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Advanced Algorithms and Data Structures3-5 Days$150
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Key Topics
  • Doctorate Programming Assignment Help
  • Implementation of Quantum Fourier Transform (QFT) in Python
  • How Our Experts Provide Superior Help with Doctorate Programming Assignments?
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Implementation of Quantum Fourier Transform (QFT) in Python

import numpy as np from qiskit import QuantumCircuit, execute, Aer def qft(circuit, n): """Apply Quantum Fourier Transform to the first n qubits of the given circuit.""" for qubit in range(n): circuit.h(qubit) for k in range(qubit + 1, n): circuit.cp(np.pi / float(2 ** (k - qubit)), k, qubit) for qubit in range(n // 2): circuit.swap(qubit, n - qubit - 1) # Example usage: n = 3 # Number of qubits qc = QuantumCircuit(n) qft(qc, n) qc.measure_all() # Simulate the circuit backend = Aer.get_backend('qasm_simulator') result = execute(qc, backend, shots=1024).result() counts = result.get_counts() print(counts)

The Quantum Fourier Transform (QFT) is a crucial algorithm for quantum computing that transforms a quantum state into its frequency domain. This code snippet illustrates a quantum circuit implementing the QFT.

By implementing QFT, students gain hands-on experience with quantum gates, circuits, and operations, allowing them to explore and experiment with quantum algorithms in real-world scenarios.

The complexity of the QFT algorithm challenges students to develop and refine their problem-solving skills in quantum programming, which is valuable for tackling other advanced quantum computing problems.

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