Perform a single step of the Rosalin optimizer.

Update trainable parameters with one step of the optimizer and return the corresponding objective function value after the step. Args

The error in our approximation

Run the optimization protocol on the model using Mean Square Error as a loss function and using stochastic gradient descent as the optimizer.

Update trainable arguments with one step of the optimizer. .. warning:: When blocking is set to be True, use step_and_cost instea

Trainable circuit block.

Some function over the integers 0,...,N-1.

The standard QFT, redefined because the PennyLane one uses terminal SWAPs.

Accuracy score. Args: y_true (array[float]): 1-d array of targets y_predicted (array[float]): 1-d array of predictions st

Returns Pauli expectation vectors for each input using the given embedding.

Compute the model cost for relative parameters and given model data.

Uses QAOA to create a cost Hamiltonian for the MaxCut problem.

r"""Returns the rank of a binary matrix over :math:`\mathbb{Z}_2`.

Parametrized Hamiltonian driving the qubit in wire with a fixed frequency.

Construct repetition code parity check matrix for specified distance.

QJIT-compatible function to determine (a ** exp) % N. Source: https://en.wikipedia.org/wiki/Modular_exponentiation#Left-to-right_binary_method

root mean square difference

Chebyshev polynomial of order n.

We only take the first d coefficients [:d] because coefficients() treats the negative frequencies as different from the positive ones.

Measure a wire and then reset it back to the |0⟩ state.

Perform a single time step in the computational graph of the custom RNN.

Get a string representation for stabilizers and destabilizers from a Tableau

Apply CNOTs in sequence using the provided control and target wires

Input : (batchsize, 2, N**2) ndarray A batch of quantum states encoding grayscale images using the FRQI. Returns : (batchsize, N, N)

Data-encoding circuit block.

Given a circuit, creates a collection of snapshots consisting of a bit string and the index of a unitary operation. Args: circui

Compute the classical distance of the code based on the parity-check matrices.

Compute geometric difference g between classical and quantum kernels. Formula: g = sqrt( || sqrt(K_quantum) @ inv(K_classical) @ sqrt(K_quant