Performs a measurement of the density matrix in the computational basis.
qid_shape: Optional[Tuple[int, ...]] = None,
out: np.ndarray = None,
seed: "cirq.RANDOM_STATE_OR_SEED_LIKE" = None
) -> Tuple[List[int], np.ndarray]
Used in the notebooks
This does not modify
density_matrix unless the optional
The density matrix to be measured. This matrix is
assumed to be positive semidefinite and trace one. The matrix is
assumed to be of shape (2 ** integer, 2 ** integer) or
(2, 2, ..., 2).
Which qubits are measured. The matrix is assumed to be supplied
in big endian order. That is the xth index of v, when expressed as
a bitstring, has the largest values in the 0th index.
The qid shape of the density matrix. Specify this argument
when using qudits.
An optional place to store the result. If
out is the same as
density_matrix parameter, then
density_matrix will be
modified inline. If
out is not None, then the result is put into
out is None a new value will be allocated. In all of
out will be the same as the returned ndarray of the
method. The shape and dtype of
out will match that of
out is None, otherwise it will match the
shape and dtype of
A seed for the pseudorandom number generator.
A tuple of a list and an numpy array. The list is an array of booleans
corresponding to the measurement values (ordered by the indices). The
numpy array is the post measurement matrix. This matrix has the same
shape and dtype as the input matrix.
ValueError if the dimension of the matrix is not compatible with a
matrix of n qubits.
IndexError if the indices are out of range for the number of qubits
corresponding to the density matrix.