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.
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At least Python 3.5 or later is needed for using QISKit. In addition, Jupyter Notebooks is recommended for interacting with the tutorials. For this reason we recomend installing 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 recomend 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 some QASM examples, which runs via the local simulator.
This is a simple superpesition example.
from qiskit import QuantumProgram
# Creating Programs create your first QuantumProgram object instance.
Q_program = QuantumProgram()
# Creating Registers create your first Quantum Register called "qr" with 2 qubits
qr = Q_program.create_quantum_register("qr", 2)
# create your first Classical Register called "cr" with 2 bits
cr = Q_program.create_classical_register("cr", 2)
# Creating Circuits create your first Quantum Circuit called "qc" involving your Quantum Register "qr" # and your Classical Register "cr"
qc = Q_program.create_circuit("superposition", [qr], [cr])
# add the H gate in the Qubit 0, we put this Qubit in superposition
qc.h(qr[0])
# add measure to see the state
qc.measure(qr, cr)
# Compiled and execute in the local_qasm_simulator
result = Q_program.execute(["superposition"], backend='local_qasm_simulator', shots=1024)
# Show the results
print(result)
print(result.get_data("superposition"))
In this case, the output will be:
COMPLETED
{'00': 509, '11': 515}
You can also use QISKit to execute your code on a real Quantum Chip.
First, get your API token:
- Create an
IBM Q experience <https://quantumexperience.ng.bluemix.net>__ account if you haven't already done so - 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 into the IBM Q experience backends. Example.
More details on this and more so in our QISKit documentation.
Now you're set up and ready to check out some of the other examples from our Tutorials 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 installation details. Complete SDK documentation can be found in the doc directory.
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.
Jim Challenger, Andrew Cross, Ismael Faro, Jay Gambetta, Juan Gomez, Paco Martin, Antonio Mezzacapo, Jesus Perez, and 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.