Interleaved Randomized Benchmarking (IRB)

Interleaved Randomized Benchmarking (IRB)#

%load_ext autoreload
%autoreload 2

Set IQM Token if using Resonance#

# import os
# from iqm.qiskit_iqm import IQMProvider
#
# token = ""
# os.environ["IQM_TOKEN"] = token
# quantum_computer = "" # provide actual quantum computer name. i.e. "emerald", "garnet", "sirius"
# iqm_server_url = "https://resonance.iqm.tech/" # provide actual IQM server URL
# os.environ["IQM_SERVER_URL"] = iqm_server_url
#
# provider = IQMProvider(iqm_server_url, quantum_computer=quantum_computer)
# backend = provider.get_backend()

Alternatively choose (or define) a simulator backend#

#backend = "fakeadonis"
backend = "fakeapollo"

Interleaved Randomized Benchmarking Configuration#

1Q gate IRB#

from iqm.benchmarks.randomized_benchmarking.interleaved_rb.interleaved_rb import *
import numpy as np

EXAMPLE_IRB_1Q = InterleavedRBConfiguration(
    qubits_array=[[0],[2]],#,[4],[6]],[8],[10],[12],[14],[16],[17],[19]],
    sequence_lengths=[2**(m+1)-1 for m in range(8)],
    num_circuit_samples=25,
    shots=2**9,
    parallel_execution=True,
    interleaved_gate = "RGate",
    interleaved_gate_params = [np.pi, 0],
    simultaneous_fit = ["amplitude", "offset"],
    max_circuits_per_batch=100,
)

Run the experiment - 1Q gate IRB#

benchmark_irb_1Q = InterleavedRandomizedBenchmarking(backend, EXAMPLE_IRB_1Q)
run_irb_1Q = benchmark_irb_1Q.run()

Analyze the results - 1Q gate IRB#

result_irb_1Q = benchmark_irb_1Q.analyze()

result_irb_1Q.observations

for v in result_irb_1Q.plots.values():
    display(v)

2Q gate IRB#

EXAMPLE_IRB_2Q = InterleavedRBConfiguration(
    qubits_array=[[0,1],[3,4]],#,[8,9],[13,14],[17,18],[5,6],[10,11],[15,16]],
    sequence_lengths=[2**(m+1)-1 for m in range(7)],
    num_circuit_samples=25,
    shots=2**8,
    parallel_execution=True, # whether RB is run in parallel - use if you know what you're doing!
    interleaved_gate = "CZGate",
    interleaved_gate_params = None,
    simultaneous_fit = ["amplitude", "offset"],
    max_circuits_per_batch=100,
)

Run the experiment - 2Q gate IRB#

benchmark_irb_2Q = InterleavedRandomizedBenchmarking(backend, EXAMPLE_IRB_2Q)
run_irb_2Q = benchmark_irb_2Q.run()

Analyze the results - 2Q gate IRB#

result_irb_2Q = benchmark_irb_2Q.analyze()

for plot in result_irb_2Q.plots.values():
    display(plot)

IRB for non-native gate#

EXAMPLE_IRB_iswap = InterleavedRBConfiguration(
    qubits_array=[[3,4],[8,9]],
    sequence_lengths=[2**(m+1)-1 for m in range(7)],
    num_circuit_samples=30,
    shots=2**10,
    parallel_execution=True, # whether RB is run in parallel - use if you know what you're doing!
    interleaved_gate = "iSwapGate",
    interleaved_gate_params = None,
    simultaneous_fit = ["amplitude", "offset"],
    max_circuits_per_batch=100,
)

benchmark_irb_iswap = InterleavedRandomizedBenchmarking(backend, EXAMPLE_IRB_iswap)
run_irb_iswap = benchmark_irb_iswap.run()

result_irb_iswap = benchmark_irb_iswap.analyze()

for plot in result_irb_iswap.plots.values():
    display(plot)
Contents