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.github/CONTRIBUTING.md

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# Contributing
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If you would like to contribute to the Qiskit-tutorials, there are a number of ways to
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If you would like to contribute to the Qiskit IQX tutorials, there are a number of ways to
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get involved:
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* **Issues**: Issues can be reported with GitHub [issue
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* **Notebooks**: If you would like to contribute a notebook, please
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create a [fork](https://help.github.com/articles/fork-a-repo/) of the repository
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from the `master` branch and create a
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[pull requests](https://help.github.com/articles/about-pull-requests) for your change.
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[pull request](https://help.github.com/articles/about-pull-requests) for your change.
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Note that new notebooks should be placed in the relevant part of the
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[Community](./community/) section.
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.gitignore

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__pycache__/
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.cache/
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.ipynb_checkpoints/*
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qiskit/*/.ipynb_checkpoints/*
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qiskit/*/*/.ipynb_checkpoints/*
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community/*/.ipynb_checkpoints/*
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community/*/*/.ipynb_checkpoints/*
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community/*/*/*/.ipynb_checkpoints/*
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# ignores any checkpoints folder anywhere
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.ipynb_checkpoints/
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Qconfig.py
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qiskit/basics/Qconfig_IBMQ_experience.py
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qiskit/basics/Qconfig_IBMQ_network-dev.py
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.DS_Store
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qiskit/.ipynb_checkpoints/start_here-checkpoint.ipynb
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.stestr/

.stestr.conf

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[DEFAULT]
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test_path=./utils/test

INSTALL.md

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**Get the tutorials**<BR>
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For the full experience, you can start by downloading the latest release of the tutorials from [here](https://github.com/Qiskit/qiskit-tutorials/releases). Unzip the archive in the directory of your choice (this is the recommended way).
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For the full experience, you can start by downloading the latest release of the
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tutorials from [here](https://github.com/Qiskit/qiskit-iqx-tutorials/releases).
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Unzip the archive in the directory of your choice (this is the recommended
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way).
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To properly view and run the tutorials, you will need to install [Jupyter Notebook](https://jupyter.readthedocs.io/en/latest/install.html).
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To properly view and run the tutorials, you will need to install [Jupyter
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Notebook](https://jupyter.readthedocs.io/en/latest/install.html).
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## 2. Install Qiskit, Qiskit Aqua and Qiskit Aqua Chemistry
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At least [Python 3.5 or later](https://www.python.org/downloads/) is required to install and use Qiskit. If you have multiple Python versions installed (and particularly if the command `python --version` returns an incompatble version), you will need to ensure that your versions are [managed correctly](https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-python). This can be done using the `environment.yml` file, as detailed below.
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At least [Python 3.5 or later](https://www.python.org/downloads/) is required
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to install and use Qiskit. If you have multiple Python versions installed (and
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particularly if the command `python --version` returns an incompatible
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version), you will need to ensure that your versions are [managed
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correctly](https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-python).
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This can be done using the `environment.yml` file, as detailed below.
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When there are no issues with dependencies, Qiskit can be installed using
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```
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pip install qiskit
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```
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Or, pre-installed Qiskit can be updated using
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Or, a pre-installed Qiskit can be updated using
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```
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pip install -U qiskit
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```
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However, in case of issues with dependencies, we recommend the following installation procedure:
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However, in case of issues with dependencies, we recommend the following
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installation procedure:
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1. **Install [conda](https://conda.io/docs/index.html)**
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2. **Create conda environment for Qiskit and install packages** (with the accompanying `environment.yml` file)
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2. **Create conda environment for Qiskit and install packages** (with the
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accompanying `environment.yml` file)
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```
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cd qiskit-tutorial
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cd qiskit-iqx-tutorials
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conda env create -f environment.yml
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```
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- Create an [IBM Q](https://quantumexperience.ng.bluemix.net) account if
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you haven't already done so
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- Get an API token from the IBM Q website under “My
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Account” > “Advanced”
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- We are now going to add the necessary credentials to Qiskit. Take your token, here called `MY_API_TOKEN`,
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and pass it to the `IBMQ.save_account()` function:
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- Get an API token from the IBM Q website under “My Account" > "Qiskit in
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local environment"
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- We are now going to add the necessary credentials to Qiskit. Take your
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token, here called `MY_API_TOKEN`, and pass it to the `IBMQ.save_account()`
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function:
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```python
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from qiskit import IBMQ
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IBMQ.save_account('MY_API_TOKEN')
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```
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- Your credentials will be stored on disk. Once they are stored, at any point in the future you can load and use
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them via:
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- Your credentials will be stored on disk. Once they are stored, at any point
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in the future you can load and use them via:
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```python
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IBMQ.load_accounts()
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provider = IBMQ.load_account()
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```
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- For those who do not want to save their credentials to disk, please use
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```python
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IBMQ.enable_account('MY_API_TOKEN')
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provider = IBMQ.enable_account('MY_API_TOKEN')
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```
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and the token will only be active for the session.
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and the token will only be active for the session.
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## 4. Explore the Tutorials
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activate Qiskitenv
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```
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**Note for conda users**<BR>
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Verify that you have installed the right Jupyter Kernel, because in the last conda version it's not installed by default.
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Verify that you have installed the right Jupyter Kernel, because in the last
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conda version it's not installed by default.
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```
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python -m ipykernel install --user --name Qiskitenv --display-name "Python (Qiskitenv)"
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## 5. [Optional] Visualizing Circuits with LaTeX
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You can visualize your quantum circuits directly from Qiskit. Qiskit circuit drawers support text, LaTeX and matplotlib. The text and matplotlib version is entirely native to Python, and thus easy to use. The LaTeX version produces publication-quality circuit images, but relies on some pre-requisite software. These include the `pdflatex` compiler for rendering LaTeX documents, and the Poppler library for converting PDF to image. To get these:
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You can visualize your quantum circuits directly from Qiskit. Qiskit circuit
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drawers support text, LaTeX and matplotlib. The text and matplotlib version is
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entirely native to Python, and thus easy to use. The LaTeX version produces
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publication-quality circuit images, but relies on some pre-requisite software.
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These include the `pdflatex` compiler for rendering LaTeX documents, and the
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Poppler library for converting PDF to image. To get these:
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- Install [MiKTeX](https://miktex.org/download#unx)
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- Install Poppler:
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- Run: ```apt-get install -y poppler-utils```
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- Run: `apt-get install -y poppler-utils`
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- Install [MiKTeX](https://miktex.org/download).
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- Install Poppler:
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- Run:```brew install poppler```
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- Run: `brew install poppler`
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- Install [MiKTeX](https://miktex.org/download).
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- Install Poppler:
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- Download the [latest binary](http://blog.alivate.com.au/wp-content/uploads/2017/01/poppler-0.51_x86.7z).
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- Extract the downloaded `.7z` file into user directory:
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`c:\Users\<user_name>\`.
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- Extract the downloaded `.7z` file into user directory: `c:\Users\<user_name>\`.
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Note: You will need to have the [7zip software](https://www.7-zip.org/download.html) for this.
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- Add to PATH:
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- Right click on "This PC" -> Properties -> Advanced System Settings -> Environment Variables

README.md

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# Qiskit Tutorials
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# Qiskit IQX Tutorials
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[![License](https://img.shields.io/github/license/Qiskit/qiskit-tutorials.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)[![](https://img.shields.io/github/release/Qiskit/qiskit-tutorials.svg?style=popout-square)](https://github.com/Qiskit/qiskit-tutorials/releases)
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[![License](https://img.shields.io/github/license/Qiskit/qiskit-iqx-tutorials.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)[![](https://img.shields.io/github/release/Qiskit/qiskit-iqx-tutorials.svg?style=popout-square)](https://github.com/Qiskit/qiskit-iqx-tutorials/releases)
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Welcome to the [Qiskit](https://www.qiskit.org/) tutorials!
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Welcome to the [Qiskit](https://www.qiskit.org/) IQX Tutorials!
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In this repository, we've put together a collection of Jupyter notebooks aimed at teaching people who want to use Qiskit for writing quantum computing programs, and executing them on one of several backends (online quantum processors, online simulators, and local simulators). The online quantum processors are the [IBM Q](https://quantum-computing.ibm.com) devices.
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In this repository, we've put together a collection of Jupyter notebooks aimed
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at teaching people who want to use Qiskit for writing quantum computing
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programs, and executing them on one of several backends (online quantum
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processors, online simulators, and local simulators). The online quantum
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processors are the [IBM Q](https://quantum-computing.ibm.com) devices.
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For our community-contributed tutorials, please check out the [qiskit-community-tutorials](https://github.com/Qiskit/qiskit-tutorials-community) repository.
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For our community-contributed tutorials, please check out the
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[qiskit-community-tutorials](https://github.com/Qiskit/qiskit-community-tutorials)
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repository.
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## Installation
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The notebooks for these tutorials can be viewed here on GitHub...but for the full experience, you'll want to interact with them!
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The notebooks for these tutorials can be viewed here on GitHub...but for the
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full experience, you'll want to interact with them! The easiest way to do this
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is by logging into the [IBM Quantum
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Experience](https://quantum-computing.ibm.com/), which lets you use Jupyter
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notebooks, including these tutorials, via the web.
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The easiest way to do this is using [the Binder image](https://mybinder.org/v2/gh/qiskit/qiskit-tutorials/master?filepath=./qiskit/start_here.ipynb), which lets you use the notebooks via the web. This means that you don't need to download or install anything, but it also means that you should not insert any private information into the notebooks (such as your API key). We recommend, as pointed out in [issue #231](https://github.com/Qiskit/qiskit-tutorials/issues/231), that after you are done using mybinder that you regenerate your token.
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Please refer to this [installation guide](INSTALL.md) for setting up Qiskit and the tutorials on your own machine (this is the recommended way).
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Please refer to this [installation guide](INSTALL.md) for setting up Qiskit and
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the tutorials on your own machine (this is the recommended way).
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## Contents
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We've collected a core reference set of notebooks in this section outlining the features of Qiskit. We will be keeping them up to date with the latest Qiskit version.
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- [Basics](qiskit/fundamentals) is meant for those who are getting started.
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- [Terra](qiskit/advanced/terra) is meant for those who want to study circuits.
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- [Aer](qiskit/advanced/aer) is meant for those who want to simulate quantum circuits.
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- [Ignis](qiskit/advanced/ignis) is meant for those who want to study noise.
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- [Aqua](qiskit/advanced/aqua) is meant for those who want to develop applications on NISQ computers.
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We've collected a core reference set of notebooks in this section outlining the
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features of Qiskit. We will be keeping them up to date with the latest Qiskit
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version.
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- [Basics](qiskit/fundamentals) is for those who are getting started.
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- [Terra](qiskit/advanced/terra) is for those who want to study circuits.
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- [Aer](qiskit/advanced/aer) is for those who want to simulate quantum circuits.
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- [Ignis](qiskit/advanced/ignis) is for those who want to study noise.
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- [Aqua](qiskit/advanced/aqua) is for those who want to develop applications on NISQ computers.
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To go through the Qiskit examples, load up the [start_here.ipynb](qiskit/1_start_here.ipynb) notebook and start seeing how Qiskit works.
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To go through the Qiskit examples, load up the
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[start_here.ipynb](qiskit/1_start_here.ipynb) notebook and start seeing how
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Qiskit works.
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## Contribution Guidelines
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If you'd like to contribute to Qiskit Tutorials, please take a look at our
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[contribution guidelines](.github/CONTRIBUTING.md). This project adheres to Qiskit's [code of conduct](.github/CODE_OF_CONDUCT.md). By participating, you are expect to uphold to this code.
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If you'd like to contribute to Qiskit IQX Tutorials, please take a look at our
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[contribution guidelines](.github/CONTRIBUTING.md). This project adheres to
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Qiskit's [code of conduct](.github/CODE_OF_CONDUCT.md). By participating, you
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are expect to uphold to this code.
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We use [GitHub issues](https://github.com/Qiskit/qiskit-tutorials/issues) for tracking requests and bugs. Please use our [slack](https://qiskit.slack.com) for discussion and simple questions. To join our Slack community, use the [link](https://join.slack.com/t/qiskit/shared_invite/enQtNDc2NjUzMjE4Mzc0LTMwZmE0YTM4ZThiNGJmODkzN2Y2NTNlMDIwYWNjYzA2ZmM1YTRlZGQ3OGM0NjcwMjZkZGE0MTA4MGQ1ZTVmYzk). For questions that are more suited for a forum, we use the Qiskit tag in the [Stack Exchange](https://quantumcomputing.stackexchange.com/questions/tagged/qiskit).
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We use [GitHub issues](https://github.com/Qiskit/qiskit-iqx-tutorials/issues) for
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tracking requests and bugs. Please use our [Slack](https://qiskit.slack.com)
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for discussion and simple questions. To join our Slack community, use the
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[link](https://join.slack.com/t/qiskit/shared_invite/enQtNDc2NjUzMjE4Mzc0LTMwZmE0YTM4ZThiNGJmODkzN2Y2NTNlMDIwYWNjYzA2ZmM1YTRlZGQ3OGM0NjcwMjZkZGE0MTA4MGQ1ZTVmYzk).
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For questions that are more suited for a forum, we use the Qiskit tag in the
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[Stack
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Exchange](https://quantumcomputing.stackexchange.com/questions/tagged/qiskit).
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## Authors and Citation
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Qiskit Tutorials is the work of [many people](https://github.com/Qiskit/qiskit-tutorials/graphs/contributors) who contribute
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to the project at different levels. If you use Qiskit, please cite as per the included [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib).
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Qiskit IQX Tutorials is the work of [many
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people](https://github.com/Qiskit/qiskit-iqx-tutorials/graphs/contributors) who
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contribute to the project at different levels. If you use Qiskit, please cite
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as per the included [BibTeX
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file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib).
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## License
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environment.yml

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name: Qiskitenv
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dependencies:
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- python==3.6
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- python>=3.5
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- pip=18
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- matplotlib
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- notebook

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