tfq.math.inner_product

Calculate the inner product between circuits.

tfq.math.inner_product(
    programs, symbol_names, symbol_values, other_programs
)

Compute (potentially many) inner products between the given circuits and the symbol free comparison circuits.

Calculates out[i][j] = $ \langle \psi{ ext{programs[i]} }
( ext{symbol_values[i]}) | \psi{ ext{other_programs[j]} } angle $

symbols = sympy.symbols('alpha beta')
qubits = cirq.GridQubit.rect(1, 2)
reference_circuits = [
    cirq.Circuit((cirq.H**symbols[0]).on_each(qubits)),
    cirq.Circuit(
        cirq.X(qubits[0]) ** symbols[0],
        cirq.Y(qubits[1]) ** symbols[1])
]
other_circuits = [
    cirq.Circuit(cirq.X.on_each(qubits)),
    cirq.Circuit((cirq.Y**0.125).on_each(qubits)),
    cirq.Circuit((cirq.X**0.5).on_each(qubits))
]
reference_tensor = tfq.convert_to_tensor(reference_circuits)
symbol_tensor = tf.convert_to_tensor([s.name for s in symbols])
values_tensor = tf.convert_to_tensor(np.arange(4).reshape(2, 2))
other_tensor = tfq.convert_to_tensor([other_circuits, other_circuits])
ip = tfq.math.inner_product(reference_tensor, symbol_tensor,
                            values_tensor, other_tensor)
ip
tf.Tensor(
    [[ 0+0.j, 8.8871640e-01+0.3681184j,
       0+0.5j],
     [ 0+0.j, 7.3223300e-02-0.17677669j,
       0-0.5j]],shape=(2, 3), dtype=complex64)

Args
`programs`	`tf.Tensor` of strings with shape [batch_size] containing the string representations of the circuits
`symbol_names`	`tf.Tensor` of strings with shape [n_params], which is used to specify the order in which the values in `symbol_values` should be placed inside of the circuits in `programs`.
`symbol_values`	`tf.Tensor` of real numbers with shape [batch_size, n_params] specifying parameter values to resolve into the circuits specificed by programs, following the ordering dictated by `symbol_names`.
`other_programs`	`tf.Tensor` of strings with shape [batch_size, n_others] containing the string representations of the circuits with which to compute the overlap on `programs` with. Must not contain any free symbols.

Returns
`tf.Tensor` with shape [batch_size, n_others] where `out[i][j]` is equal to the inner product of `programs[i]` with `symbol_values[i]` resolved in and `other_programs[i][j]`.

tfq.math.inner_product

Args

Returns