quantumrings-toolkit-qiskit 0.1.4

Qiskit Backend for QuantumRings

Step 1. Import the required libraries

from qiskit.circuit import QuantumCircuit
from qiskit import QuantumCircuit, transpile, QuantumRegister, ClassicalRegister, AncillaRegister
from qiskit.visualization import plot_histogram
from matplotlib import pyplot as plt

import QuantumRingsLib
from QuantumRingsLib import QuantumRingsProvider
from quantumrings.toolkit.qiskit import QrBackendV2
from quantumrings.toolkit.qiskit import QrJobV1

from matplotlib import pyplot as plt

Step 2. Obtain the Quantum Rings Provider

Do not forget to replace your account key and account name.

qr_provider = QuantumRingsProvider(token = <ACCOUNT_KEY>, name=<ACCOUNT_NAME>)

Step 3. Build the Quantum Circuit using Qiskit provided functions

shots = 1000
numberofqubits = int(qr_provider.active_account()["max_qubits"])
q = QuantumRegister(numberofqubits , 'q')
c = ClassicalRegister(numberofqubits , 'c')
qc = QuantumCircuit(q, c)


# Create the GHZ state (Greenberger–Horne–Zeilinger)
qc.h(0);
for i in range (qc.num_qubits - 1):
    qc.cx(i, i + 1);

# Measure all qubits
qc.measure_all();

Step 4. Transpile the code for Quantum Rings SDK

mybackend = QrBackendV2(qr_provider)
qc_transpiled = transpile(qc, mybackend)

Step 5. Execute the code and plot the histogram

job = mybackend.run(qc_transpiled, shots = shots)
result = job.result()
counts = result.get_counts()
plot_histogram(counts)