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Welcome to Boulder Opal!

We're excited that you're here to discover the most versatile and flexible AI-powered tools to support quantum hardware design, automation, and scaling. We want to help you get up and running as quickly as possible and have assembled a quick start guide for you.

What is Boulder Opal?

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 that can connect directly to your hardware.

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

It’s a perfect complement to advanced control electronics, serving as a critical design tool so you can tell the electronics what to output for your experiment. And it’s perfect for theorists too, providing advanced numerical packages used in the design and analysis of next-generation quantum devices. If you want to learn more, you can read our Boulder Opal overview topic.

Five steps to get moving fast

1. Install Boulder Opal (if you haven’t already) using our getting started guide. You’ll be up and running in just a few minutes.

2. Discover how our documentation works for Boulder Opal. We follow a framework that helps ensure you can find what you need, whether you’re just trying to learn about a topic or you’re deep into coding.

3. Execute a tutorial focused on how to design numerically optimized error-robust quantum logic gates. This simple tutorial is self contained and code-complete so you can execute step-by-step to get a feel for how Boulder Opal can help you solve your toughest problems.

4. Learn more about the breadth of features Boulder Opal delivers and the various ways that Boulder Opal can be applied to solve challenges in quantum computing and quantum sensing.

5. Browse our application notes where we show end-to-end solutions inspired by our users—many of which became the subject of technical publications. You’ll find deployments across the breadth of quantum technologies being studied today from superconducting qubits to NV diamond sensors.