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def random_bitstring_generator(bit_number, backend):
    """
    Generate a bitstring with one qubit
    :param bit_number: number of bits that we want to generate
    :param backend: Qiskit hardware or simulator
    :return: string object with random bits
    """

    bitstring = ""

    one_qubit_random_bit_generator_circuit = QuantumCircuit(1,1)
    one_qubit_random_bit_generator_circuit.h(0)
    one_qubit_random_bit_generator_circuit.measure(0,0)

    for _ in range(bit_number):
        counts = execute(one_qubit_random_bit_generator_circuit, backend, shots=1000).result().get_counts()
        bit = list(counts.keys())[0]  # we have only one key because shots=1
        bitstring += bit

    return bitstring


backend = BasicAer.get_backend('qasm_simulator')

print(random_bitstring_generator(512, backend))

Executed the above code for QRNG using 1 qubit and received a 512 bit sequence 512 bit output

Executing the same circuit for 3 qubit code as given in image received an output of increased length as shown in image3 qubit qrng

increased length ouptut for 3 qubit qrng implementation of 512 bits

Also how can i change the backend from qasm_simulator to vigo/melbourne/any other quantum machine

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The number of bits in the counts dictionary equals the number of qubits in the circuit. So in your first example, you have a 1-qubit circuit, therefore you're dictionary looks something like

counts = {'0': 400, '1': 600}  # for for 1000 shots
counts = {'0': 1} # for 1 shot

In the second example, the Jupyter notebook screenshot, you have three qubits. Therefore

counts = {'000': 70, '010': 80, '110': 70, ... }  # for for 1000 shots
counts = {'101': 1} # for 1 shot

Since you add these bitstrings together, the resulting bitstring will be three times longer in the second case.


Side note: You are actually running a 1000 shots, not one, you should change the argument shots=1000 to shots=1.

You might also want to have a look at the get_memory method of the job, which allows you to run e.g. 512 shots and get all single measurements, which should be more efficient than running a 1-shot experiment 512 times.

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To execute on hardware backend:

provider = IBMQ.load_account()
backend = provider.get_backend('ibmq_vigo') 
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