Terra provides the foundations for Qiskit. It allows the user to write quantum circuits easily, and takes care of the constraints of real hardware.
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README.md

Qiskit Terra

PyPI Build Status Build Status IBM Q

Qiskit is a software development kit for developing quantum computing applications and working with NISQ (Noisy-Intermediate Scale Quantum) computers.

Qiskit is made up elements that each work together to enable quantum computing. This element is Terra and is the foundation on which the rest of Qiskit is built (see this post for an overview).

Installation

We encourage installing Qiskit via the PIP tool (a python package manager):

pip install qiskit

PIP will handle all dependencies automatically for us and you will always install the latest (and well-tested) version.

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.

See installing Qiskit for detailed instructions, how to build from source and using environments.

Creating your first quantum program

Now that Qiskit is installed, it's time to begin working with Terra.

We are ready to try out a quantum circuit example, which is simulated locally using the Qiskt Aer element. This is a simple example that makes an entangled state.

$ python
>>> from qiskit import *
>>> q = QuantumRegister(2)
>>> c = ClassicalRegister(2)
>>> qc = QuantumCircuit(q, c)
>>> qc.h(q[0])
>>> qc.cx(q[0], q[1])
>>> qc.measure(q, c)
>>> backend_sim = Aer.get_backend('qasm_simulator')
>>> result = execute(qc, backend_sim).result()
>>> print(result.get_counts(qc))

In this case, the output will be:

{'counts': {'00': 513, '11': 511}}

A script is available here, where we also show how to run the same program on a real quantum computer via IBMQ.

Executing your code on a real quantum chip

You can also use Qiskit to execute your code on a real quantum chip. In order to do so, you need to configure Qiskit for using the credentials in your IBM Q account:

Configure your IBMQ credentials

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

  2. Get an API token from the IBM Q website under My Account > Advanced > API Token.

  3. Take your token from step 2, here called MY_API_TOKEN, and run:

    >>> from qiskit import IBMQ
    >>> IBMQ.save_account('MY_API_TOKEN')
  4. If you have access to the IBM Q Network features, you also need to pass the url listed on your IBM Q account page to save_account.

After calling IBMQ.save_account(), your credentials will be stored on disk. Once they are stored, at any point in the future you can load and use them in your program simply via:

>>> from qiskit import IBMQ
>>> IBMQ.load_accounts()

For those who do not want to save there credentials to disk please use

>>> from qiskit import IBMQ
>>> IBMQ.enable_account('MY_API_TOKEN')

and the token will only be active for the session. For examples using Terra with real devices we have provided a set of examples in examples/python and we suggest starting with using_qiskit_terra_level_0.py and working up in the levels.

Contribution guidelines

If you'd like to contribute to Qiskit, please take a look at our contribution guidelines. This project adheres to Qiskit's code of conduct. By participating, you are expect to uphold to this code.

We use GitHub issues for tracking requests and bugs. Please use our slack for discussion. To join our Slack community use the link. To ask questions to Stack Overflow.

Next Steps

Now you're set up and ready to check out some of the other examples from our Qiskit Tutorial repository.

Authors

Qiskit Terra is the work of many people who contribute to the project at different levels.

License

Apache License 2.0