How to use Qiskit for randomized benchmarking?

How to use Qiskit for randomized benchmarking?

We should first import the relevant qiskit classes for the demonstration: A RB protocol (see [1,2]) consists of the following steps: The RB sequences consist of random Clifford elements chosen uniformly from the Clifford group on n n -qubits, including a computed reversal element, that should return the qubits to the initial state.

How is randomized benchmarking used for quantum gates?

A scalable (in the number n n of qubits comprising the system) and robust algorithm for benchmarking the full set of Clifford gates by a single parameter using randomization techniques was presented in [1]. The concept of using randomization methods for benchmarking quantum gates is commonly called Randomized Benchmarking (RB).

How are the RB sequences chosen in Qiskit?

A RB protocol (see [1,2]) consists of the following steps: The RB sequences consist of random Clifford elements chosen uniformly from the Clifford group on n n -qubits, including a computed reversal element, that should return the qubits to the initial state. More precisely, for each length m m, we choose Km K m RB sequences.

Which is the best method for randomized benchmarking?

Both methods give metrics of fidelity in the n n -qubit space. For example, it is common to perform 2Q RB on the subset of two-qubits defining a CNOT gate while the other qubits are quiescent. As explained in [4], this RB data will not necessarily decay exponentially because the other qubit subspaces are not twirled.

How is quantum error correction used in Qiskit?

One is exactly what it is used for in Qiskit: as the first and simplest test of implementing the ideas behind quantum error correction. We will now implement these ideas explicitly using Qiskit. To see the effects of imperfect qubits, we simply can use the qubits of the prototype devices. We can also reproduce the effects in simulations.

Which is the latest version of Qiskit runtime?

This initial release of Qiskit Runtime uses Qiskit version 0.26.0, Terra version 0.17.3, and IBM Quantum Provider version 0.13.1. In this example we will use a preloaded Qiskit Runtime program called circuit-runner. We will first build a circuit using Qiskit, then execute it with Qiskit Runtime, taking advantage of its low-latency architecture.

How are quantum gates used in Qiskit circuit?

The initialization of q0 q 0 into a desired state |ψ⟩ | ψ ⟩ can then follow by applying single-qubit gates. Second, we apply a sequence of quantum gates that manipulate the three qubits as required by the teleportation algorithm. In this case, we only need to apply single-qubit Hadamard ( H H) and two-qubit Controlled-X ( ⊕ ⊕) gates.

How to find the average sequence fidelity in Qiskit?

Average over the Km K m random realizations of the sequence to find the averaged sequence fidelity, is the average sequence operation. Repeat Steps 1 through 4 for different values of m m and fit the results for the averaged sequence fidelity to the model: