles = [prime / 2 for prime in diagonal_angles]
-    np.testing.assert_allclose(expected_angles, sqrt_diagonal_gate._diag_angles_radians, atol=1e-8)
+    np.testing.assert_allclose(expected_angles, sqrt_diagonal_gate._diag_angles_radians, atol=1e-6)
 
     assert cirq.pow(cirq.DiagonalGate(diagonal_angles), "test", None) is None
 
@@ -78,7 +80,7 @@ def test_decomposition_diagonal_exponent(n):
     expected_f = [np.exp(1j * angle / 2) for angle in diagonal_angles]
     decomposed_f = cirq.unitary(decomposed_circ).diagonal()
 
-    np.testing.assert_allclose(decomposed_f, expected_f)
+    np.testing.assert_allclose(decomposed_f, expected_f, atol=1e-6)
 
 
 @pytest.mark.parametrize('n', [1, 2, 3, 4])
@@ -97,7 +99,7 @@ def test_decomposition_with_parameterization(n):
             resolved_op = cirq.resolve_parameters(parameterized_op, resolver)
             resolved_circuit = cirq.resolve_parameters(decomposed_circuit, resolver)
             np.testing.assert_allclose(
-                cirq.unitary(resolved_op), cirq.unitary(resolved_circuit), atol=1e-8
+                cirq.unitary(resolved_op), cirq.unitary(resolved_circuit), atol=1e-6
             )
 
 

cirq-core/cirq/ops/fsim_gate_test.py

@@ -317,7 +317,7 @@ def test_phased_fsim_from_fsim_rz(theta, phi, rz_angles_before, rz_angles_after)
         cirq.rz(rz_angles_after[0]).on(q0),
         cirq.rz(rz_angles_after[1]).on(q1),
     )
-    cirq.testing.assert_allclose_up_to_global_phase(cirq.unitary(f), cirq.unitary(c), atol=1e-8)
+    cirq.testing.assert_allclose_up_to_global_phase(cirq.unitary(f), cirq.unitary(c), atol=1e-6)
 
 
 @pytest.mark.parametrize(

cirq-core/cirq/ops/matrix_gates.py

@@ -56,7 +56,7 @@ def __init__(
         name: str = None,
         qid_shape: Optional[Iterable[int]] = None,
         unitary_check_rtol: float = 1e-5,
-        unitary_check_atol: float = 1e-8,
+        unitary_check_atol: float = 1e-6,
     ) -> None:
         """Initializes a matrix gate.
 

cirq-core/cirq/ops/parallel_gate_test.py

@@ -119,7 +119,7 @@ def test_unitary(gate, num_copies, qubits):
     step = gate.num_qubits()
     qubit_lists = [qubits[i * step : (i + 1) * step] for i in range(num_copies)]
     np.testing.assert_allclose(
-        cirq.unitary(g), cirq.unitary(cirq.Circuit(gate.on_each(qubit_lists))), atol=1e-8
+        cirq.unitary(g), cirq.unitary(cirq.Circuit(gate.on_each(qubit_lists))), atol=1e-6
     )
 
 

cirq-core/cirq/ops/phased_x_gate_test.py

@@ -176,7 +176,7 @@ def test_parameterize(resolve_fn, global_shift):
         np.testing.assert_allclose(
             cirq.unitary(resolved_gate(q)),
             cirq.unitary(resolve_fn(parameterized_decomposed_circuit, resolver)),
-            atol=1e-8,
+            atol=1e-6,
         )
 
     unparameterized_gate = cirq.PhasedXPowGate(

cirq-core/cirq/ops/two_qubit_diagonal_gate_test.py

@@ -51,6 +51,7 @@ def test_parameterized_decompose():
         np.testing.assert_allclose(
             cirq.unitary(cirq.resolve_parameters(parameterized_op, resolver)),
             cirq.unitary(cirq.resolve_parameters(decomposed_circuit, resolver)),
+            atol=1e-6,
         )
 
 

cirq-core/cirq/optimizers/merge_interactions_test.py

@@ -54,7 +54,7 @@ def assert_optimization_not_broken(circuit):
         cirq.MergeInteractions().optimize_circuit(circuit)
     u_after = circuit.unitary()
 
-    cirq.testing.assert_allclose_up_to_global_phase(u_before, u_after, atol=1e-8)
+    cirq.testing.assert_allclose_up_to_global_phase(u_before, u_after, atol=1e-6)
 
 
 def test_clears_paired_cnot():
@@ -254,4 +254,4 @@ def clean_up(operations):
 
     u_before = c_orig.unitary()
     u_after = circuit[1:-1].unitary()
-    cirq.testing.assert_allclose_up_to_global_phase(u_before, u_after, atol=1e-8)
+    cirq.testing.assert_allclose_up_to_global_phase(u_before, u_after, atol=1e-6)

cirq-core/cirq/testing/circuit_compare_test.py

@@ -126,12 +126,13 @@ def test_measuring_qubits():
     'circuit', [cirq.testing.random_circuit(cirq.LineQubit.range(2), 4, 0.5) for _ in range(5)]
 )
 def test_random_same_matrix(circuit):
+    circuit_copy = circuit.copy()
     a, b = cirq.LineQubit.range(2)
     same = cirq.Circuit(
         cirq.MatrixGate(circuit.unitary(qubits_that_should_be_present=[a, b])).on(a, b)
     )
 
-    cirq.testing.assert_circuits_with_terminal_measurements_are_equivalent(circuit, same)
+    cirq.testing.assert_circuits_with_terminal_measurements_are_equivalent(circuit_copy, same)
 
     mutable_circuit = circuit.copy()
     mutable_circuit.append(cirq.measure(a))

cirq-core/cirq/testing/consistent_decomposition.py

@@ -43,10 +43,10 @@ def assert_decompose_is_consistent_with_unitary(val: Any, ignoring_global_phase:
     actual = circuits.Circuit(dec).unitary(qubit_order=qubits)
 
     if ignoring_global_phase:
-        lin_alg_utils.assert_allclose_up_to_global_phase(actual, expected, atol=1e-8)
+        lin_alg_utils.assert_allclose_up_to_global_phase(actual, expected, atol=1e-6)
     else:
         # coverage: ignore
-        np.testing.assert_allclose(actual, expected, atol=1e-8)
+        np.testing.assert_allclose(actual, expected, atol=1e-6)
 
 
 def _known_gate_with_no_decomposition(val: Any):

cirq-core/cirq/testing/consistent_qasm.py

@@ -125,7 +125,7 @@ def assert_qiskit_parsed_qasm_consistent_with_unitary(qasm, unitary):
     qiskit_unitary = result.result().get_unitary()
     qiskit_unitary = _reorder_indices_of_matrix(qiskit_unitary, list(reversed(range(num_qubits))))
 
-    lin_alg_utils.assert_allclose_up_to_global_phase(unitary, qiskit_unitary, rtol=1e-8, atol=1e-8)
+    lin_alg_utils.assert_allclose_up_to_global_phase(unitary, qiskit_unitary, rtol=1e-6, atol=1e-6)
 
 
 def _indent(*content: str) -> str:

cirq-core/cirq/transformers/analytical_decompositions/controlled_gate_decomposition_test.py

@@ -46,7 +46,7 @@ def test_decompose_x():
                 *qubits[0 : controls_count + 1]
             )
             expected_matrix = circuit2.unitary()
-            assert np.allclose(expected_matrix, result_matrix)
+            assert np.allclose(expected_matrix, result_matrix, atol=1e-6)
 
 
 def _random_unitary():
@@ -88,7 +88,9 @@ def _test_decompose(matrix, controls_count):
         [cirq.MatrixGate(matrix).on(qubits[-1]).controlled_by(*qubits[:-1])]
     ).unitary()
 
-    assert np.allclose(expected_matrix, result_matrix)
+    # Decompose can build rather large circuits for large controls_count,
+    # so we lose a lot of precision.
+    np.testing.assert_allclose(expected_matrix, result_matrix, atol=1e-5)
 
 
 def test_decompose_specific_matrices():

cirq-core/cirq/transformers/analytical_decompositions/cphase_to_fsim_test.py

@@ -84,7 +84,7 @@ def assert_decomposition_valid(cphase_gate, fsim_gate):
     u_expected = cirq.unitary(cphase_gate)
     ops = cirq.decompose_cphase_into_two_fsim(cphase_gate, fsim_gate=fsim_gate)
     u_actual = cirq.unitary(cirq.Circuit(ops))
-    assert np.allclose(u_actual, u_expected)
+    assert np.allclose(u_actual, u_expected, atol=1e-6)
 
 
 @pytest.mark.parametrize(