cuquantum.densitymat.OperatorTerm

class cuquantum.densitymat.OperatorTerm(dtype: Optional[str] = None)

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

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

__iadd__(other: OperatorTerm) → OperatorTerm

Inplace add another OperatorTerm into this OperatorTerm.

__init__(dtype: Optional[str] = None)

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

__mul__(other: Union[numbers.Number, numpy.ndarray, cupy.ndarray, Callback, Tuple[numbers.Number, Callback], Tuple[Union[numpy.ndarray, cupy.ndarray], Callback], OperatorTerm]) → OperatorTerm

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: Union[numbers.Number, numpy.ndarray, cupy.ndarray, Callback, Tuple[numbers.Number, Callback], Tuple[Union[numpy.ndarray, cupy.ndarray], Callback], OperatorTerm]) → OperatorTerm

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: Union[numbers.Number, numpy.ndarray, cupy.ndarray, Callback, Tuple[numbers.Number, Callback], Tuple[Union[numpy.ndarray, cupy.ndarray], Callback]] = 1 + 0j, batch_size: int = 1) → None

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: Union[numbers.Number, numpy.ndarray, cupy.ndarray, Callback, Tuple[numbers.Number, Callback], Tuple[Union[numpy.ndarray, cupy.ndarray], Callback]] = 1 + 0j, batch_size: int = 1) → None

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

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

Return a new OperatorTerm with duality reversed.

Attributes

dtype

Data type of this OperatorTerm.

hilbert_space_dims

Hilbert space dimensions of this OperatorTerm.