These samples demonstrate the use of the Quantum Development Kit for a variety of different quantum computing tasks.
Each sample is self-contained in a folder, and demonstrates how to use Q# to develop quantum applications.
A small number of the samples have additional installation requirements beyond those for the rest of the Quantum Development Kit. These are noted in the README.md files for each sample, along with complete installation instructions.
You can find instructions on how to install the Quantum Development Kit in our online documentation, which also includes an introduction to quantum programming concepts.
For a quick guide on how to set up a development environment from scratch using Visual Studio Code or Visual Studio Codespaces, see here.
A Docker image definition is also provided for your convenience, see here for instructions on how to build and use it.
If you're new to quantum or to the Quantum Development Kit, we recommend starting with the Getting Started samples.
After setting up your development environment using one of the options above, try to browse to samples/getting-started/teleportation
via the terminal and run dotnet run
. You should see something like the following:
Round 1: Sent False, got False.
Teleportation successful!
Round 2: Sent True, got True.
Teleportation successful!
Round 3: Sent False, got False.
Teleportation successful!
Round 4: Sent False, got False.
Teleportation successful!
Round 5: Sent False, got False.
Teleportation successful!
Round 6: Sent False, got False.
Teleportation successful!
Round 7: Sent True, got True.
Teleportation successful!
Round 8: Sent False, got False.
Teleportation successful!
Congratulations, you can now start quantum programming!
As you go further with quantum development, we provide several different categories of samples for you to explore:
- Algorithms: These samples demonstrate various quantum algorithms, such as database search and integer factorization.
- Arithmetic: These samples show how to coherently transform arithmetic data.
- Characterization: These samples demonstrate how to learn properties of quantum systems from classical data.
- Chemistry:
- Diagnostics: These samples show how to diagnose and test Q# applications.
- Error Correction: These samples show how to work with quantum error correcting codes in Q# programs.
- Interoperability: These samples show how to use Q# with different host languages.
- Numerics: The samples in this folder show how to use the numerics library.
- Runtime: These samples show how to work with the Q# simulation runtime.
- Simulation: These samples show how to simulate evolution under different Hamiltonians.
We also encourage taking a look at the unit tests used to check the correctness of the Quantum Development Kit samples.
This repo contains several configuration files that will make it easy to get started with coding. Below we lay out some instructions for getting started with VSCode or with Jupyter notebooks.
If you prefer to develop code locally, we recommend to install an editor such as Visual Studio Code. Make sure to install the .NET Core SDK 3.1 or later on your local machine. For more detailed instructions on how to set up VS Code for development with the QDK, go to our docs here.
Once you have installed VS Code and the .NET Core SDK, download this repository to your computer and open the folder in VS Code. The editor will automatically recognize the files in the .vscode
folder and request you to install the recommended extension. This includes the Microsoft Quantum Development Kit for Visual Studio Code extension, which is the fastest way to get started with the QDK.
Open a terminal to start running your first samples (see here).
Another way to quickly start developing in Q# is to use Docker and launch a Jupyter notebook on your local machine. You can use the included Dockerfile to create a docker image with all the necessary libraries to use the Quantum Development Kit to build quantum applications in C#, Python or Jupyter.
Once you have installed Docker, you can use the following commands to get you started:
To build the docker image and tag it iqsharp
:
docker build -t iqsharp .
To run the image in the container named iqsharp-container
with interactive command-line and redirect container port 8888 to local port 8888 (needed to run jupyter):
docker run -it --name iqsharp-container -p 8888:8888 iqsharp /bin/bash
From the corresponding container command line, you can run the C# version of the Teleportation sample using:
cd ~/samples/getting-started/teleportation && dotnet run
Similarly, you can run the Python version of the Teleportation sample using:
cd ~/samples/getting-started/teleportation && python host.py
Finally, to start Jupyter Notebook within the image for the Teleportation sample, use:
cd ~/samples/getting-started/teleportation && jupyter notebook --ip=0.0.0.0 --no-browser
Once Jupyter has started, you can open in your browser the Teleportation notebook (you will need a token generated by jupyter when it started on the previous step):
Once you're done, to remove container named iqsharp-container
:
docker rm --force iqsharp-container