qiskit_bell_state_circuit_simulation_with_statevector_primitives.py

1from qiskit import QuantumCircuit
2from qiskit.quantum_info import SparsePauliOp
3from qiskit_aer import AerSimulator
4from qiskit.visualization import plot_histogram
5import matplotlib.pyplot as plt
6
7# Create a new circuit with two qubits
8qc = QuantumCircuit(2)
9
10# Add a Hadamard gate to qubit 0
11qc.h(0)
12
13# Perform a Controlled-X gate on qubit 1, controlled by qubit 0
14qc.cx(0, 1)
15
16# Return a drawing of the circuit
17print(qc.draw())
18
19# The setup: we want to measure the observable ZIZ (Z on qubit 1, I on qubit 0)
20# and the observable ZZI (Z on both qubits)
21observable = SparsePauliOp.from_list([("ZZ", 1)])
22
23# Initialize the simulator
24simulator = AerSimulator()
25
26# Run the circuit and get the result
27# In modern Qiskit (1.x), we use Primitives to run circuits
28from qiskit.primitives import StatevectorEstimator
29
30estimator = StatevectorEstimator()
31job = estimator.run([(qc, observable)])
32result = job.result()
33
34print(f" > Expectation value: {result[0].data.evs}")
35
36# To get counts (measurement results), we add measurements and use Sampler
37qc.measure_all()
38from qiskit.primitives import StatevectorSampler
39
40sampler = StatevectorSampler()
41job = sampler.run([qc])
42result = job.result()
43
44# Extract the counts for the first (and only) pub result
45counts = result[0].data.meas.get_counts()
46print(f" > Counts: {counts}")
47
48# Plot the results
49plot_histogram(counts)
50plt.show()