import numpy as np

def simulate_error_correction_with_repetition(num_qubits, error_rate, repetition_factor):
    """
    Simulate error correction using the repetition code.

    Parameters:
    - num_qubits: Number of qubits in the quantum state.
    - error_rate: Probability of error in the quantum state.
    - repetition_factor: Factor by which the quantum state is repeated for error correction.

    Returns:
    - original_states: Original random quantum state.
    - received_states: Quantum states with errors.
    - corrected_states: Corrected quantum states after error correction.
    """
    original_states = np.random.choice([0, 1], size=num_qubits)
    error = np.random.choice([0, 1], size=num_qubits, p=[1-error_rate, error_rate])

    original_states_repeated = np.tile(original_states, repetition_factor)
    error_repeated = np.tile(error, repetition_factor)

    received_states = (original_states_repeated + error_repeated) % 2

    corrected_states = np.sum(
        np.reshape(received_states, (repetition_factor, num_qubits)),
        axis=0
    ) >= repetition_factor // 2

    return original_states, received_states, corrected_states

def measure_error_correction_accuracy(original_states, corrected_states):
    """
    Measure the accuracy of error correction.

    Parameters:
    - original_states: Original quantum state without errors.
    - corrected_states: Quantum states after error correction.

    Returns:
    - accuracy: Error correction accuracy as a percentage.
    """
    correct_count = np.sum(original_states == corrected_states)
    accuracy = correct_count / len(original_states)

    return accuracy