QAOA, sample measured bitstrings 100 times, Error

PennyLane Help
1 
def qaoa(n_layers=1):
    
    
    print("\np={:d}".format(n_layers))

    # initialize the parameters near zero
    init_params = 0.01 * np.random.rand(2, n_layers)

    # minimize the negative of the objective function
    def objective(params):
        
        gammas = params[0]
        betas = params[1]
        neg_obj = 0
        for idx in range(zahl_qubits):
            obj = circuit(gammas, betas, edge=graph1[idx], n_layers=n_layers)
        return obj

    # initialize optimizer: Adagrad works well empirically
    opt = qml.GradientDescentOptimizer(stepsize=0.01)

    # optimize parameters in objective
    params = init_params
    steps = 30
    for i in range(steps):
        params = opt.step(objective, params)
        if (i + 1) % 5 == 0:
            print("Objective after step {:5d}: {: .7f}".format(i + 1, objective(params)))

    # sample measured bitstrings 100 times
    n_samples = 10
    bit_strings = []

    for i in range(n_samples):
        gamma = params[0]
        beta = params[1]
        bit_string = int(circuit(gamma, beta, edge = None, n_layers = n_layers))
        print(bit_string)
        bit_strings.append(bit_string)

    # print optimal parameters and most frequently sampled bitstring
    counts = np.bincount(np.array(bit_strings))
    most_freq_bit_string = np.argmax(counts)
    print("Optimized (gamma, beta) vectors:\n{}".format(params[:, :n_layers]))
    print("Most frequently sampled bit string is: {:05b}".format(most_freq_bit_string))

    return objective(params), bit_strings

b1=qaoa(n_layers=1)

Error comes when I give shots more than 1 in dev = qml.device("default.qubit", wires=n_wires, shots=5)

p=1
Objective after step     5:  0.2000000
Objective after step    10: -0.2000000
Objective after step    15: -0.2000000
Objective after step    20: -0.2000000
Objective after step    25:  0.2000000
Objective after step    30: -0.2000000
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-309-01b03994f51e> in <module>
      1 #perform qaoa on our graph with p=1,2 and # keep the bitstring sample lists
----> 2 b1=qaoa(n_layers=1)

<ipython-input-308-61abd27f982d> in qaoa(n_layers)
     35         gamma = params[0]
     36         beta = params[1]
---> 37         bit_string = int(circuit(gamma, beta, edge = None, n_layers = n_layers))
     38         print(bit_string)
     39         bit_strings.append(bit_string)

TypeError: only size-1 arrays can be converted to Python scalars
2

Hi @Amandeep!

Would you be able to post a fully contained, minimal non-working version to highlight this issue? That is,

  • The code posted should execute by itself, without needing any extra information

  • As much of the boilerplate has been removed, so that the posted code is as small as possible while still showing the error.

This will be a great help in allowing me to assist you in debugging this issue :slight_smile: