The Quantum Information Software Kit (QISKit for short) is a software development kit (SDK) for working with OpenQASM and the IBM Q experience (QX).

Use QISKit to create quantum computing programs, compile them, and execute them on one of several backends (online Real quantum processors, online simulators, and local simulators). For the online backends, QISKit uses our python API client to connect to the IBM Q experience.

We use GitHub issues for tracking requests and bugs. Please see the IBM Q experience community for questions and discussion.

If you'd like to contribute to QISKit, please take a look at our contribution guidelines.

Links to Sections:

• Installation
• Creating your first Quantum Program
• More Information
• Authors
• License

At least Python 3.5 or later is needed for using QISKit. In addition, Jupyter Notebook is recommended for interacting with the tutorials. For this reason we recommend installing the Anaconda 3 python distribution, as it comes with all of these dependencies pre-installed.

In addition, a basic understanding of quantum information is very helpful when interacting with QISKit. If you're new to quantum, start with our User Guides!

For those more familiar with python, the fastest way to install QISKit is by using the PIP tool (a python package manager):

    pip install qiskit

An alternative method is to clone the QISKit SDK repository onto your local machine, and change into the cloned directory:

Select the "Clone or download" button at the top of this webpage (or from the URL shown in the git clone command), unzip the file if needed, and change into qiskit-sdk-py folder in a terminal window.

Or, if you have Git installed, run the following commands:

    git clone https://github.com/QISKit/qiskit-sdk-py
    cd qiskit-sdk-py

We recommend using python virtual environments to improve your experience. Refer to our Environment Setup documentation for more information.

Now that the SDK is installed, it's time to begin working with QISKit.

We are ready to try out a quantum circuit example, which runs via the local simulator.

This is a simple example that makes an entangled state.

from qiskit import QuantumProgram, QISKitError, RegisterSizeError

# Create a QuantumProgram object instance.
Q_program = QuantumProgram()
backend = 'local_qasm_simulator'
try:
    # Create a Quantum Register called "qr" with 2 qubits.
    qr = Q_program.create_quantum_register("qr", 2)
    # Create a Classical Register called "cr" with 2 bits.
    cr = Q_program.create_classical_register("cr", 2)
    # Create a Quantum Circuit called "qc" involving the Quantum Register "qr"
    # and the Classical Register "cr".
    qc = Q_program.create_circuit("bell", [qr], [cr])

    # Add the H gate in the Qubit 0, putting this qubit in superposition.
    qc.h(qr[0])
    # Add the CX gate on control qubit 0 and target qubit 1, putting 
    # the qubits in a Bell state
    qc.cx(qr[0], qr[1])

    # Add a Measure gate to see the state.
    qc.measure(qr, cr)

    # Compile and execute the Quantum Program in the local_qasm_simulator.
    result = Q_program.execute(["bell"], backend=backend, shots=1024, seed=1)

    # Show the results.
    print(result)
    print(result.get_data("bell"))

except QISKitError as ex:
    print('There was an error in the circuit!. Error = {}'.format(ex))
except RegisterSizeError as ex:
    print('Error in the number of registers!. Error = {}'.format(ex))

In this case, the output will be:

COMPLETED
{'counts': {'00': 512, '11': 512}}

This script is avaiable here.

You can also use QISKit to execute your code on a real Quantum Chip. In order to do so, you need to configure the SDK for using the credentials for your Quantum Experience Account:

1. Create an IBM Q experience> account if you haven't already done so

2. Get an API token from the IBM Q experience website under "My Account" > "Personal Access Token". This API token allows you to execute your programs with the IBM Q experience backends. Example.

3. You will insert your API token in a file called Qconfig.py. First copy the default version of this file from the tutorial folder to the main SDK folder (on Windows, replace cp with copy):

    $ cp Qconfig.py.default Qconfig.py

4. Open your Qconfig.py, remove the # from the beginning of the API token line, and copy/paste your API token into the space between the quotation marks on that line. Save and close the file.

5. If you have access to the IBM Q features, you also need to setup the values for your hub, group, and project. You can do so by filling the config variable with the values you can find on your IBM Q account page.

For example, a valid and fully configured Qconfig.py file would look like:

APItoken = '123456789abc...'

config = {
    'url': 'https://quantumexperience.ng.bluemix.net/api',
    # The following should only be needed for IBM Q users.
    'hub': 'MY_HUB',
    'group': 'MY_GROUP',
    'project': 'MY_PROJECT'
}

Once the Qconfig.py file is set up, it can be used for running Quantum Programs by passing its variables to QuantumProgram.set_api(). For example:

from qiskit import QuantumProgram
import Qconfig

# Creating Programs create your first QuantumProgram object instance.
Q_program = QuantumProgram()
Q_program.set_api(Qconfig.APItoken, Qconfig.config["url"], verify=False,
                  hub=Qconfig.config["hub"],
                  group=Qconfig.config["group"],
                  project=Qconfig.config["project"])

For more details on this and more information see our QISKit documentation.

Now you're set up and ready to check out some of the other examples from our Tutorial repository. Start with the index tutorial and then go to the ‘Getting Started’ example. If you already have Jupyter Notebooks installed, you can copy and modify the notebooks to create your own experiments.

To install the tutorials as part of the QISKit SDK, see the following installation details. Complete SDK documentation can be found in the doc directory and in the official QISKit site.

For more information on how to use QISKit, tutorial examples, and other helpful links, take a look at these resources:

• User Guides, a good starting place for learning about quantum information and computing
• Tutorials, for example notebooks, start with the index and ‘Getting Started’ Jupyter notebook
• OpenQASM, for additional information and examples of QASM code
• IBM Quantum Experience Composer, a GUI for interacting with real and simulated quantum computers
• QISkit Python API, an API to use the IBM Quantum Experience in Python

QISKit was originally developed by researchers and developers on the IBM-Q Team at IBM Research, with the aim of offering a high level development kit to work with quantum computers.

Visit the IBM Q experience community for questions and discussions on QISKit and quantum computing more broadly. If you'd like to contribute to QISKit, please take a look at our contribution guidelines.

• Korean Translation, Basic guide line written in Korean.

Ismail Yunus Akhalwaya, Jim Challenger, Andrew Cross, Vincent Dwyer, Mark Everitt, Ismael Faro, Jay Gambetta, Juan Gomez, Yunho Maeng, Paco Martin, Antonio Mezzacapo, Diego Moreda, Jesus Perez, Russell Rundle, Todd Tilma, John Smolin, Erick Winston, Chris Wood.

In future releases, anyone who contributes with code to this project is welcome to include their name here.

This project uses the Apache License Version 2.0 software license.