OperatorTerm#

class cuquantum.densitymat.OperatorTerm(dtype: str | None = None)[source]#

Operator term consisting of tensor products of elementary operators.

An OperatorTerm containing a tensor product of elementary operators can be obtained from the free function tensor_product(). Sums of more than a single product are obtained by in-place (+=) or out-of-place addition (+) of OperatorTerm objects.

Parameters:

dtype – Numeric data type of the underlying elementary operators’ data. Defaults to None and will be inferred from the appended tensor products of elementary operators.

Note

  • Scalar operators, for which no product is appended, require specification of dtype at construction.

Methods

__add__(
other: OperatorTerm,
) → OperatorTerm[source]#

Return a new OperatorTerm equal to the sum of this OperatorTerm and another OperatorTerm.

__iadd__(
other: OperatorTerm,
) → OperatorTerm[source]#

Inplace add another OperatorTerm into this OperatorTerm.

__init__(dtype: str | None = None)[source]#

Initialize an operator term consisting of tensor products of elementary operators.

__mul__(
other: Number | ndarray | ndarray | Callback | Tuple[Number, Callback] | Tuple[ndarray | ndarray, Callback] | OperatorTerm,
) → OperatorTerm[source]#

Multiply this OperatorTerm with another OperatorTerm or with a coefficient. Note that multiplication by a Callable that outputs a batched coefficient vector requires all static coefficients to have the the same batch_size as the output of the callable.

__rmul__(
other: Number | ndarray | ndarray | Callback | Tuple[Number, Callback] | Tuple[ndarray | ndarray, Callback] | OperatorTerm,
) → OperatorTerm[source]#

Multiply this OperatorTerm with a number, callable or another OperatorTerm on the right.

append_elementary_product(
elem_ops: Iterable[ElementaryOperator],
modes: Iterable[Sequence[int]],
duals: Iterable[Sequence[bool]],
coeff: Number | ndarray | ndarray | Callback | Tuple[Number, Callback] | Tuple[ndarray | ndarray, Callback] = 1 + 0j,
batch_size: int = 1,
) → None[source]#

Append a product of elementary operators to this operator term.

Parameters:

  • elem_ops – An iterable of elementary operators.

  • modes – An iterable of the mode indices of the elementary operators.

  • duals – Dualities of the elementary operators.

  • coeff – Coefficient associated with this tensor product of elementary operators.

  • batch_size – Batch size associated with this product of elementary operators.

Note

The relation among operators in elem_ops is matrix multiplication/tensor contraction, which is equivalent to tensor product when there are no overlapping modes.

append_matrix_product(
matrix_ops: Iterable[MatrixOperator],
conjugations: Iterable[bool],
duals: Iterable[bool],
coeff: Number | ndarray | ndarray | Callback | Tuple[Number, Callback] | Tuple[ndarray | ndarray, Callback] = 1 + 0j,
batch_size: int = 1,
) → None[source]#

Append a product of matrix operators to this operator term.

Parameters:

  • matrix_ops – An iterable of matrix operators.

  • conjugations – An iterable of whether each matrix operator is conjugated.

  • duals – Dualities of the matrix operators.

  • coeff – Coefficient associated with this tensor product of matrix operators.

  • batch_size – Batch size associated with this product of matrix operators.

Note

The relation among operators in matrix_ops is matrix multiplication.

dag() → OperatorTerm[source]#

Return a new OperatorTerm equal to the complex conjugate of this OperatorTerm.

Warning

A error will be raised if the OperatorTerm contains tensor products of elementary operators acting on both bra and ket modes at the same time.

dual() → OperatorTerm[source]#

Return a new OperatorTerm with duality reversed.

Attributes

dtype#

Data type of this OperatorTerm.

hilbert_space_dims#

Hilbert space dimensions of this OperatorTerm.