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.


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)



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.


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.


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

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

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