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Merged
Ericgig merged 4 commits into from
Oct 31, 2025
Merged

Rework to operterm #17

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dd5394a
Rework to operterm
Ericgig Oct 17, 2025
a0c1606
Fixing bugs
Ericgig Oct 28, 2025
bb41145
Fix tests
Ericgig Oct 29, 2025
2798eb3
remove debug print
Ericgig Oct 29, 2025
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7 changes: 5 additions & 2 deletions setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
import setuptools
from Cython.Build import cythonize
import qutip
import qutip.core.cy as qutip_cc
import numpy


Expand Down Expand Up @@ -94,7 +95,9 @@ def get_ext_modules(options):
pyx_file = os.path.join("src", "qutip_cuquantum", "qobjevo.pyx")
include_dirs = [
numpy.get_include(),
os.path.abspath(os.path.join(qutip.core.data.__file__, os.pardir))
os.path.abspath(os.path.join(qutip.core.data.__file__, os.pardir)),
os.path.abspath(os.path.join(qutip_cc.__file__, os.pardir)),
os.path.abspath(os.path.join(qutip.__file__, os.pardir))
]
print("*********************************************************************************")
print(include_dirs)
Expand All @@ -107,7 +110,7 @@ def get_ext_modules(options):
language="c++",
)

return cythonize(ext)
return cythonize(ext, include_path=include_dirs)


if __name__ == "__main__":
Expand Down
140 changes: 82 additions & 58 deletions src/qutip_cuquantum/operator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,17 +26,32 @@
# Input fixed in tests, but did not fail early


def _transpose_cu_operator(oper):
if isinstance(oper, MultidiagonalOperator):
out = MultidiagonalOperator(
oper.data,
[-offset for offset in oper.offsets],
callback=oper.callback,
)
def _transpose_cu_operator(oper, transpose: list[bool]):
"""
Transpose modes where ``transpose`` is True.
"""
if isinstance(oper, MultidiagonalOperator) and len(transpose) == 1:
if transpose[0]:
out = MultidiagonalOperator(
oper.data,
[-offset for offset in oper.offsets],
callback=oper.callback,
)
elif isinstance(oper, DenseOperator):
N = oper.num_modes
batch_dims_oper = len(oper.data.shape) % 2
perm = tuple(range(N, 2*N)) + tuple(range(N))

perm_l = []
perm_r = []
for i, trans in enumerate(transpose):
if trans:
perm_l.append(i + N)
perm_r.append(i)
else:
perm_l.append(i)
perm_r.append(i+ N)
perm = tuple(perm_l + perm_r)

new_callback = None

if oper.callback is not None:
Expand Down Expand Up @@ -102,7 +117,8 @@ def _oper_to_ElementaryOperator(
oper,
hilbert_idx,
hilbert_dims,
transform,
transpose,
dag,
copy=False
):
N = len(hilbert_idx)
Expand All @@ -111,32 +127,27 @@ def _oper_to_ElementaryOperator(
if isinstance(oper, (DenseOperator, MultidiagonalOperator)):
if N != 1 and isinstance(oper, MultidiagonalOperator):
raise ValueError(
"MultidiagonalOperator on multiple hilbert spaces"
"MultidiagonalOperator on multiple hilbert spaces are not supported."
)
if list(oper.shape[:len(oper.shape) // 2]) != list(shape):
raise ValueError(
f"Operator shape does not match hilbert spaces: "
f"{list(oper.shape[:len(oper.shape) // 2])}, {shape}"
)

if transform == Transform.DIRECT:
out = oper
elif transform == Transform.ADJOINT:
out = oper.dag()
elif transform == Transform.CONJ:
out = _transpose_cu_operator(oper).dag()
elif transform == Transform.TRANSPOSE:
out = _transpose_cu_operator(oper)
cu_oper = oper

else:
if transform == Transform.DIRECT:
pass
elif transform == Transform.ADJOINT:
oper = oper.adjoint()
elif transform == Transform.CONJ:
if all(transpose) and dag:
oper = oper.conj()
elif transform == Transform.TRANSPOSE:
transpose = [False]
dag = False
elif dag:
oper = oper.adjoint()
dag = False
elif all(transpose):
oper = oper.transpose()
transpose = [False]

if isinstance(oper, _data.Dia) and N == 1:
dia_matrix = oper.as_scipy()
Expand All @@ -145,12 +156,17 @@ def _oper_to_ElementaryOperator(
for i, offset in enumerate(offsets):
end = None if offset == 0 else -abs(offset)
data[:end, i] = dia_matrix.diagonal(offset)
out = MultidiagonalOperator(data, offsets)
cu_oper = MultidiagonalOperator(data, offsets)

else:
out = DenseOperator(oper.to_array().reshape(shape + shape))
cu_oper = DenseOperator(oper.to_array().reshape(shape + shape))

return out
if any(transpose):
cu_oper = _transpose_cu_operator(cu_oper, transpose)
if dag:
cu_oper = cu_oper.dag()

return cu_oper


###############################################################################
Expand Down Expand Up @@ -538,11 +554,14 @@ def to_OperatorTerm(self, dual=False, copy=True, hilbert_dims=None):
for term in self.terms:
cuterm = tensor_product(dtype="complex128")
for pterm in term.prod_terms:
transpose = pterm.transform in [Transform.TRANSPOSE, Transform.CONJ]
dag = pterm.transform in [Transform.ADJOINT, Transform.CONJ]
oper = _oper_to_ElementaryOperator(
pterm.operator,
pterm.hilbert,
self.hilbert_space_dims,
pterm.transform,
[transpose] * len(pterm.hilbert),
dag,
copy
)
# Inverted order confirmed by nvidia
Expand All @@ -552,40 +571,29 @@ def to_OperatorTerm(self, dual=False, copy=True, hilbert_dims=None):
else:
N_hilbert = len(self.hilbert_dims) // 2
# TODO: make this tests weak compare?
assert self.hilbert_dims[:N_hilbert] == self.hilbert_dims[N_hilbert:]
if self.hilbert_dims[:N_hilbert] != self.hilbert_dims[N_hilbert:]:
raise ValueError(
f"Hilbert space inconsistent with square superoperator: {self.hilbert_dims}"
)
for term in self.terms:
cuterm = tensor_product(dtype="complex128")
for pterm in term.prod_terms:
if all(i < N_hilbert for i in pterm.hilbert):
oper = _oper_to_ElementaryOperator(
pterm.operator,
pterm.hilbert,
self.hilbert_space_dims,
trans_transform[pterm.transform],
copy
)
# Inverted order confirmed by nvidia
cuterm = cuterm * tensor_product(
(oper, pterm.hilbert, (True,))
)

elif any(i < N_hilbert for i in pterm.hilbert):
raise NotImplementedError(
"Operators acting on both original and "
"dual spaces are not supported."
)
modes = tuple(mode % N_hilbert for mode in pterm.hilbert)
duals = tuple(mode < N_hilbert for mode in pterm.hilbert)
transpose = tuple(duals)
dag = pterm.transform in [Transform.ADJOINT, Transform.CONJ]
if pterm.transform in [Transform.CONJ, Transform.TRANSPOSE]:
transpose = tuple(not trans for trans in transpose)

else:
oper = _oper_to_ElementaryOperator(
pterm.operator,
pterm.hilbert,
self.hilbert_space_dims,
pterm.transform,
copy
)
cuterm = cuterm * tensor_product(
(oper, tuple(i - N_hilbert for i in pterm.hilbert))
)
oper = _oper_to_ElementaryOperator(
pterm.operator,
pterm.hilbert,
self.hilbert_space_dims,
transpose,
dag,
copy
)
cuterm = cuterm * tensor_product((oper, modes, duals,))

out = out + (cuterm * term.factor)

Expand Down Expand Up @@ -731,6 +739,22 @@ def isherm(operator, tol=-1):
if tol < 0:
tol = settings.core["atol"]
return cp.allclose(oper, oper.T.conj(), atol=tol)


@_data.identity_like.register(CuOperator)
def identity_like(data, /):
"""
Create an identity matrix of the same type and shape.
"""
if not data.shape[0] == data.shape[1]:
raise ValueError(
"Can't create an identity matrix like a non square matrix."
)

new = CuOperator(hilbert_dims=data.hilbert_dims)
new.terms.append(Term([], 1.))
return new

###############################################################################
###############################################################################

Expand Down
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