User Guide#
This guide provides an overview and explanation of the Fermioniq Python package, and how you can use it to submit quantum computing jobs to the Fermioniq platform. The content in the tutorials can serve as a starting point for your own Python scripts.
For details on specific modules, classes and functions, see the API reference.
Note
All the tutorials are based on Jupyter Notebooks. You can run all the tutorials yourself in this interactive Google Colab Notebook directly in your browser. You can also download the Colab notebook and run it locally on your machine.
These tutorials cover the different functionalities in the fermioniq package, from
your first submission of a quantum circuit to more advanced use cases and settings. They are
structured as Jupyter notebooks.
In section Setup we go over how to set up the emulator.
In section Emulating Quantum Circuits we cover the topics:
Sending your first quantum circuit to the emulator
Configuring the input and output of the emulator
Configuring the mode of emulation
Configuring the type of backend to use for the emulation (like CPU and GPU)
Section Advanced Emulation includes:
Emulating circuits with noise
Using the emulator to compute observables
Using the emulator to run a VQE algorithm
Running trajectory based emulations for circuits with intermediate measurements
In section Job Management we look at how to use the Client() class to:
Submit jobs asynchronously to the server
Submit multiple jobs at once
Note
All the code examples in the documentation have clickable links that take you to their corresponding page in the API reference. Try clicking on the class or the method call in the code example below to see it in action.
from fermioniq import Client
client = Client()
my_jobs = client.jobs()