qaas 0.3.0

Quantum-as-a-Service utilizing IQMProvider, IQMBackend, IQMJob and HEAppE. Developed by IT4Innovations.

Access IQM quantum hardware through the LEXIS platform via HEAppE.

Documentation: https://it4innovations.github.io/quantum-as-a-service/

Requirements

• Python 3.11+

• required Python packages: see dependencies in pyproject.toml

Quick start

QaaS is available on PyPI, so you can install it easily using pip.

pip install qaas

Alternatively, you can install the latest (development) version using:

pip install git+https://github.com/It4innovations/quantum-as-a-service.git@main

Example usage:

from py4lexis.session import LexisSession
from qaas import QProvider
from qiskit import QuantumCircuit

token    = LexisSession().get_access_token()
backend  = QProvider(token, "my_project").get_backend("EQE1-CZ-P0001")

qc = QuantumCircuit(2, 2)
qc.h(0); qc.cx(0, 1); qc.measure_all()

counts = backend.run(backend.transpile(qc), shots=1000).result().get_counts()
print(counts)

Also OpenQASM is supported on input:

from qiskit.qasm3 import dumps as qasm3dumps

qc = QuantumCircuit(2, 2)
qc.h(0); qc.cx(0, 1); qc.measure_all()

qasm_transpiled_qc:str = qasm3dumps(backend.transpile(qc))

counts = backend.run([qasm_transpiled_qc], shots=1000).result().get_counts()
print(counts)

IQM Pulla

from qiskit import QuantumCircuit, visualization
from qiskit.compiler import transpile
from iqm.qiskit_iqm.iqm_transpilation import optimize_single_qubit_gates
from iqm.pulla.utils_qiskit import sweep_job_to_qiskit
from qaas.client import QProvider, QBackend
from qaas.client.qpulla import qiskit_to_pulla, QPullaBackendIQM

provider = QProvider(lexis_access_token, "my_project")
client = provider.get_client(lexis_resource_name)
dqa = client.get_dynamic_architecture()
compiler = p.get_standard_compiler()
# Create Pulla instance
p = provider.get_pulla(lexis_resource_name)
pulla_backend: QPullaBackendIQM = QPullaBackendIQM(dqa,p,compiler)

qc_transpiled = backend.transpile(
   qc,
   layout_method='sabre',
   optimization_level=0
)
# Optimize single-qubit gates
qc_optimized = optimize_single_qubit_gates(qc_transpiled)

circuits, compiler = qiskit_to_pulla(p, pulla_backend, [qc_optimized])
playlist, context = compiler.compile(circuits[0])
# Build settings for execution
settings, context = compiler.build_settings(context, shots=100)
# Submit playlist returns SweepJob
job = p.submit_playlist(playlist, settings, context=context)
job.wait_for_completion()

# Get raw results
raw_results = job.result()

# Convert to Qiskit result format
qiskit_result = sweep_job_to_qiskit(
   job,
   shots=100,
   execution_options=context['options']
)
# Qiskit Counts
counts = qiskit_result.get_counts()

Authors

• Jan Swiatkowski ([e-mail])

• Jakub Konvička ([e-mail])

• Jan Martinovič ([e-mail])

• Ladislav Foltyn ([e-mail])

License

Apache 2.0 — see LICENSE.