Illustration 2: QuantumPath solution with some quantum execution devices enabled

Uso de Q Provider Factory

·       Installl QrEngineer SDK.

To work with Q Provider Factory, it is necessary to install QrEngineer SDK if we did not already have it, for which it is necessary to execute the following instruction in a command console:

 pip install QrEngineerSDK

 Note: since these are Beta products, it is advisable to update the libraries if you already have them installed.

pip install –-upgrade QrEngineerSDK

·       Identify the main file of the quantum program to be integrated with QuantumPath®, in this case simon_algorithm.py.

·       Identify the line where the creation of the Circuit object with the definition of the quantum circuit ends and delete the code used to launch the experiment against the local simulator.

…

n = len(s)

circ = Circuit()

# Apply Hadamard gates to first n qubits

circ.h(range(n))

# Now apply the Oracle for f

circ.simons_oracle(s)

# Apply Hadamard gates to the first n qubits

circ.h(range(n))

print(circ)    # get number of qubits

                                                                     |                                                                    

task = device.run(circ, shots=4*n)

result = task.result()

counts = result.measurement_counts

plt.bar(counts.keys(), counts.values());

plt.xlabel(‘bit strings’);

plt.ylabel(‘counts’);

plt.xticks(rotation=90)

plt.show()

…

·       Add after that line, the Q Provider Factory code needed to transpile the circuit and run it through QuantumPath®: 

o   Add an import statement to the QProviderFactory class of the SDK.

 from QrEngineerSDK import QProviderFactory

o   Instantiate the QProviderFactory object, specifying the QuantumPath® credentials.

qprovider = QProviderFactory(user = ‘***qpath user***’, passwordSHA256=’***sha-256 encrypted password***’)

o   Transpile the original circuit to a QuantumPath® gate circuit, using the transpileAmazonCircuit instruction.

qpathCircuit = qProvider.transpileAmazonCircuit(circuit)

o   Launch the execution of the circuit through QuantumPath®, providing the solution identifier, the quantum device, the namespace, the name of the circuit and the number of executions or samples to be carried out.

qpathSolutionID = 10223
qpathDeviceID = 14 #AMAZON BRAKET 25qbits Local Simulator
qpathCircuitName = ‘SIMONS_ALGORITHM’
qpathNamespace = ‘TEST’
qpathNumRepeats = 100
result = qprovider.executeQPathCircuit(qpathSolutionID,qpathDeviceID,qpathCircuitName,qpathNamespace,qpathNumRepeats,qpathCircuit)

Note: As mentioned above, both the solution id and the quantum device id can be obtained from the information page of the solution itself in QuantumPath®. 

Once the circuit has been executed through QuantumPath®, it is necessary to recover the histogram resulting from the execution, to perform the aggregation of the results ignoring the measurement in the last qubits, beyond the n digits of the string, as in the original secret (n) example:

new_results = {}

histogramValues = list(qpathResult.histogram.values())[0]

for bitstring, count in histogramValues.items():        

# Only keep the outcomes on first n qubits

   trunc_bitstring = bitstring[:n]

   # Add the count to that of the of truncated bit string

new_results[trunc_bitstring] =
new_results.get(trunc_bitstring, 0) + count

The rest of the classical post-processing performed in the original example remains unchanged. 

Once the refactored code has been executed, the user can access the QuantumPath® platform and visualize the circuit and flow automatically generated by the SDK in the indicated solution and check the result of the execution on the platform.