qiskit.ignis.verification.calculate_1q_epg

calculate_1q_epg(gate_per_cliff, epc_1q, qubit)

Convert error per Clifford (EPC) into error per gates (EPGs) of single qubit basis gates.

Given that a standard 1Q RB sequences consist of u1, u2 and u3 gates, the EPC can be written using those EPGs:

where $N_{x}$ is the number of gate $x$ per Clifford. Assuming u1 composed of virtual-Z gate, ie FrameChange instruction, the $EPG_{U1}$ is estimated to be zero within the range of quantization error. Therefore the EPC can be written as:

Because u2 and u3 gates are respectively implemented by a single and two half-pi pulses with virtual-Z rotations, we assume $EPG_{U3} = 2EPG_{U2}$. Using this relation in the limit of $EPG_{U2} \ll 1$:

Finally the EPG of each basis gate can be written using EPC and number of gates:

To run this function, you first need to run a standard 1Q RB experiment with transpiled QuantumCircuit and count the number of basis gates composing the RB circuits.

import pprint
import qiskit.ignis.verification.randomized_benchmarking as rb
 
# assuming we ran 1Q RB experiment for qubit 0
gpc = {0: {'cx': 0, 'u1': 0.13, 'u2': 0.31, 'u3': 0.51}}
epc = 1.5e-3
 
# calculate 1Q EPGs
epgs = rb.rb_utils.calculate_1q_epg(gate_per_cliff=gpc, epc_1q=epc, qubit=0)
pprint.pprint(epgs)

{'u1': 0, 'u2': 0.0011278195488721805, 'u3': 0.002255639097744361}

In the example, gpc can be generated by gates_per_clifford(). The output of the function epgs can be used to calculate EPG of CNOT gate in conjugation with 2Q RB results, see calculate_2q_epg().

Parameters

• gate_per_cliff (Dict[int, Dict[str, float]]) – dictionary of gate per Clifford. see gates_per_clifford().
• epc_1q (float) – EPC fit from 1Q RB experiment data.
• qubit (int) – index of qubit to calculate EPGs.

Return type

Dict[str, float]

Returns

Dictionary of EPGs of single qubit basis gates.

Raises

QiskitError – when u2 or u3 is not found, cx gate count is nonzero, or specified qubit is not included in the gate count dictionary.