Skip to main content

Forest backend for Qiskit: run Qiskit code on Rigetti quantum computers or simulators

Project description

Forest backend for Qiskit

Allows running Qiskit code on Rigetti simulators and quantum computers by changing only two lines of your Qiskit code.

More goodies at https://quantastica.com

Install

pip install quantastica-qiskit-forest

Usage

Import ForestBackend into your Qiskit code:

from quantastica.qiskit_forest import ForestBackend

And replace Aer.get_backend with ForestBackend.get_backend.

Example

from qiskit import QuantumRegister, ClassicalRegister
from qiskit import QuantumCircuit, execute, Aer

# Import ForestBackend:
from quantastica.qiskit_forest import ForestBackend

qc = QuantumCircuit()

q = QuantumRegister(2, "q")
c = ClassicalRegister(2, "c")

qc.add_register(q)
qc.add_register(c)

qc.h(q[0])
qc.cx(q[0], q[1])

qc.measure(q[0], c[0])
qc.measure(q[1], c[1])


# Instead:
#backend = Aer.get_backend("qasm_simulator")

# Use:
backend = ForestBackend.get_backend("qasm_simulator")

# OR:
# backend = ForestBackend.get_backend("statevector_simulator")
# backend = ForestBackend.get_backend("Aspen-7-28Q-A")
# backend = ForestBackend.get_backend("Aspen-7-28Q-A", as_qvm=True)
# ...

# To speed things up a little bit qiskit's optimization can be disabled
# by setting optimization_level to 0 like following:
# job = execute(qc, backend=backend, optimization_level=0)
job = execute(qc, backend=backend)
job_result = job.result()

print(job_result.get_counts(qc))

Prerequisites

Running on your local Rigetti simulator

You need to install Rigetti Forest SDK and make sure that quilc compiler and qvm simulator are running:

Open new terminal and run:

quilc -S

And in one more new terminal run:

qvm -S -c

Running on Rigetti quantum computer

  • You need to get access to Rigetti Quantum Cloud Services (QCS)

  • In your Quantum Machine Image (QMI) install this package and Qiskit

  • Reserve a QPU lattice

  • Run your code via QMI terminal or Jupyter notebook served by your QMI

Details

Syntax

ForestBackend.get_backend(backend_name = None, as_qvm = False)

Arguments

backend_name can be:

  • any valid Rigetti lattice name

OR:

  • qasm_simulator will be sent to QVM as Nq-qvm (where N is number of qubits in the circuit)

  • statevector_simulator will be executed as WavefunctionSimulator.wavefunction()

If backend name is not provided then it will act as qasm_simulator

as_qvm boolean:

  • False (default)

  • True: if backend_name is QPU lattice name, then code will execute on QVM which will mimic QPU

That's it. Enjoy! :)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quantastica-qiskit-forest-0.9.20.tar.gz (12.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

quantastica_qiskit_forest-0.9.20-py3-none-any.whl (15.6 kB view details)

Uploaded Python 3

File details

Details for the file quantastica-qiskit-forest-0.9.20.tar.gz.

File metadata

  • Download URL: quantastica-qiskit-forest-0.9.20.tar.gz
  • Upload date:
  • Size: 12.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.7

File hashes

Hashes for quantastica-qiskit-forest-0.9.20.tar.gz
Algorithm Hash digest
SHA256 7ec179d1bfcddc9208a8b4dec2890b71855dc137ff1d2cc8c3d7b23d335bd69c
MD5 498ae8836c91ddd32206ea7fb08ee4b5
BLAKE2b-256 a677b9977675889f50f4b7f8565be90ea87174a5740b237c788731b2581e7998

See more details on using hashes here.

File details

Details for the file quantastica_qiskit_forest-0.9.20-py3-none-any.whl.

File metadata

  • Download URL: quantastica_qiskit_forest-0.9.20-py3-none-any.whl
  • Upload date:
  • Size: 15.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.7

File hashes

Hashes for quantastica_qiskit_forest-0.9.20-py3-none-any.whl
Algorithm Hash digest
SHA256 942644efd5981458c4e07754593cbd24a4958092ce2ed66f8d558d71592cf15a
MD5 66acd05bd521d47b7d4101578f13c13a
BLAKE2b-256 155df8bbb8b6335827a10aee539fd50eff85d0b76fcaf09c0959ee2db4f15d40

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page