|
1 |
| -""" |
2 |
| -Build the quantum fourier transform (qft) for a desire |
3 |
| -number of quantum bits using Qiskit framework. This |
4 |
| -experiment run in IBM Q simulator with 10000 shots. |
5 |
| -This circuit can be use as a building block to design |
6 |
| -the Shor's algorithm in quantum computing. As well as, |
7 |
| -quantum phase estimation among others. |
8 |
| -. |
9 |
| -References: |
10 |
| -https://en.wikipedia.org/wiki/Quantum_Fourier_transform |
11 |
| -https://qiskit.org/textbook/ch-algorithms/quantum-fourier-transform.html |
12 |
| -""" |
13 |
| - |
14 | 1 | import math
|
15 |
| - |
16 | 2 | import numpy as np
|
17 |
| -import qiskit |
18 | 3 | from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
|
19 | 4 |
|
20 |
| - |
21 |
| -def quantum_fourier_transform(number_of_qubits: int = 3) -> qiskit.result.counts.Counts: |
| 5 | +def quantum_fourier_transform(number_of_qubits: int = 3) -> dict: |
22 | 6 | """
|
23 |
| - # >>> quantum_fourier_transform(2) |
24 |
| - # {'00': 2500, '01': 2500, '11': 2500, '10': 2500} |
25 |
| - # quantum circuit for number_of_qubits = 3: |
26 |
| - ┌───┐ |
27 |
| - qr_0: ──────■──────────────────────■───────┤ H ├─X─ |
28 |
| - │ ┌───┐ │P(π/2) └───┘ │ |
29 |
| - qr_1: ──────┼────────■───────┤ H ├─■─────────────┼─ |
30 |
| - ┌───┐ │P(π/4) │P(π/2) └───┘ │ |
31 |
| - qr_2: ┤ H ├─■────────■───────────────────────────X─ |
32 |
| - └───┘ |
33 |
| - cr: 3/═════════════════════════════════════════════ |
| 7 | + Build and simulate the Quantum Fourier Transform (QFT) circuit |
| 8 | + for a given number of qubits using the Qiskit framework. |
| 9 | + |
34 | 10 | Args:
|
35 |
| - n : number of qubits |
36 |
| - Returns: |
37 |
| - qiskit.result.counts.Counts: distribute counts. |
| 11 | + number_of_qubits (int): The number of qubits for the QFT circuit. |
38 | 12 |
|
39 |
| - >>> quantum_fourier_transform(2) |
40 |
| - {'00': 2500, '01': 2500, '10': 2500, '11': 2500} |
41 |
| - >>> quantum_fourier_transform(-1) |
42 |
| - Traceback (most recent call last): |
43 |
| - ... |
44 |
| - ValueError: number of qubits must be > 0. |
45 |
| - >>> quantum_fourier_transform('a') |
46 |
| - Traceback (most recent call last): |
47 |
| - ... |
48 |
| - TypeError: number of qubits must be a integer. |
49 |
| - >>> quantum_fourier_transform(100) |
50 |
| - Traceback (most recent call last): |
51 |
| - ... |
52 |
| - ValueError: number of qubits too large to simulate(>10). |
53 |
| - >>> quantum_fourier_transform(0.5) |
54 |
| - Traceback (most recent call last): |
55 |
| - ... |
56 |
| - ValueError: number of qubits must be exact integer. |
| 13 | + Returns: |
| 14 | + dict: A dictionary containing the counts of measurement results. |
| 15 | + |
| 16 | + Raises: |
| 17 | + ValueError: If the number of qubits is less than or equal to 0, |
| 18 | + greater than 10, or not an integer. |
| 19 | + TypeError: If the input is not an integer. |
57 | 20 | """
|
58 |
| - if isinstance(number_of_qubits, str): |
59 |
| - raise TypeError("number of qubits must be a integer.") |
| 21 | + if not isinstance(number_of_qubits, int): |
| 22 | + raise TypeError("Number of qubits must be an integer.") |
60 | 23 | if number_of_qubits <= 0:
|
61 |
| - raise ValueError("number of qubits must be > 0.") |
62 |
| - if math.floor(number_of_qubits) != number_of_qubits: |
63 |
| - raise ValueError("number of qubits must be exact integer.") |
| 24 | + raise ValueError("Number of qubits must be > 0.") |
64 | 25 | if number_of_qubits > 10:
|
65 |
| - raise ValueError("number of qubits too large to simulate(>10).") |
| 26 | + raise ValueError("Number of qubits too large to simulate (>10).") |
66 | 27 |
|
67 | 28 | qr = QuantumRegister(number_of_qubits, "qr")
|
68 | 29 | cr = ClassicalRegister(number_of_qubits, "cr")
|
69 |
| - |
70 | 30 | quantum_circuit = QuantumCircuit(qr, cr)
|
71 | 31 |
|
72 |
| - counter = number_of_qubits |
| 32 | + # Apply the QFT circuit |
| 33 | + for i in range(number_of_qubits): |
| 34 | + quantum_circuit.h(i) |
| 35 | + for j in range(i + 1, number_of_qubits): |
| 36 | + quantum_circuit.cp(np.pi / 2 ** (j - i), j, i) |
73 | 37 |
|
74 |
| - for i in range(counter): |
75 |
| - quantum_circuit.h(number_of_qubits - i - 1) |
76 |
| - counter -= 1 |
77 |
| - for j in range(counter): |
78 |
| - quantum_circuit.cp(np.pi / 2 ** (counter - j), j, counter) |
| 38 | + # Swap the qubits |
| 39 | + for i in range(number_of_qubits // 2): |
| 40 | + quantum_circuit.swap(i, number_of_qubits - i - 1) |
79 | 41 |
|
80 |
| - for k in range(number_of_qubits // 2): |
81 |
| - quantum_circuit.swap(k, number_of_qubits - k - 1) |
82 |
| - |
83 |
| - # measure all the qubits |
| 42 | + # Measure all qubits |
84 | 43 | quantum_circuit.measure(qr, cr)
|
85 |
| - # simulate with 10000 shots |
| 44 | + |
| 45 | + # Simulate the circuit with 10000 shots |
86 | 46 | backend = Aer.get_backend("qasm_simulator")
|
87 | 47 | job = execute(quantum_circuit, backend, shots=10000)
|
| 48 | + result = job.result() |
88 | 49 |
|
89 |
| - return job.result().get_counts(quantum_circuit) |
| 50 | + return result.get_counts(quantum_circuit) |
90 | 51 |
|
91 | 52 |
|
92 | 53 | if __name__ == "__main__":
|
93 |
| - print( |
94 |
| - f"Total count for quantum fourier transform state is: \ |
95 |
| - {quantum_fourier_transform(3)}" |
96 |
| - ) |
| 54 | + result_counts = quantum_fourier_transform(3) |
| 55 | + print(f"Total count for quantum fourier transform state is: {result_counts}") |
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