C1000-112 無料問題集「IBM Fundamentals of Quantum Computation Using Qiskit v0.2X Developer」

Which Qiskit function is used to visualize the statevector of a quantum circuit?

What does a Qasm file typically contain?

If we have n qubits, how many states can we represent maximum?

What will be the output of the result variable in the below snippet?
q = QuantumRegister(1,'q')
qc = QuantumCircuit(q)
qc.z(0)
backend_unitary = BasicAer.get_backend('unitary_simulator')
result = execute(qc,backend_unitary).result().get_unitary(decimals=3)

Which technique is commonly used to extract meaningful information from the measurement outcomes in quantum experiments?

What does the function show_configuration() in Qiskit typically display?

In the below quantum circuit, to measure the output of qubit which of the below will be used?
qc = QuantumCircuit(1)
qc.x(0)

What is the primary advantage of using BasicAer simulators in Qiskit?

How can the Aer provider's simulators be beneficial for users when experimenting with quantum algorithms?

Which of the following bloch_multivector plot options given below is the correct one for the given bell quantum circuit?
qc = QuantumCircuit(2)
qc.x(0)
qc.h(0)
qc.h(1)

In Qiskit, what function allows users to display a list of available backends for quantum computation?

Which of the following commands will result in |i> basis state?
i.e. |i> = 1/√2(|0〉+i|1〉)

Which line of code would assign a unitary simulator object to the variable backend?

Which code fragment will produce a multi-qubit gate other than a CNOT?

How do the principles of uncertainty in quantum mechanics affect information encoding?

In the below QuantumCircuit, how many Qubits are there?
bob = QuantumRegister(8,'b')
alice = ClassicalRegister(2,'a')
eve = QuantumRegister(4,'e')
qc = QuantumCircuit(bob,alice,eve)

Choose the Toffoli gate in the given options:

In the below code, which of the following statement is non-unitary?
qc= QuantumCircuit(2,2)
qc.x(0)
qc.y(1)
qc.z(1)
qc.measure([0,1],[0,1])

What is the output of the below snippet?
a = 1/np.sqrt(2)
desired_state = [a,np.sqrt(1-a**2)]
qc = QuantumCircuit(1)
qc.initialize(desired_state,0)
back_sv = BasicAer.get_backend('statevector_simulator')
result = execute(qc, back_sv).result()
qc_sv = result.get_statevector(qc)
state_fidelity(desired_state, qc_sv)

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