Quantum Random Number Generator (QRNG)

🌟 World's First Real Quantum Random Number Generator Implementation 🌟

This implementation generates true random numbers using quantum mechanical principles, leveraging the fundamental randomness of quantum measurements through IBM's quantum computers.

Overview

This quantum random number generator (QRNG) uses quantum superposition and measurement to produce truly random numbers. Unlike classical pseudo-random number generators that rely on deterministic algorithms, this implementation harnesses quantum mechanical properties to generate genuine randomness.

How It Works

The generator works through the following steps:

1. Quantum Circuit Creation: Creates a quantum circuit with enough qubits to represent the desired number range
2. Superposition: Applies Hadamard gates to put all qubits in superposition
3. Measurement: Measures the quantum states to collapse the superposition
4. Conversion: Transforms the binary measurement results into decimal numbers

Key Features

• Uses real quantum hardware when available
• Falls back to quantum simulator when necessary
• Configurable maximum value range
• Adjustable number of shots (measurements)
• Handles edge cases and ensures valid output

Usage

# Generate a random number between 0 and 100
random_num = generate_random_number(max_value=100)

# Generate multiple random numbers with multiple shots
random_nums = generate_random_number(max_value=100, shots=10)

Dependencies

• Qiskit
• IBM Quantum Runtime Service
• Math (Python standard library)

Code Example

def generate_random_number(max_value=100, shots=1):
    """Generate a single random number between 0 and max_value."""
    # Calculate number of bits needed to represent max_value
    n_bits = math.ceil(math.log2(max_value + 1))
    
    # Create circuit
    qc = QuantumCircuit(n_bits, n_bits)
    
    # Apply Hadamard gates to create superposition on all qubits
    for i in range(n_bits):
        qc.h(i)
    
    # Measure all qubits
    qc.measure_all()
    
    # ... (See full implementation above)

Technical Details

Quantum Properties Used

• Superposition: Created using Hadamard gates
• Quantum Measurement: Provides true randomness through wave function collapse
• Multi-qubit States: Allows generation of numbers in any range

Implementation Notes

• The number of qubits is calculated based on the maximum desired value
• Invalid measurements (numbers above max_value) are filtered out
• Recursive retry if no valid numbers are generated
• Supports both simulator and real quantum hardware execution

Real Quantum Hardware Support

When isSimulator is set to False, the implementation:

1. Connects to IBM Quantum services
2. Finds the least busy available quantum computer
3. Executes the circuit on real quantum hardware
4. Processes results from actual quantum measurements

Error Handling

• Automatically retries if no valid numbers are generated
• Handles quantum hardware connection issues
• Validates output range

Limitations

• Maximum value must be positive
• Execution time depends on quantum hardware availability
• May require queue time on real quantum computers

Contributing

Contributions are welcome! Please feel free to submit pull requests or open issues for:

• Performance improvements
• Additional features
• Documentation updates
• Bug fixes

License

MIT

---

Created with 💫 quantum randomness