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Adds improved Bloch-Messiah that gives correct results when the symplectic matrix is degenerate #352

Merged
merged 13 commits into from
Sep 6, 2022
4 changes: 3 additions & 1 deletion .github/CHANGELOG.md
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Expand Up @@ -2,6 +2,8 @@

### New features

* New function to produce Bloch-Messiah decomposition of symplectic matrices.

### Breaking changes

### Improvements
Expand All @@ -25,7 +27,7 @@

This release contains contributions from (in alphabetical order):

Mikhail Andrenkov, Sebastián Duque, Jacon Hastrup, Antonín Hoskovec, Filippo Miatto
Mikhail Andrenkov, Sebastián Duque, Jacob Hastrup, Antonín Hoskovec, Filippo Miatto

---

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5 changes: 3 additions & 2 deletions .github/workflows/tests.yml
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Expand Up @@ -38,6 +38,7 @@ jobs:
run: python3 -m pytest thewalrus --randomly-seed=137 --cov=thewalrus --cov-report term-missing --cov-report=html:coverage_html_report --cov-report=xml:coverage.xml

- name: Upload coverage to Codecov
uses: codecov/codecov-action@v1
uses: codecov/codecov-action@v3
with:
file: ./coverage.xml
files: ./coverage.xml
fail_ci_if_error: true
60 changes: 60 additions & 0 deletions thewalrus/decompositions.py
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Expand Up @@ -28,6 +28,7 @@
.. autosummary::
williamson
symplectic_eigenvals
blochmessiah

Code details
------------
Expand All @@ -36,6 +37,7 @@

from scipy.linalg import block_diag, sqrtm, schur
from thewalrus.symplectic import sympmat
from thewalrus.quantum.gaussian_checks import is_symplectic


def williamson(V, rtol=1e-05, atol=1e-08):
Expand Down Expand Up @@ -112,3 +114,61 @@ def symplectic_eigenvals(cov):
M = int(len(cov) / 2)
D, _ = williamson(cov)
return np.diag(D)[:M]


def blochmessiah(S):
"""Returns the Bloch-Messiah decomposition of a symplectic matrix S = uff @ dff @ vff
where uff and vff are orthogonal symplectic matrices and dff is a diagonal matrix
of the form diag(d1,d2,...,dn,d1^-1, d2^-1,...,dn^-1),

Args:
S (array[float]): 2N x 2N real symplectic matrix

Returns:
tupple(array[float], : orthogonal symplectic matrix uff
array[float], : diagional matrix dff
array[float]) : orthogonal symplectic matrix vff
"""

N, _ = S.shape

if not is_symplectic(S):
raise ValueError("Input matrix is not symplectic.")

# Changing Basis
R = (1 / np.sqrt(2)) * np.block(
[[np.eye(N // 2), 1j * np.eye(N // 2)], [np.eye(N // 2), -1j * np.eye(N // 2)]]
)
Sc = R @ S @ np.conjugate(R).T
# Polar Decomposition
u1, d1, v1 = np.linalg.svd(Sc)
Sig = u1 @ np.diag(d1) @ np.conjugate(u1).T
Unitary = u1 @ v1
# Blocks of Unitary and Hermitian symplectics
alpha = Unitary[0 : N // 2, 0 : N // 2]
beta = Sig[0 : N // 2, N // 2 : N]
# Bloch-Messiah in this Basis
u2, d2, v2 = np.linalg.svd(beta)
sval = np.arcsinh(d2)
takagibeta = u2 @ sqrtm(np.conjugate(u2).T @ (v2.T))
uf = np.block([[takagibeta, 0 * takagibeta], [0 * takagibeta, np.conjugate(takagibeta)]])
vf = np.block(
[
[np.conjugate(takagibeta).T @ alpha, 0 * takagibeta],
[0 * takagibeta, np.conjugate(np.conjugate(takagibeta).T @ alpha)],
]
)
df = np.block(
[
[np.diag(np.cosh(sval)), np.diag(np.sinh(sval))],
[np.diag(np.sinh(sval)), np.diag(np.cosh(sval))],
]
)
# Rotating Back to Original Basis
uff = np.conjugate(R).T @ uf @ R
vff = np.conjugate(R).T @ vf @ R
dff = np.conjugate(R).T @ df @ R
dff = np.real_if_close(dff)
vff = np.real_if_close(vff)
uff = np.real_if_close(uff)
return uff, dff, vff
108 changes: 107 additions & 1 deletion thewalrus/tests/test_decompositions.py
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Expand Up @@ -18,8 +18,10 @@
from scipy.linalg import block_diag

from thewalrus.random import random_interferometer as haar_measure
from thewalrus.decompositions import williamson
from thewalrus.random import random_symplectic
from thewalrus.decompositions import williamson, blochmessiah
from thewalrus.symplectic import sympmat as omega
from thewalrus.quantum.gaussian_checks import is_symplectic


class TestWilliamsonDecomposition:
Expand Down Expand Up @@ -147,3 +149,107 @@ def test_mixed_state(self, create_cov, hbar, tol):
assert np.allclose(sorted(nbar[:n]), sorted(nbar_in), atol=tol, rtol=0)
# check S is symplectic
assert np.allclose(S @ O @ S.T, O, atol=tol, rtol=0)


class TestBlochMessiahDecomposition:
"""Tests for the Bloch Messiah decomposition"""

@pytest.fixture
def create_transform(self):
"""create a symplectic transform for use in testing.

Args:
n (int): number of modes
passive (bool): whether transform should be passive or not

Returns:
array: symplectic matrix
"""

def _create_transform(n, passive=True):
"""wrapped function"""
O = omega(n)

# interferometer 1
U1 = haar_measure(n)
S1 = np.vstack([np.hstack([U1.real, -U1.imag]), np.hstack([U1.imag, U1.real])])

Sq = np.identity(2 * n)
if not passive:
# squeezing
r = np.log(0.2 * np.arange(n) + 2)
Sq = block_diag(np.diag(np.exp(-r)), np.diag(np.exp(r)))

# interferometer 2
U2 = haar_measure(n)
S2 = np.vstack([np.hstack([U2.real, -U2.imag]), np.hstack([U2.imag, U2.real])])

# final symplectic
S_final = S2 @ Sq @ S1

# check valid symplectic transform
assert np.allclose(S_final.T @ O @ S_final, O)
return S_final

return _create_transform

@pytest.mark.parametrize("N", range(50, 500, 50))
def test_blochmessiah_rand(self, N):
"""Tests blochmessiah function for different matrix sizes."""
S = random_symplectic(N)
u, d, v = blochmessiah(S)
assert np.allclose(u @ d @ v, S)
assert np.allclose(u.T @ u, np.eye(len(u)))
assert np.allclose(v.T @ v, np.eye(len(v)))
assert is_symplectic(u)
assert is_symplectic(v)

@pytest.mark.parametrize("M", [np.random.rand(4, 5), np.random.rand(4, 4)])
def test_blochmessiah_error(self, M):
"""Tests that non-symplectic matrices raise a ValueError in blochmessiah."""
with pytest.raises(ValueError, match="Input matrix is not symplectic."):
blochmessiah(M)

def test_identity(self, tol):
"""Test identity"""
n = 2
S_in = np.identity(2 * n)
O1, S, O2 = blochmessiah(S_in)

assert np.allclose(O1 @ O2, np.identity(2 * n), atol=tol, rtol=0)
assert np.allclose(S, np.identity(2 * n), atol=tol, rtol=0)

# test orthogonality
assert np.allclose(O1.T, O1, atol=tol, rtol=0)
assert np.allclose(O2.T, O2, atol=tol, rtol=0)

# test symplectic
O = omega(n)
assert np.allclose(O1 @ O @ O1.T, O, atol=tol, rtol=0)
assert np.allclose(O2 @ O @ O2.T, O, atol=tol, rtol=0)

@pytest.mark.parametrize("passive", [True, False])
def test_transform(self, passive, create_transform, tol):
"""Test decomposition agrees with transform. also checks that passive transform has no squeezing.
Note: this test also tests the case with degenerate symplectic values"""
n = 3
S_in = create_transform(3, passive=passive)
O1, S, O2 = blochmessiah(S_in)

# test decomposition
assert np.allclose(O1 @ S @ O2, S_in, atol=tol, rtol=0)

# test no squeezing
if passive:
assert np.allclose(O1 @ O2, S_in, atol=tol, rtol=0)
assert np.allclose(S, np.identity(2 * n), atol=tol, rtol=0)

# test orthogonality
assert np.allclose(O1.T @ O1, np.identity(2 * n), atol=tol, rtol=0)
assert np.allclose(O2.T @ O2, np.identity(2 * n), atol=tol, rtol=0)

# test symplectic
O = omega(n)
assert np.allclose(O1.T @ O @ O1, O, atol=tol, rtol=0)
assert np.allclose(O2.T @ O @ O2, O, atol=tol, rtol=0)
assert np.allclose(S @ O @ S.T, O, atol=tol, rtol=0)