[Jan-2025] C1000-112 Braindumps – C1000-112 Questions to Get Better Grades

C1000-112 Exam Dumps - Try Best C1000-112 Exam Questions - ValidExam

IBM C1000-112 certification exam covers a wide range of topics related to quantum computing, including quantum mechanics, quantum circuits, quantum gates, quantum algorithms, and quantum error correction. C1000-112 exam is designed to test the candidate's understanding of these topics, as well as their ability to use the Qiskit SDK to develop and run quantum programs.

IBM C1000-112 (Fundamentals of Quantum Computation Using Qiskit v0.2X Developer) Exam is a professional certification that provides individuals with the skills, knowledge, and understanding of quantum computing using Qiskit v0.2X as a developer. Fundamentals of Quantum Computation Using Qiskit v0.2X Developer certification is accredited by IBM and recognizes the skills of individuals in the area of quantum computing. It is a valuable asset for professionals who are seeking career advancement or for students who want to demonstrate their expertise in the field.

IBM C1000-112 certification exam consists of 60 questions that must be completed within 90 minutes. C1000-112 exam is designed to assess a candidate's knowledge and understanding of quantum computing concepts, including quantum gates, quantum circuits, and quantum algorithms. Additionally, the exam assesses a candidate's ability to use Qiskit to develop and test quantum algorithms and applications.

 

NEW QUESTION # 60
What is the return type of the Qiskit Visualizations plots?

• A. PIL.Image
• B. matplotlib.Figure
• C. TextDrawing
• D. str

Answer: B

NEW QUESTION # 61
What does a Qasm file typically contain?

• A. Digital images representing qubit states
• B. Quantum circuit descriptions and quantum operations
• C. Classical binary data
• D. Classical programming instructions

Answer: B

NEW QUESTION # 62
Which statement will create a quantum circuit with five quantum bits and seven classical bits?

• A. QuantumCircuit(7)
• B.
• C. QuantumCircuit([5, 7])
• D. QuantumCircuit(5,7)

Answer: D

NEW QUESTION # 63
What is the default number of shots which QuantumCircuit.execute function performs?

• A. 0
• B. 1
• C. 2
• D. 3

Answer: B

NEW QUESTION # 64
Which of the below gates can be considered as Involutory?

• A. X-gate
• B. T-gate
• C. Y-gate
• D. S-gate
• E. H-gate
• F. P-gate

Answer: A,C,E

NEW QUESTION # 65
Which of the following commands will result in |i> basis state?
i.e. |i> = 1/√2(|0〉+i|1〉)

• A. H-gate followed by Y-gate
• B. H-gate followed by Z-gate
• C. Z-gate followed by H-gate
• D. H-gate followed by S-gate

Answer: D

NEW QUESTION # 66
What is the function of a quantum oracle in quantum algorithms?

• A. It provides classical inputs to quantum systems
• B. It speeds up quantum computations
• C. It implements a specific problem within a quantum algorithm
• D. It encodes classical information into quantum states

Answer: C

NEW QUESTION # 67
In quantum computing, what does a histogram of measurement outcomes represent?

• A. The probability of obtaining each classical bit value
• B. The distribution of entangled qubit states
• C. The number of gates applied in the circuit
• D. The representation of qubit error rates

Answer: A

NEW QUESTION # 68
Which of the following options given below depicts the given bloch_vector plot?

• A. plot_bloch_vector([0,0,-1])
• B. plot_bloch_vector([0,0,1])
• C. plot_bloch_vector([0,-1,0])
• D. plot_bloch_vector([1,0,1])

Answer: C

NEW QUESTION # 69
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)

• A. Error in executing state_fidelity
• B. 0
• C. 1.0
• D. 0.5

Answer: C

NEW QUESTION # 70
Which of the following statement will return a random state vector of dimension 2?

• A. random_get_statevector(2)
• B. random_get_statevector_operator(2)
• C. random_statevector(2)
• D. random_statevector_operator(2)

Answer: C

NEW QUESTION # 71
In the single-qubit quantum circuit, we apply the operators H, X, X, H, X in order, where X and H are Not and Hadamard operators respectively. (assume the qubit is initialized to |0>) What is the final state of the quantum circuit?

• A. -|1>
• B. |0>
• C. 1√2(|0>+|1>)
• D. 1√2(|0>-|1>)
• E. |1>

Answer: E

NEW QUESTION # 72
What is the purpose of executing a quantum experiment on a simulator?

• A. To validate quantum algorithms using classical computing resources
• B. To study the behavior of classical algorithms
• C. To generate random numbers efficiently
• D. To measure the performance of quantum hardware

Answer: A

NEW QUESTION # 73
Which quantum logic gate is commonly used to create entangled states?

• A. Toffoli gate
• B. Pauli-X gate
• C. CNOT gate
• D. Hadamard gate

Answer: C

NEW QUESTION # 74
Which line of code would assign a statevector simulator object to the variable backend?

• A. backend = BasicAer.StatevectorSimulatorPy()
• B. backend = BasicAer.get_back('statevector_simulator')
• C. backend = BasicAer.get_backend('statevector_simulator')
• D. backend = BasicAer.StatevectorSimulatorPy().name()

Answer: C

NEW QUESTION # 75
In the below code snippet, what is the probability of measuring |1>?
qc = QuantumCircuit(1)
qc.rx(3*math.pi/4, 0)

• A. 0.8536
• B. 0.5
• C. 1.0
• D. 0.1464

Answer: A

NEW QUESTION # 76
How does using BasicAer simulators differ from running experiments on actual quantum hardware?

• A. BasicAer simulators provide higher qubit capacity
• B. BasicAer simulators cannot handle quantum error correction codes
• C. BasicAer simulators produce noise-free ideal simulations
• D. BasicAer simulators execute quantum computations faster than hardware

Answer: C

NEW QUESTION # 77
How is the controlled-RX gate different from the CNOT gate in a quantum circuit?

• A. Controlled-RX gate applies a Pauli-X operation, while CNOT gate applies a Hadamard operation
• B. Controlled-RX gate is a single qubit gate, while CNOT gate is a two-qubit gate
• C. They are equivalent gates with different notations
• D. Controlled-RX gate applies a rotation around the X-axis, while CNOT gate flips the target qubit

Answer: D

NEW QUESTION # 78
In Qiskit, what function allows users to display a list of available backends for quantum computation?

• A. display_backends()
• B. show_backends()
• C. list_quantum_devices()
• D. available_backends()

Answer: B

NEW QUESTION # 79
Which of the below command is used to get the information about real quantum computers available in the qiskit?

• A.
• B.
• C.
• D.

Answer: D

NEW QUESTION # 80
In the below QuantumCircuit, how many Qubits are there?
q1 = QuantumRegister(7, 'q1')
q2 = ClassicalRegister(2, 'q2')
q3 = QuantumRegister(5, 'q3')
qc = QuantumCircuit(q1, q2, q3)

• A. 0
• B. 1
• C. 2
• D. 3

Answer: A

NEW QUESTION # 81
What would be the fidelity result(s) for these two operators, which differ only by global phase?
op_a = Operator(XGate())
op_b = numpy.exp(1j * 0.5) * Operator(XGate())

• A. state_fidelity() of 1.0
• B. average_gate_fidelity() and process_fidelity() of 1.0
• C. state_fidelity() and average_gate_fidelity() of 1.0
• D. state_fidelity(), average_gate_fidelity() and process_fidelity() of 1.0

Answer: B

NEW QUESTION # 82
Which code fragment will produce a multi-qubit gate other than a Toffoli?

• A. qc.ccx(0,1,2)
• B. qc.mct([0,1], 2)
• C. qc.cry(0,1,2)
• D. from qiskit.circuit.library import CXGate
  ccx = CXGate().control()
  qc.append(ccx, [0,1,2])

Answer: C

NEW QUESTION # 83
......

Verified C1000-112 exam dumps Q&As with Correct 250 Questions and Answers: https://www.validexam.com/C1000-112-latest-dumps.html