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qiskitalicebobprovider 0.7.2
Alice & Bob Qiskit provider
This project contains a provider that allows access to
Alice & Bob QPUs and emulators using
the Qiskit framework.
Full documentation
is available here
and sample notebooks using the provider
are available here.
Installation
You can install the provider using pip:
pip install qiskit-alice-bob-provider
pip will handle installing all the python dependencies automatically and you
will always install the latest (and well-tested) version.
Remote execution on Alice & Bob QPUs: use your API key
To obtain an API key, please contact Alice & Bob.
You can initialize the Alice & Bob remote provider using your API key
locally with:
from qiskit_alice_bob_provider import AliceBobRemoteProvider
ab = AliceBobRemoteProvider('MY_API_KEY')
Where MY_API_KEY is your API key to the Alice & Bob API.
print(ab.backends())
backend = ab.get_backend('EMU:1Q:LESCANNE_2020')
The backend can then be used like a regular Qiskit backend:
from qiskit import QuantumCircuit, execute
c = QuantumCircuit(1, 2)
c.initialize('+', 0)
c.measure_x(0, 0)
c.measure(0, 1)
job = execute(c, backend)
res = job.result()
print(res.get_counts())
Local emulation of cat qubit processors
This project contains multiple emulators of multi cat qubit processors.
from qiskit_alice_bob_provider import AliceBobLocalProvider
from qiskit import QuantumCircuit, execute, transpile
provider = AliceBobLocalProvider()
print(provider.backends())
# EMU:6Q:PHYSICAL_CATS, EMU:40Q:PHYSICAL_CATS, EMU:1Q:LESCANNE_2020
The EMU:nQ:PHYSICAL_CATS backends are theoretical models of quantum processors made
up of physical cat qubits.
They can be used to study the properties of error correction codes implemented
with physical cat qubits, for different hardware performance levels
(see the parameters of class PhysicalCatProcessor).
The EMU:1Q:LESCANNE_2020 backend is an interpolated model simulating the processor
used in the seminal paper by Raphaƫl
Lescanne in 2020.
This interpolated model is configured to act as a digital twin of the cat qubit
used in this paper.
It does not represent the current performance of Alice & Bob's cat qubits.
The example below schedules and simulates a Bell state preparation circuit on
a EMU:6Q:PHYSICAL_CATS processor, for different values of parameters
average_nb_photons and kappa_2.
from qiskit_alice_bob_provider import AliceBobLocalProvider
from qiskit import QuantumCircuit, execute, transpile
provider = AliceBobLocalProvider()
circ = QuantumCircuit(2, 2)
circ.initialize('0+')
circ.cx(0, 1)
circ.measure(0, 0)
circ.measure(1, 1)
# Default 6-qubit QPU with the ratio of memory dissipation rates set to
# k1/k2=1e-5 and cat size, average_nb_photons, set to 16.
backend = provider.get_backend('EMU:6Q:PHYSICAL_CATS')
print(transpile(circ, backend).draw())
# *Displays a timed and scheduled circuit*
print(execute(circ, backend, shots=100000).result().get_counts())
# {'11': 49823, '00': 50177}
# Changing the cat size from 16 (default) to 4 and k1/k2 to 1e-2.
backend = provider.get_backend(
'EMU:6Q:PHYSICAL_CATS', average_nb_photons=4, kappa_2=1e4
)
print(execute(circ, backend, shots=100000).result().get_counts())
# {'01': 557, '11': 49422, '10': 596, '00': 49425}
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