Is there a function that gives the ideal probability distribution of a measurement in Qiskit?

Question

I want to compare the theoretical output of a circuit measurement with the actual output from a real quantum computer. I can approximate the ideal output by running the circuit on a simulator. However when you're measuring a state in superposition, the results you get from a simulator are still nondeterministic, making them not ideal for comparison.

For instance, when measuring a single qubit in even superposition (the state $\frac{1}{\sqrt{2}}(|0\rangle + |1\rangle)$, the ideal result would be that you measure $|0\rangle$ with probability $0.5$ and $|1\rangle$ with probability $0.5$. However, when running on a simulator, you might naturally get $|0\rangle$ with probability $0.501$ and $|1\rangle$ with probability $0.499$:

In other words, knowing that the theoretical probability of obtaining state $|\phi\rangle$ when measuring a state $|\psi\rangle$ is $\langle\phi|\psi\rangle$, is there a function in Qiskit to calculate this value from a circuit or state, or to get the ideal probability distribution that I can compare my actual distribution against?

Answer 1

You can use the statevector_simulator to return the statevector of your system. From this statevector, you can see the theoretical probability of obtaining each possible state for your system. For example:

qc = QuantumCircuit(2)
qc.x(0)

sim = Aer.get_backend('statevector_simulator')

job = execute(qc, sim)

print(job.result().get_statevector(qc))

will print out [0.+0.j 1.+0.j 0.+0.j 0.+0.j]. Each element refers to a possible 2-qubit state. The 0th element would refer to state 00, the 1st refers to 01, the 2nd to 10, and the 3rd to 11.

Answer 2

You can use the probabilities snapshot. Enter a snapshot as a circuit instruction:

circuit.snapshot_probabilities(label, qubits)

Then after execution get the probabilities from the result, see the documentation of Result.data.