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IBM C1000-112 Exam Syllabus Topics:

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

1. Predict the output of the average_gate_fidelity, process_fidelity of the below snippet:
a = Operator(YGate())
b = np.exp(1j /2) * a
average_gate_fidelity(a,b)
process_fiedlity(a,b)

A) average_gate_fidelity will be 1.0 and process_fidelity will be 0.5
B) average_gate_fidelity will be 1.0 and process_fidelity will be 1.0
C) average_gate_fidelity will be 0.5 and process_fidelity will be 1.0
D) average_gate_fidelity will be 0 and process_fidelity will be 0.5

2. What is the output of the below snippet?
qc = QuantumCircuit(q, c)
qc.h(q)
qc.reset(q[0])
qc.measure(q, c)
job = execute(qc, backend, shots=1024)
job.result().get_counts(qc)

A) {'0': 1024}
B) {'1':1024}
C) {'0':200, '1':824}
D) {'0':500, '1':524}

3. Which of the following multi qubit-gate represents the controlled-z gate?

A)

B)

C)

D)

4. In the circuit given below having unitary simulator as the backend, choose the
_missing_element_from the options?
qc = QuantumCircuit(1)
qc.h(0)
backend_unitary = BasicAer.get_backend('unitary_simulator')
result = execute(qc,backend_unitary).result()._missing_element_

A) get_unitary_simulator()
B) get_unitary_result()
C) get_unitary_matrix()
D) get_unitary()

5. How does Qasm contribute to the execution of quantum circuits in simulators or actual quantum hardware?

A) It focuses on quantum gate optimization for faster computations
B) It provides the instructions for simulating or executing quantum operations
C) It translates quantum circuits into classical bits for execution
D) It serves as a visual representation tool for quantum operations

Solutions: