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IBM Fundamentals of Quantum Computation Using Qiskit v0.2X Developer Sample Questions:

1. What information does the Bloch sphere visualization provide in quantum computing?

A) The probability amplitudes of qubits
B) Connectivity details of quantum hardware
C) A graphical representation of quantum circuits
D) A display of gate errors and noise in quantum systems

2. Which of the below command is used to get the information about real quantum computers available in the qiskit?

A)

B)

C)

D)

3. What is the output of the result in the below snippet?
ghz = QuantumCircuit(3)
ghz.x(0)
ghz.h(0)
ghz.cx([0,0],[1,2])
ghz.measure_all()
backend_qasm = BasicAer.get_backend('qasm_simulator')
job = execute(ghz, backend_qasm,shots=1024)
result = job.result().get_counts()

A) {'111': 300, '000': 724}
B) {'100': 253, '010': 261, '111': 253, '000': 261}
C) {'100': 514, '010': 510}
D) {'000': 512, '111':512}

4. Given this code fragment, which output fits most closely with the measurement probability distribution?
qc = QuantumCircuit(2, 2)
qc.x(0)
qc.measure([0,1], [0,1])
simulator = Aer.get_backend('qasm_simulator')
result = execute(qc, simulator, shots=1000).result()
counts = result.get_counts(qc)
print(counts)

A) {'10': 1000}
B) {'01': 1000}
C) {'00': 1000}
D) {'11': 1000}

5. In the circuit given below having statevector simulator as the backend, choose the
_missing_element_from the options?
qc = QuantumCircuit(1)
qc.x(0)
qc.z(0)
backend_state = BasicAer.get_backend('statevector_simulator')
result = execute(qc,backend_state).result()._missing_element_

A) get_state_simulator()
B) get_statevector()
C) get_statevector_state()
D) get_statevector_result()

Solutions: