Quantum Random Number Generator (QRNG)

Overview

This project implements a Quantum Random Number Generator (QRNG) using Qiskit, a quantum computing framework. Unlike classical random number generators that rely on algorithms or pseudo-randomness, this QRNG uses the principles of quantum mechanics to produce true randomness.

Key Features

• Generates quantum-random binary sequences.
• Converts binary sequences into floating-point numbers.
• Demonstrates quantum principles such as superposition through practical implementation.

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How It Works

1. Quantum Bit (Qubit): Qubits are placed into a state of superposition using the Hadamard gate (H-gate). When measured, each qbit collapses to either 0 or 1 with equal probability, producing randomness.

2. Binary Sequence Generation: By preparing and measuring multiple qubits, the circuit generates a sequence of random bits.

3. Random Float Conversion: Binary sequences are interpreted as fractional numbers to produce a floating-point number between 0 and 1.

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Project Requirements

• Python 3.8+
• Qiskit
• Jupyter Notebook

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Usage

Generate n random bits, m times

random_bits = generate_random_bits(m,n)
print("Random Bits:", random_bits)

Generate m random floats, each using n bits

random_float = bits_to_float(generate_random_bits(m,n))
print("Random Float (0 to 1):", random_float)

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Results

By executing this QRNG, you should observe:

• A list of random floats in the range [0, 1) (e.g., 0.7465834309463501).

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References

• Qiskit Documentation
• IBM Quantum
• Hadamard Gate

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License

This project is licensed under the MIT License. Feel free to use, modify, and distribute!