Execute the superposition experiment with the shots=1 parameter, then shots=1000, and then shots=8000. What is different
Posted: Sat Aug 12, 2023 4:54 am
When executing a quantum circuit, such as a superposition experiment, with different numbers of shots, the difference lies in the number of times the circuit is repeated or sampled. The number of shots determines how many times the measurement is performed, which directly affects the statistics and probabilities of obtaining different measurement outcomes.
Let's consider the superposition experiment where we prepare a qubit in a superposition state (Hadamard gate) and then measure it:
When you execute the above code with different numbers of shots, you'll notice the following differences:
shots=1: With only one shot, you're effectively performing a single measurement. The outcome will be either '0' or '1', representing the possible measurement results for the superposition state.
shots=1000: With 1000 shots, you're sampling the measurement outcomes 1000 times. This allows you to estimate the probabilities of measuring '0' and '1' based on the superposition state. The distribution of measurement outcomes will start to resemble the expected probabilities.
shots=8000: Increasing the number of shots to 8000 further improves the accuracy of the probability estimates. The distribution of outcomes will be even closer to the theoretical probabilities of a superposition state.
In summary, the main difference between the different numbers of shots is the quality of the statistics you obtain. As the number of shots increases, the measurement outcomes will converge to the expected probabilities for the given quantum state or circuit.
Let's consider the superposition experiment where we prepare a qubit in a superposition state (Hadamard gate) and then measure it:
Code: Select all
from qiskit import QuantumCircuit, Aer, execute
# Create a quantum circuit
circuit = QuantumCircuit(1)
circuit.h(0) # Apply Hadamard gate
circuit.measure_all() # Measure all qubits
# Choose the simulator backend
simulator = Aer.get_backend('qasm_simulator')
# Execute the circuit with different numbers of shots
for shots in [1, 1000, 8000]:
job = execute(circuit, simulator, shots=shots)
result = job.result().get_counts()
print(f"Shots: {shots}, Measurement Results: {result}")
shots=1: With only one shot, you're effectively performing a single measurement. The outcome will be either '0' or '1', representing the possible measurement results for the superposition state.
shots=1000: With 1000 shots, you're sampling the measurement outcomes 1000 times. This allows you to estimate the probabilities of measuring '0' and '1' based on the superposition state. The distribution of measurement outcomes will start to resemble the expected probabilities.
shots=8000: Increasing the number of shots to 8000 further improves the accuracy of the probability estimates. The distribution of outcomes will be even closer to the theoretical probabilities of a superposition state.
In summary, the main difference between the different numbers of shots is the quality of the statistics you obtain. As the number of shots increases, the measurement outcomes will converge to the expected probabilities for the given quantum state or circuit.