def test_seed(self, dtype, sparse):
a = qu.rand_matrix(10, sparse=sparse, dtype=dtype, seed=42)
b = qu.rand_matrix(10, sparse=sparse, dtype=dtype, seed=42)
if sparse:
assert_allclose(a.data, b.data)
else:
assert_allclose(a, b)
def test_2d_simple(self):
a = (qu.rand_matrix(2), qu.rand_matrix(2))
dims = ((2, 3), (3, 2))
inds = ((0, 0), (1, 1))
b = qu.ikron(a, dims, inds)
assert b.shape == (36, 36)
assert_allclose(b, a[0] & qu.eye(9) & a[1])
def test_2d_simple(self):
a = (rand_matrix(2), rand_matrix(2))
dims = ((2, 3), (3, 2))
inds = ((0, 0), (1, 1))
b = eyepad(a, dims, inds)
assert b.shape == (36, 36)
assert_allclose(b, a[0] & eye(9) & a[1])
def test_ikron_ownership(self, sparse, ri, rf):
dims = [7, 2, 4, 3]
X = qu.rand_matrix(2, sparse=sparse)
Y = qu.rand_matrix(3, sparse=sparse)
X1 = qu.ikron((X, Y), dims, (1, 3))[ri:rf, :]
X2 = qu.ikron((X, Y), dims, (1, 3), ownership=(ri, rf))
assert_allclose(X1.A, X2.A)
def test_sparse(self):
i = qu.eye(2, sparse=True)
a = qu.qu(qu.rand_matrix(2), sparse=True)
b = qu.ikron(a, [2, 2, 2], 1) # infer sparse
assert (qu.issparse(b))
assert_allclose(b.A, (i & a & i).A)
a = qu.rand_matrix(2)
b = qu.ikron(a, [2, 2, 2], 1, sparse=True) # explicit sparse
assert (qu.issparse(b))
assert_allclose(b.A, (i & a & i).A)
def test_sparse(self):
i = eye(2, sparse=True)
a = qu(rand_matrix(2), sparse=True)
b = eyepad(a, [2, 2, 2], 1) # infer sparse
assert(issparse(b))
assert_allclose(b.A, (i & a & i).A)
a = rand_matrix(2)
b = eyepad(a, [2, 2, 2], 1, sparse=True) # explicit sparse
assert(issparse(b))
assert_allclose(b.A, (i & a & i).A)
def test_ndarrays(self):
a = rand_matrix(2)
i = eye(2)
b = eyepad([a], np.array([2, 2, 2]), [0, 2])
assert_allclose(b, a & i & a)
b = eyepad([a], [2, 2, 2], np.array([0, 2]))
assert_allclose(b, a & i & a)
def test_ndarrays(self):
a = qu.rand_matrix(2)
i = qu.eye(2)
b = qu.ikron([a], np.array([2, 2, 2]), [0, 2])
assert_allclose(b, a & i & a)
b = qu.ikron([a], [2, 2, 2], np.array([0, 2]))
assert_allclose(b, a & i & a)
def test_ldmul_large(self):
vec = np.random.randn(501)
mat = rand_matrix(501)
a = ldmul(vec, mat)
b = np.diag(vec) @ mat
assert isinstance(a, np.matrix)
assert_allclose(a, b)
def test_rdmul_large(self):
vec = np.random.randn(501)
mat = rand_matrix(501)
a = rdmul(mat, vec)
b = mat @ np.diag(vec)
assert isinstance(a, np.matrix)
assert_allclose(a, b)
def test_mid_multi_reverse(self):
a = [qu.rand_matrix(2) for i in range(3)]
i = qu.eye(2)
dims = [2, 2, 2, 2, 2, 2]
inds = [5, 4, 1]
b = qu.ikron(a, dims, inds)
assert_allclose(b, i & a[2] & i & i & a[1] & a[0])
def test_mid_multi(self):
a = [rand_matrix(2) for i in range(3)]
i = eye(2)
dims = [2, 2, 2, 2, 2, 2]
inds = [1, 2, 4]
b = eyepad(a, dims, inds)
assert_allclose(b, i & a[0] & a[1] & i & a[2] & i)
def test_rand_matrix_bsr(self, dtype):
a = qu.rand_matrix(10,
sparse=True,
density=0.2,
stype='bsr',
dtype=dtype)
assert a.shape == (10, 10)
assert type(a) == sp.bsr_matrix
assert a.dtype == dtype
def test_overlap(self):
a = [qu.rand_matrix(4) for i in range(2)]
dims1 = [2, 2, 2, 2, 2, 2]
dims2 = [2, 4, 4, 2]
b = qu.ikron(a, dims1, [1, 2, 3, 4])
c = qu.ikron(a, dims2, [1, 2])
assert_allclose(c, b)
dims2 = [4, 2, 2, 4]
b = qu.ikron(a, dims1, [0, 1, 4, 5])
c = qu.ikron(a, dims2, [0, 3])
assert_allclose(c, b)
def srho_dot_ls():
rho = rand_rho(3)
ham = rand_herm(3, sparse=True, density=0.5)
gamma = 0.7
ls = [rand_matrix(3, sparse=True, density=0.5) for _ in range(3)]
rhodl = -1.0j * (ham @ rho - rho @ ham)
for l in ls:
rhodl += gamma * (l @ rho @ l.H)
rhodl -= gamma * 0.5 * (rho @ l.H @ l)
rhodl -= gamma * 0.5 * (l.H @ l @ rho)
return rho, ham, gamma, ls, rhodl
def rho_dot_ls():
np.random.seed(1)
rho = rand_rho(3)
ham = rand_herm(3)
gamma = 0.7
ls = [rand_matrix(3) for _ in range(3)]
rhodl = -1.0j * (ham @ rho - rho @ ham)
for l in ls:
rhodl += gamma * (l @ rho @ l.H)
rhodl -= gamma * 0.5 * (rho @ l.H @ l)
rhodl -= gamma * 0.5 * (l.H @ l @ rho)
return rho, ham, gamma, ls, rhodl
def test_basic(self):
a = qu.rand_matrix(2)
i = qu.eye(2)
dims = [2, 2, 2]
b = qu.ikron([a], dims, [0])
assert_allclose(b, a & i & i)
b = qu.ikron([a], dims, [1])
assert_allclose(b, i & a & i)
b = qu.ikron([a], dims, [2])
assert_allclose(b, i & i & a)
b = qu.ikron([a], dims, [0, 2])
assert_allclose(b, a & i & a)
b = qu.ikron([a], dims, [0, 1, 2])
assert_allclose(b, a & a & a)
def test_epeps_absorb_3body_tensor(self, Lx, Ly, method):
'''Currently only tests 3-body ops!
contract_methods = {0: False, 1: 'triangle_absorb'}
'''
# opts for splitting 'blob' in `triangle_absorb` method
compress_opts = {'method': method}
epeps = qnets.QubitEncodeVector.rand(Lx,
Ly).convert_to_ePEPS(dummy_size=1)
bra = epeps.H
# compile (vertex, vertex, face) 'target' qubits
LatticeCooHam = hams.SpinlessSimHam(Lx, Ly).\
convert_to_coordinate_ham(lambda q: epeps.qubit_to_coo_map[q])
for coos, _ in LatticeCooHam.gen_ham_terms():
# SKIP 2-body interactions
if len(coos) == 2:
continue
rand_gate = qu.rand_matrix(8) #use a random 3-body gate
G_ket_0 = epeps.gate(G=rand_gate, coos=coos, contract=False)
G_ket_1 = epeps.gate(G=rand_gate,
coos=coos,
contract='triangle_absorb',
**compress_opts)
expec_0 = (bra & G_ket_0) ^ all # `contract=False` reference
expec_1 = (bra & G_ket_1) ^ all # `triangle_absorb` reference
assert expec_1 == pytest.approx(expec_0, rel=1e-2)
coos = (coos[1], coos[0], coos[2]
) # now try w/ vertex qubits swapped
G_ket_0 = epeps.gate(G=rand_gate, coos=coos, contract=False)
G_ket_2 = epeps.gate(G=rand_gate,
coos=coos,
contract='triangle_absorb',
**compress_opts)
expec_0 = (bra & G_ket_0) ^ all
expec_2 = (bra & G_ket_2) ^ all
assert expec_2 == pytest.approx(expec_0, rel=1e-2)
def test_holey_overlap(self):
a = qu.rand_matrix(8)
dims1 = (2, 2, 2, 2, 2)
dims2 = (2, 8, 2)
b = qu.ikron(a, dims1, (1, 3))
c = qu.ikron(a, dims2, 1)
assert_allclose(b, c)
dims1 = (2, 2, 2, 2, 2)
dims2 = (2, 2, 8)
b = qu.ikron(a, dims1, (2, 4))
c = qu.ikron(a, dims2, 2)
assert_allclose(b, c)
dims1 = (2, 2, 2, 2, 2)
dims2 = (8, 2, 2)
b = qu.ikron(a, dims1, (0, 2))
c = qu.ikron(a, dims2, 0)
assert_allclose(b, c)
def test_qev_triangle_absorb_method(self, Lx, Ly, method):
'''Test 'triangle_absorb' method, which works for
`QubitEncodeVector`-type geometry without rotating the
face tensors (i.e. non-rectangular lattice geometry).
'''
# opts for splitting 'blob' in `triangle_absorb` method
compress_opts = {'method': method}
# without rotating face tensors!
psi = qnets.QubitEncodeVector.rand(Lx, Ly, bond_dim=2)
bra = psi.H
# norm = (bra & psi) ^ all
# compile all 3-tuples (vertex, vertex, face) qubits to act on
LatticeHam = hams.SpinlessSimHam(Lx, Ly)
for where, _ in LatticeHam.gen_ham_terms():
# skip 2-body terms
if len(where) == 2:
continue
rand_gate = qu.rand_matrix(8)
# apply gate both 0) without contracting, and 1) with 'triangle-absorb'
G_ket_0 = psi.apply_gate(G=rand_gate, where=where, contract=False)
G_ket_1 = psi.apply_gate(G=rand_gate,
where=where,
contract='triangle_absorb',
**compress_opts)
expec_0 = (bra & G_ket_0) ^ all
expec_1 = (bra & G_ket_1) ^ all
assert expec_1 == pytest.approx(expec_0, rel=1e-2)
## also try with vertex qubits switched!
where = (where[1], where[0], where[2])
G_ket_0 = psi.apply_gate(G=rand_gate, where=where, contract=False)
G_ket_2 = psi.apply_gate(G=rand_gate,
where=where,
contract='triangle_absorb',
**compress_opts)
expec_0 = (bra & G_ket_0) ^ all
expec_2 = (bra & G_ket_2) ^ all
assert expec_2 == pytest.approx(expec_0, rel=1e-2)
def test_epeps_absorb_3body_gate(self, Lx, Ly, method):
'''Test absorbing a 3-body dense, random gate into the tn.
'''
# opts for splitting 'blob' in `triangle_absorb` method
compress_opts = {'method': method}
epeps = qnets.QubitEncodeVector.rand(Lx,
Ly).convert_to_ePEPS(dummy_size=1)
bra = epeps.H
# norm = (bra & epeps) ^ all
# use Ham to get (vertex, vertex, face) 'target' qubits
LatticeCooHam = hams.SpinlessSimHam(Lx, Ly).\
convert_to_coordinate_ham(lambda q: epeps.qubit_to_coo_map[q])
for coos, _ in LatticeCooHam.gen_ham_terms():
# skip 2-body interactions
if len(coos) == 2:
continue
rand_gate = qu.rand_matrix(8) #use a random 3-body gate
G_ket_0 = epeps.gate(G=rand_gate, coos=coos, contract=False)
G_ket_1 = epeps.absorb_three_body_gate(G=rand_gate,
coos=coos,
**compress_opts)
expec_0 = (bra & G_ket_0) ^ all # `contract=False` reference
expec_1 = (bra & G_ket_1) ^ all # `triangle_absorb` reference
assert expec_1 == pytest.approx(expec_0, rel=1e-2)
# now try with the vertex qubits swapped
coos = (coos[1], coos[0], coos[2])
G_ket_0 = epeps.gate(G=rand_gate, coos=coos, contract=False)
G_ket_2 = epeps.absorb_three_body_gate(G=rand_gate,
coos=coos,
**compress_opts)
expec_0 = (bra & G_ket_0) ^ all
expec_2 = (bra & G_ket_2) ^ all
assert expec_2 == pytest.approx(expec_0, rel=1e-2)
def test_epeps_2body_reduce_split(self, Lx, Ly, contract):
epeps = qnets.QubitEncodeVector.rand(Lx,
Ly).convert_to_ePEPS(dummy_size=1)
bra = epeps.H
# compile (vertex, vertex) 'target' qubit pairs
LatticeCooHam = hams.SpinlessSimHam(Lx, Ly).\
convert_to_coordinate_ham(lambda q: epeps.qubit_to_coo_map[q])
for coos, _ in LatticeCooHam.gen_ham_terms():
# skip 3-body terms here
if len(coos) == 3:
continue
rand_gate = qu.rand_matrix(4)
G_ket_0 = epeps.gate(G=rand_gate, coos=coos, contract=False)
G_ket_1 = epeps.gate(G=rand_gate, coos=coos, contract=contract)
assert (bra & G_ket_1) ^ all == pytest.approx(
(bra & G_ket_0) ^ all, rel=1e-2)
def rand_rect(m, n, sparse=False, dtype=complex):
X = qu.rand_matrix(max(m, n), dtype=dtype, sparse=sparse)
return X[:m, :n]
def mat_s_nnz():
return rand_matrix(_TEST_SZ, sparse=True, density=0.75)
def mat_s2():
return rand_matrix(_TEST_SZ, sparse=True, density=0.5)
def mat_d3():
return rand_matrix(_TEST_SZ)
def test_axes_types(self, axes):
a = qu.rand_matrix(4)
b = qu.itrace(a, axes)
assert_allclose(b, np.trace(a))
def os1():
return qu.rand_matrix(3, sparse=True, density=0.5)
def test_kron_ownership(self, sparse, ri, rf):
dims = [7, 2, 4, 3]
ops = [qu.rand_matrix(d, sparse=sparse) for d in dims]
X1 = qu.kron(*ops)[ri:rf, :]
X2 = qu.kron(*ops, ownership=(ri, rf))
assert_allclose(X1.A, X2.A)
def test_auto(self):
a = qu.rand_matrix(2)
i = qu.eye(2)
b = qu.ikron([a], (2, -1, 2), [1])
assert_allclose(b, i & a & i)
