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[Testing] Projector tests #687

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Feb 26, 2025
Merged

[Testing] Projector tests #687

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859e30d
better projector tests
Feb 25, 2025
62e96eb
fix merge conflict
Feb 25, 2025
697cf02
add cnot for hamevo test projector
Feb 26, 2025
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124 changes: 31 additions & 93 deletions tests/qadence/test_matrices.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -76,99 +76,6 @@ def _calc_mat_vec_wavefunction(
@pytest.mark.parametrize(
"projector, exp_projector_mat",
[
(
Projector(bra="1", ket="1", qubit_support=0),
torch.tensor([[0.0 + 0.0j, 0.0 + 0.0j], [0.0 + 0.0j, 1.0 + 0.0j]]),
),
(
Projector(bra="10", ket="01", qubit_support=(1, 2)),
torch.tensor(
[
[
[
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
[
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
[
0.0 + 0.0j,
1.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
[
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
[
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
[
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
[
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
1.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
[
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
0.0 + 0.0j,
],
]
]
),
),
(
N(0),
(IMAT - ZMAT) / 2.0,
Expand Down Expand Up @@ -579,6 +486,37 @@ def test_projector_composition_unitaries(
assert torch.allclose(block_to_tensor(projector), block_to_tensor(exp_projector), atol=ATOL_64)


@pytest.mark.parametrize(
"projector_decomp, pauli",
[
(
Projector(ket="0", bra="1", qubit_support=0)
+ Projector(ket="1", bra="0", qubit_support=0),
X(0),
),
(
1j * Projector(ket="0", bra="1", qubit_support=0)
- 1j * Projector(ket="1", bra="0", qubit_support=0),
Y(0),
),
(
Projector(ket="0", bra="0", qubit_support=0)
- Projector(ket="1", bra="1", qubit_support=0),
Z(0),
),
(
cnot,
CNOT(0, 1),
),
],
)
def test_projector_hamevo(projector_decomp: AbstractBlock, pauli: AbstractBlock) -> None:
tevo = np.random.rand()
hamevo_comp = HamEvo(projector_decomp, tevo)
hamevo_pauli = HamEvo(pauli, tevo)
assert torch.allclose(block_to_tensor(hamevo_comp), block_to_tensor(hamevo_pauli), atol=ATOL_64)


@pytest.mark.parametrize("use_full_support", [True, False])
@given(st.batched_digital_circuits())
@settings(deadline=None)
Expand Down
83 changes: 32 additions & 51 deletions tests/qadence/test_operators.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
from __future__ import annotations

import numpy as np
import random
import pytest
import torch
from openfermion import QubitOperator, get_sparse_operator
Expand Down Expand Up @@ -96,58 +97,38 @@ def cphase_eigenvals(p: float, n_qubits: int = 2) -> torch.Tensor:
return torch.cat((torch.ones(2**n_qubits - 1), eigenval(2.0 * p).conj()))


# PyQTorch only supports single qubit projectors.
@pytest.mark.parametrize(
"projector, state, exp_wf",
[
(
Projector(bra="0", ket="0", qubit_support=0),
product_state("0"),
torch.tensor([[1.0, 0.0]], dtype=torch.cdouble),
),
(
Projector(bra="0", ket="0", qubit_support=0),
product_state("1"),
torch.tensor([[0.0, 0.0]], dtype=torch.cdouble),
),
(
Projector(bra="1", ket="1", qubit_support=0),
product_state("0"),
torch.tensor([[0.0, 0.0]], dtype=torch.cdouble),
),
(
Projector(bra="1", ket="1", qubit_support=0),
product_state("1"),
torch.tensor([[0.0, 1.0]], dtype=torch.cdouble),
),
(
Projector(bra="00", ket="00", qubit_support=(0, 1)),
product_state("00"),
torch.tensor([[1.0, 0.0, 0.0, 0.0]], dtype=torch.cdouble),
),
(
Projector(bra="01", ket="10", qubit_support=(0, 1)),
product_state("01"),
torch.tensor([[0.0, 0.0, 1.0, 0.0]], dtype=torch.cdouble),
),
(
Projector(bra="10", ket="01", qubit_support=(0, 1)),
product_state("10"),
torch.tensor([[0.0, 1.0, 0.0, 0.0]], dtype=torch.cdouble),
),
(
Projector(bra="11", ket="11", qubit_support=(0, 1)),
product_state("11"),
torch.tensor([[0.0, 0.0, 0.0, 1.0]], dtype=torch.cdouble),
),
],
)
def test_projector_with_pyqtorch(projector: AbstractBlock, state: Tensor, exp_wf: Tensor) -> None:
circuit = QuantumCircuit(projector.n_qubits, projector)
@pytest.mark.parametrize("n_qubits", [1, 2, 3])
def test_projector_with_pyqtorch(n_qubits: int) -> None:
qubit_support = tuple(range(n_qubits))
max_possibility = 2**n_qubits
possible_nbs = list(range(max_possibility - 1))

backend_inst = backend_factory(backend=BackendName.PYQTORCH)
conv_circuit = backend_inst.circuit(circuit=circuit)
wf = backend_inst.run(circuit=conv_circuit, state=state)
assert torch.allclose(wf, exp_wf)

for ket in [random.choice(possible_nbs) for _ in range(2 * n_qubits)]:
for bra in [random.choice(possible_nbs) for _ in range(2 * n_qubits)]:
projector = Projector(
qubit_support=qubit_support, ket=f"{ket:0{n_qubits}b}", bra=f"{bra:0{n_qubits}b}"
)
exp_wf = product_state(f"{ket:0{n_qubits}b}")

circuit = QuantumCircuit(projector.n_qubits, projector)
conv_circuit = backend_inst.circuit(circuit=circuit)
wf = backend_inst.run(circuit=conv_circuit, state=product_state(f"{bra:0{n_qubits}b}"))
# input state bra will transform to ket
assert torch.allclose(wf, exp_wf)

if ket > 0:
projector = Projector(
qubit_support=qubit_support, ket=f"{ket:0{n_qubits}b}", bra=f"{ket:0{n_qubits}b}"
)
circuit = QuantumCircuit(projector.n_qubits, projector)
conv_circuit = backend_inst.circuit(circuit=circuit)
wf = backend_inst.run(
circuit=conv_circuit, state=product_state(f"{ket-1:0{n_qubits}b}")
)
exp_wf = torch.zeros((1, max_possibility), dtype=torch.cdouble)
assert torch.allclose(wf, exp_wf)


@pytest.mark.parametrize(
Expand Down