def test_ComplexSuperApply(self):
"""
Superoperator: Efficient numerics and reference return same result,
acting on non-composite system
"""
rho_list = list(map(rand_dm, [2, 3, 2, 3, 2]))
rho_input = tensor(rho_list)
superop = kraus_to_super(rand_kraus_map(3))
analytic_result = rho_list
analytic_result[1] = Qobj(
vec2mat(superop.data.todense() *
mat2vec(analytic_result[1].data.todense())))
analytic_result[3] = Qobj(
vec2mat(superop.data.todense() *
mat2vec(analytic_result[3].data.todense())))
analytic_result = tensor(analytic_result)
naive_result = subsystem_apply(rho_input,
superop,
[False, True, False, True, False],
reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
assert_(norm(naive_diff) < 1e-12)
efficient_result = subsystem_apply(rho_input, superop,
[False, True, False, True, False])
efficient_diff = (efficient_result - analytic_result).data.todense()
assert_(norm(efficient_diff) < 1e-12)
def test_ComplexSingleApply(self):
"""
Composite system, operator on Hilbert space.
"""
tol = 1e-12
rho_list = list(map(rand_dm, [2, 3, 2, 3, 2]))
rho_input = tensor(rho_list)
single_op = rand_unitary(3)
analytic_result = rho_list
analytic_result[1] = single_op * analytic_result[1] * single_op.dag()
analytic_result[3] = single_op * analytic_result[3] * single_op.dag()
analytic_result = tensor(analytic_result)
naive_result = subsystem_apply(rho_input,
single_op,
[False, True, False, True, False],
reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
naive_diff_norm = norm(naive_diff)
assert_(naive_diff_norm < tol,
msg="ComplexSingle: naive_diff_norm {} "
"is beyond tolerance {}".format(naive_diff_norm, tol))
efficient_result = subsystem_apply(rho_input, single_op,
[False, True, False, True, False])
efficient_diff = (efficient_result - analytic_result).data.todense()
efficient_diff_norm = norm(efficient_diff)
assert_(efficient_diff_norm < tol,
msg="ComplexSingle: efficient_diff_norm {} "
"is beyond tolerance {}".format(efficient_diff_norm, tol))
def test_ComplexSuperApply(self):
"""
Superoperator: Efficient numerics and reference return same result,
acting on non-composite system
"""
tol = 1e-10
rho_list = list(map(rand_dm, [2, 3, 2, 3, 2]))
rho_input = tensor(rho_list)
superop = kraus_to_super(rand_kraus_map(3))
analytic_result = rho_list
analytic_result[1] = Qobj(
vec2mat(superop.full() @ mat2vec(analytic_result[1].full())))
analytic_result[3] = Qobj(
vec2mat(superop.full() @ mat2vec(analytic_result[3].full())))
analytic_result = tensor(analytic_result)
naive_result = subsystem_apply(rho_input,
superop,
[False, True, False, True, False],
reference=True)
naive_diff = (analytic_result - naive_result).full()
naive_diff_norm = norm(naive_diff)
assert_(naive_diff_norm < tol,
msg="ComplexSuper: naive_diff_norm {} "
"is beyond tolerance {}".format(naive_diff_norm, tol))
efficient_result = subsystem_apply(rho_input, superop,
[False, True, False, True, False])
efficient_diff = (efficient_result - analytic_result).full()
efficient_diff_norm = norm(efficient_diff)
assert_(efficient_diff_norm < tol,
msg="ComplexSuper: efficient_diff_norm {} "
"is beyond tolerance {}".format(efficient_diff_norm, tol))
def test_ComplexSuperApply(self):
"""
Superoperator: Efficient numerics and reference return same result,
acting on non-composite system
"""
rho_list = list(map(rand_dm, [2, 3, 2, 3, 2]))
rho_input = tensor(rho_list)
superop = kraus_to_super(rand_kraus_map(3))
analytic_result = rho_list
analytic_result[1] = Qobj(vec2mat(superop.data.todense() *
mat2vec(analytic_result[1].data.todense())))
analytic_result[3] = Qobj(vec2mat(superop.data.todense() *
mat2vec(analytic_result[3].data.todense())))
analytic_result = tensor(analytic_result)
naive_result = subsystem_apply(rho_input, superop,
[False, True, False, True, False],
reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
assert_(norm(naive_diff) < 1e-12)
efficient_result = subsystem_apply(rho_input, superop,
[False, True, False, True, False])
efficient_diff = (efficient_result - analytic_result).data.todense()
assert_(norm(efficient_diff) < 1e-12)
def test_ComplexSingleApply(self):
"""
Composite system, operator on Hilbert space.
"""
tol = 1e-12
rho_list = list(map(rand_dm, [2, 3, 2, 3, 2]))
rho_input = tensor(rho_list)
single_op = rand_unitary(3)
analytic_result = rho_list
analytic_result[1] = single_op * analytic_result[1] * single_op.dag()
analytic_result[3] = single_op * analytic_result[3] * single_op.dag()
analytic_result = tensor(analytic_result)
naive_result = subsystem_apply(rho_input, single_op, [False, True, False, True, False], reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
naive_diff_norm = norm(naive_diff)
assert_(
naive_diff_norm < tol,
msg="ComplexSingle: naive_diff_norm {} " "is beyond tolerance {}".format(naive_diff_norm, tol),
)
efficient_result = subsystem_apply(rho_input, single_op, [False, True, False, True, False])
efficient_diff = (efficient_result - analytic_result).data.todense()
efficient_diff_norm = norm(efficient_diff)
assert_(
efficient_diff_norm < tol,
msg="ComplexSingle: efficient_diff_norm {} " "is beyond tolerance {}".format(efficient_diff_norm, tol),
)
def test_SimpleSingleApply(self):
"""
Non-composite system, operator on Hilbert space.
"""
rho_3 = rand_dm(3)
single_op = rand_unitary(3)
analytic_result = single_op * rho_3 * single_op.dag()
naive_result = subsystem_apply(rho_3, single_op, [True],
reference=True)
efficient_result = subsystem_apply(rho_3, single_op, [True])
naive_diff = (analytic_result - naive_result).data.todense()
efficient_diff = (efficient_result - analytic_result).data.todense()
assert_(norm(naive_diff) < 1e-12 and norm(efficient_diff) < 1e-12)
def test_SimpleSuperApply(self):
"""
Non-composite system, operator on Liouville space.
"""
rho_3 = rand_dm(3)
superop = kraus_to_super(rand_kraus_map(3))
analytic_result = vec2mat(superop.data.todense() *
mat2vec(rho_3.data.todense()))
naive_result = subsystem_apply(rho_3, superop, [True], reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
assert_(norm(naive_diff) < 1e-12)
efficient_result = subsystem_apply(rho_3, superop, [True])
efficient_diff = (efficient_result - analytic_result).data.todense()
assert_(norm(efficient_diff) < 1e-12)
def test_SimpleSuperApply(self):
"""
Non-composite system, operator on Liouville space.
"""
rho_3 = rand_dm(3)
superop = kraus_to_super(rand_kraus_map(3))
analytic_result = vec2mat(superop.data.todense() *
mat2vec(rho_3.data.todense()))
naive_result = subsystem_apply(rho_3, superop, [True],
reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
assert_(norm(naive_diff) < 1e-12)
efficient_result = subsystem_apply(rho_3, superop, [True])
efficient_diff = (efficient_result - analytic_result).data.todense()
assert_(norm(efficient_diff) < 1e-12)
def test_SimpleSuperApply(self):
"""
Non-composite system, operator on Liouville space.
"""
tol = 1e-12
rho_3 = rand_dm(3)
superop = kraus_to_super(rand_kraus_map(3))
analytic_result = vec2mat(superop.full() @ mat2vec(rho_3.full()))
naive_result = subsystem_apply(rho_3, superop, [True], reference=True)
naive_diff = (analytic_result - naive_result).full()
naive_diff_norm = norm(naive_diff)
assert_(naive_diff_norm < tol,
msg="SimpleSuper: naive_diff_norm {} "
"is beyond tolerance {}".format(naive_diff_norm, tol))
efficient_result = subsystem_apply(rho_3, superop, [True])
efficient_diff = (efficient_result - analytic_result).full()
efficient_diff_norm = norm(efficient_diff)
assert_(efficient_diff_norm < tol,
msg="SimpleSuper: efficient_diff_norm {} "
"is beyond tolerance {}".format(efficient_diff_norm, tol))
def test_SimpleSingleApply(self):
"""
Non-composite system, operator on Hilbert space.
"""
tol = 1e-12
rho_3 = rand_dm(3)
single_op = rand_unitary(3)
analytic_result = single_op * rho_3 * single_op.dag()
naive_result = subsystem_apply(rho_3,
single_op, [True],
reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
naive_diff_norm = norm(naive_diff)
assert_(naive_diff_norm < tol,
msg="SimpleSingle: naive_diff_norm {} "
"is beyond tolerance {}".format(naive_diff_norm, tol))
efficient_result = subsystem_apply(rho_3, single_op, [True])
efficient_diff = (efficient_result - analytic_result).data.todense()
efficient_diff_norm = norm(efficient_diff)
assert_(efficient_diff_norm < tol,
msg="SimpleSingle: efficient_diff_norm {} "
"is beyond tolerance {}".format(efficient_diff_norm, tol))
def test_ComplexSingleApply(self):
"""
Composite system, operator on Hilbert space.
"""
rho_list = list(map(rand_dm, [2, 3, 2, 3, 2]))
rho_input = tensor(rho_list)
single_op = rand_unitary(3)
analytic_result = rho_list
analytic_result[1] = single_op * analytic_result[1] * single_op.dag()
analytic_result[3] = single_op * analytic_result[3] * single_op.dag()
analytic_result = tensor(analytic_result)
naive_result = subsystem_apply(rho_input, single_op,
[False, True, False, True, False],
reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
assert_(norm(naive_diff) < 1e-12)
efficient_result = subsystem_apply(rho_input, single_op,
[False, True, False, True, False])
efficient_diff = (efficient_result - analytic_result).data.todense()
assert_(norm(efficient_diff) < 1e-12)
def test_SimpleSingleApply(self):
"""
Non-composite system, operator on Hilbert space.
"""
tol = 1e-12
rho_3 = rand_dm(3)
single_op = rand_unitary(3)
analytic_result = single_op * rho_3 * single_op.dag()
naive_result = subsystem_apply(rho_3, single_op, [True], reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
naive_diff_norm = norm(naive_diff)
assert_(
naive_diff_norm < tol,
msg="SimpleSingle: naive_diff_norm {} " "is beyond tolerance {}".format(naive_diff_norm, tol),
)
efficient_result = subsystem_apply(rho_3, single_op, [True])
efficient_diff = (efficient_result - analytic_result).data.todense()
efficient_diff_norm = norm(efficient_diff)
assert_(
efficient_diff_norm < tol,
msg="SimpleSingle: efficient_diff_norm {} " "is beyond tolerance {}".format(efficient_diff_norm, tol),
)
def test_SimpleSuperApply(self):
"""
Non-composite system, operator on Liouville space.
"""
tol = 1e-12
rho_3 = rand_dm(3)
superop = kraus_to_super(rand_kraus_map(3))
analytic_result = vec2mat(superop.data.todense() * mat2vec(rho_3.data.todense()))
naive_result = subsystem_apply(rho_3, superop, [True], reference=True)
naive_diff = (analytic_result - naive_result).data.todense()
naive_diff_norm = norm(naive_diff)
assert_(
naive_diff_norm < tol,
msg="SimpleSuper: naive_diff_norm {} " "is beyond tolerance {}".format(naive_diff_norm, tol),
)
efficient_result = subsystem_apply(rho_3, superop, [True])
efficient_diff = (efficient_result - analytic_result).data.todense()
efficient_diff_norm = norm(efficient_diff)
assert_(
efficient_diff_norm < tol,
msg="SimpleSuper: efficient_diff_norm {} " "is beyond tolerance {}".format(efficient_diff_norm, tol),
)