78 lines
2.1 KiB
Python
78 lines
2.1 KiB
Python
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import numpy as np
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from qiskit import (
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QuantumCircuit,
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execute,
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Aer)
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from qiskit.visualization import plot_histogram, plot_bloch_vector
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from matplotlib import pyplot as plt
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from collections import defaultdict
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# Use Aer's qasm_simulator
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simulator = Aer.get_backend('qasm_simulator')
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def create_bloch_vector(theta, phi):
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x = np.sin(theta) * np.cos(phi)
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y = np.sin(theta) * np.sin(phi)
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z = np.cos(theta)
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return [x, y, z]
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def perform_exp(iterations, case, draw=False):
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simulator = Aer.get_backend('qasm_simulator')
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all_counts = defaultdict(int)
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for i in range(iterations):
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qc = QuantumCircuit(2, 2)
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# uniform distribution on the sphere
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t = round(np.random.uniform(0, 1), 10)
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theta = np.arccos(1 - 2 * t)
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phi = round(np.random.uniform(0, 2 * np.pi), 10)
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CASE_ANGLES = {
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'identical': (theta, phi),
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'orthogonal': (theta + np.pi, phi)
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}
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qc.r(theta, phi, 0)
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theta1, phi1 = CASE_ANGLES[case]
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qc.r(theta1, phi1, 1)
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# print(theta, phi, phi1)
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if draw:
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q0 = create_bloch_vector(theta, phi)
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plot_bloch_vector(q0)
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plt.show()
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q1 = create_bloch_vector(theta1, phi1)
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plot_bloch_vector(q1)
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plt.show()
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# Measure in the Bell's basis
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qc.cx(0, 1)
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qc.h(0)
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qc.measure([0, 1], [0, 1])
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# print(qc)
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# execute the job
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job = execute(qc, simulator, shots=1)
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result = job.result()
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counts = result.get_counts(qc)
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for k, v in counts.items():
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all_counts[k] += v
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# gather all counts
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print("\nTotal counts for experiment '{}' are:\n".format(case))
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for k, v in sorted(all_counts.items(), key=lambda x: x[0]):
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print("{}: {}".format(k, v))
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if __name__ == "__main__":
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# draw produces a Bloch sphere but does not work in this notebook
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perform_exp(iterations=100, case='identical', draw=False) # same state
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perform_exp(iterations=100, case='orthogonal', draw=False) # different orthogonal states
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