cirq.Circuit.apply_unitary_effect_to_state¶

Circuit.apply_unitary_effect_to_state(initial_state: Union[int, numpy.ndarray] = 0, qubit_order: Union[cirq.ops.qubit_order.QubitOrder, Iterable[cirq.ops.raw_types.Qid]] = <cirq.ops.qubit_order.QubitOrder object>, qubits_that_should_be_present: Iterable[cirq.ops.raw_types.Qid] = (), ignore_terminal_measurements: bool = True, dtype: Type[numpy.number] = <class 'numpy.complex128'>) → numpy.ndarray

THIS FUNCTION IS DEPRECATED.

IT WILL BE REMOVED IN cirq v0.7.0.

Left-multiplies a state vector by the circuit’s unitary effect.

A circuit's "unitary effect" is the unitary matrix produced by
multiplying together all of its gates' unitary matrices. A circuit
with non-unitary gates (such as measurement or parameterized gates) does
not have a well-defined unitary effect, and the method will fail if such
operations are present.

For convenience, terminal measurements are automatically ignored
instead of causing a failure. Set the ignore_terminal_measurements
argument to False to disable this behavior.

This method is equivalent to left-multiplying the input state by
cirq.unitary(circuit) but it's computed in a more efficient
way.

Args:
initial_state: The input state for the circuit. This can be an int
or a vector. When this is an int, it refers to a computational
basis state (e.g. 5 means initialize to |5⟩ = |...000101⟩).
If this is a state vector, it directly specifies the initial
state's amplitudes. The vector must be a flat numpy array with a
type that can be converted to np.complex128.
qubit_order: Determines how qubits are ordered when passing matrices
into np.kron.
qubits_that_should_be_present: Qubits that may or may not appear
in operations within the circuit, but that should be included
regardless when generating the matrix.
ignore_terminal_measurements: When set, measurements at the end of
the circuit are ignored instead of causing the method to
fail.
dtype: The numpy dtype for the returned unitary. Defaults to
np.complex128. Specifying np.complex64 will run faster at the
cost of precision. dtype must be a complex np.dtype, unless
all operations in the circuit have unitary matrices with
exclusively real coefficients (e.g. an H + TOFFOLI circuit).

Returns:
A (possibly gigantic) numpy array storing the superposition that
came out of the circuit for the given input state.

Raises:
ValueError: The circuit contains measurement gates that are not
ignored.
TypeError: The circuit contains gates that don't have a known
unitary matrix, e.g. gates parameterized by a Symbol.