Backend Interface

The backend interface contains a minimal set of features that apply to every gate-based quantum computer. The main motivation in designing the interface, is to provide a convenient setup for both clients and providers of physical quantum backends. To ensure compatibility to existing network architectures, the interface is realized as REST-based interface. Also available is a Thrift implementation of the same interface.

BackendServer

This class is a wrapper for convenient setup of a server, capable of processing quantum circuits. Backend providers simply have to create a Python function called run_func which receives a QuantumCircuit, an integer called shots and optionally a string called token. The return value should be the measurement results as a dictionary of bitstrings.

from qrisp.interface import BackendServer
from backend_provider import run_func, ping_func

server = BackendServer( run_func, port = 8080)

server.start()

BackendClient

This class can be used to connect to BackendServers in order to send out requests for processing quantum circuits.

from qrisp.interface import BackendClient
backend = BackendClient(server_ip, port)

from some_library import some_quantum_algorithm

qv = some_quantum_algorithm()

res = qv.get_measurement(backend = backend)

In this code snippet, we create connect a BackendClient, to the BackendServer running under the ip server_ip and port. Subsequently, we run some quantum algorithm returing a QuantumVariable and call the qrisp.QuantumVariable.get_measurement() method, to query the remote backend.

Docker Backend

This module describes the inbuilt Docker container to enable utilization of alternative simulation frameworks. It supports: Cirq (cirq.Simulator), MQT (ddsim qasm_simulator), Qiskit (Aer Backend), PyTket (AerBackend), Rigetti (numpy wavefunction simulator), Qulacs (sampler).

This functionality is meant to be accessed via a Docker container. Appropriate setup should be conducted. This setup includes: Installation of Docker, building of the image provided in this repo, and starting the container built with the image. Specific steps/ info for utilization in this context is given below.

VirtualBackend

The VirtualBackend class allows to run external circuit dispatching code locally and having adherence to the Qrisp interface at the same time. Using this class it is possible to use the (Python) infrastructure of any backend provider as a Qrisp backend.

QiskitBackend

This class is a wrapper for the VirtualBackend to quickly integrate Qiskit backend instances.

from qiskit import Aer
from qrisp.interface import QiskitBackend
qiskit_backend = Aer.get_backend('qasm_simulator')
vrtl_qasm_sim = QiskitBackend(qiskit_backend)

Naturally, this also works for non-simulator Qiskit backends.

IQMBackend

The IQMBackend class allows to run Qrisp programs on IQM quantum computers available via IQM Resonance. For an up-to-date list of device instance names check the IQM Resonance Dashboard. Devices available via IQM Resonance currently support up to 20 000 shots.

from qrisp.interface import IQMBackend
qrisp_garnet = IQMBackend(
   api_token = "YOUR_IQM_RESONANCE_TOKEN",
   device_instance = "garnet" # check the website for an up-to-date list of devices
)