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Boulder Opal at a glance and quickstart

Boulder Opal overview

Boulder Opal is a versatile Python toolset that provides everything a research team needs to automate and optimize quantum hardware performance at scale for quantum computing and quantum sensing.

The challenges of hardware instability, onerous manual tune-up, and increasing complexity with system scaling can dramatically slow down progress. Boulder Opal helps research teams to overcome these challenges and accelerate progress by leveraging five core capabilities based on a powerful discipline called quantum control engineering:

  • Characterize hardware: Identify key system parameters and imperfections for effective calibration, simulation, and optimization.

  • Design error-robust controls: Create control solutions to manipulate quantum systems that are resilient to noise and errors.

  • Simulate quantum dynamics:
    Understand and anticipate the behavior of complex quantum devices under realistic conditions.

  • Automate hardware with AI: Automate and speed up calibration and optimization with closed-loop agents at scale.

  • Verify performance: Evaluate control solutions to gain insights and ensure effectiveness.

If you want to learn more, you can read our Boulder Opal overview topic. In this get started guide, you will run through the steps to get Boulder Opal ready for your calculations.

Setup

1. Sign up for an account

You will need to sign up for a Q-CTRL account to get started with Boulder Opal for free.

2. Install the Q-CTRL Python package

To get started quickly and easily, we recommend Anaconda—a free and open-source distribution of the Python and R programming languages for scientific computing. The Q-CTRL Python package requires Python 3.8 or later.

Once you're set up with a valid Python version, install the Q-CTRL Python package using pip on the command line.

pip install qctrl

Several of the Boulder Opal user guides and application notes use the Q-CTRL Open Controls package. You can also install it using pip.

pip install qctrl-open-controls

If you already have the qctrl package installed and wish to update to the latest version, use the upgrade flag in pip.

pip install --upgrade qctrl

You can similarly update the qctrl-open-controls package.

3. Start a Boulder Opal session

Import the Q-CTRL Python package in your Jupyter notebook or Python script, and start a session by creating a Qctrl object:

# Import Q-CTRL Python package.
from qctrl import Qctrl

# Start a Boulder Opal session.
qctrl = Qctrl()

An authentication link will open up automatically, or be provided for you to copy and open in your browser of choice. You will be asked to enter your credentials if you are not already authenticated on our web app.

It should look something like this:

Authentication URL:

https://id.q-ctrl.com/auth/...

The URL above should be automatically opened in your default web browser.
(Please copy and paste if it doesn't open automatically)

Authenticate your credentials in your browser...

Finalizing authentication...
Successful authentication!

You can also call the authentication tool from your command-line interface with qctrl auth.

You are now ready to run your calculations! You can monitor your calculations and manage your computing resources on the Boulder Opal web app. Check out our tutorials, guiding you through Boulder Opal's core capabilities step by step, and topics, discussing the key concepts surrounding Boulder Opal.

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Topics

Background information for the use of Boulder Opal in quantum research