Opal
Boulder Opal

Build superior
quantum computers

Move faster with the most powerful control design
and automation solution for the quantum era.

Compare plans
Atom ComputingAlice & Bob

Our clients

Chalmers UniversityNord QuantiqueNorthwestern UniversityPasqal

<5min

Time to integration

>99.9%

2-qubit gate fidelities

<4 hours

Time to device bring-up

Boulder Opal empowers hardware teams to solve
their biggest challenges

Quantum hardware teams must advance to bigger, higher performing devices, but these systems are notoriously sensitive and hard to control.

Boulder Opal provides cutting-edge control technologies through a familiar Python client so users can effectively design, automate, and scale quantum hardware.

With the Scale Up package, Q-CTRL uses industry-leading control expertise to collaborate on custom Boulder Opal solutions to solve critical performance and operational problems.

Design hardware and control solutions together

Quickly realize and expand your hardware's full potential

Push hardware to the limit with optimized control solutions

Accelerate workflows between theory and experimentation

Uncover critical system parameters that drive performance

Automate key control and characterization tasks

Reach peak efficiency and performance with automation

Title

Simplify repetitive characterization, optimization, and calibration tasks

Title

Achieve performance beyond what's possible manually

Title

Save hours through massive increases in efficiency

Scale control solutions for
broader impact

Reach commercial scale with bigger, higher quality devices.

Title

Standardize control routines for consistency and speed

Title

Maximize throughput while ensuring product quality

Title

Abstract technical workflows so anyone can do them

How it works

Boulder Opal provides access to the key building blocks of critical quantum control techniques so users can uncover the true characteristics of underlying hardware and then optimize the performance of that hardware to its full potential.

This is all delivered through a local Python client and cloud-accelerated computational tools to provide the scalability and speed required for quantum hardware development and deployment.

Simulation

Model quantum systems with integrated time-varying noise and signal libraries.

Model-based control

Design control solutions delivering peak performance based on the encoded quantum model.

Characterization

Accurately define hardware specifications, hamiltonian parameters, and environmental noise.

Closed-loop optimization

Implement automated feedback loops for various design, calibration, and hardware-performance optimization tasks.

Experiment scheduling

Orchestrate complex automated calibration and tuneup workflows constructed using Boulder Opal’s functions.

What’s included in Boulder Opal

These powerful capabilities support hardware teams with impactful control techniques to address problems that are otherwise out of reach.

Python client for easy integration
into current workflows

Comprehensive documentation
for easier onboarding

Cloud accelerated computation 
and web-based admin tools

Get up and running
in minutes

Boulder Opal integrates easily with common Python packages and a wide range of control electronics systems so you can add powerful new capabilities with minimal effort.

Software

Qiskit, Quil, QuTip, ARTIQ

Controllers

Quantum Machines, Qblox, Zurich Instruments, Tabor Quantum Solutions, Keysight

Hardware

We support superconducting, trapped ion, neutral atom, and other types of quantum hardware

We have the right plan for you

Start with our free Basic plan and upgrade if you need 
to further accelerate research and development progress.

Go to FAQs

Basic

$0

Free Basic plan, yearly limits apply

For beginners, students, and explorers

Cloud software platform

4 vCPU, 32 GB RAM machine

1 machine (1 calculation at a time)

12 cloud machine hours

Standard support

Essentials

$1,500

USD / year

Managed compute for small teams

Cloud software platform

8 vCPU, 64 GB RAM machine

1 machine (1 calculation at a time)

200 cloud machine hours

Standard support

Performance

$9.99

$5,000

USD / year

Expanded computational resources for performance minded teams

Cloud software platform

16 vCPU, 128 GB RAM machine

Up to 4 machines (1 calculation per machine)

400 cloud machine hours

Standard + solutions engineering support

Professional

HPC-like resourcing for demanding teams of scientists and engineers

Hybrid cloud software platform

32 vCPU, 256 GB RAM machines

Up to 16 machines (1 calculation per machine)

1600 cloud machine hours

Dedicated + solutions engineering support

Real-world use cases

Chalmers University of Technology

Chalmers achieves 8X faster quantum logic using Boulder Opal

With Boulder Opal, Chalmers was able to design totally new numerically optimized gates that enable massive speedups without introducing new gate errors.

>180X

Reduction in gate duration.

Read the case study

It was really easy to go from code to experiments. I started from the relevant notebook in the documentation, followed the steps, adapted when necessary, and it simply worked! We’re now using Q-CTRL pulses that allow us to cut the time of our gates by eight times.

Marina Kudra
PhD Student
,
Chalmers University of Technology
The University of Sydney

Making sense of quantum noise with machine learning

Q-CTRL's quantum control engineers developed a new machine-learning tool allowing high-fidelity reconstruction of the spectral “fingerprint” of quantum noise.

<1PPM

Sensitivity error-source identification during quantum logic.

Read the case study

Collaboration between experimentalists at University of Sydney and quantum control engineers at Q-CTRL breakthrough result published in Physical Review Letters

Dr. Cornelius Hempel
Research Fellow
,
The University of Sydney
Nord Quantique

Nord Quantique is accelerating the path to useful quantum error correction with Boulder Opal

Nord Quantique used Boulder Opal to design a hardware-efficient QEC protocol for a superconducting system where quantum information is encoded in GKP states.

14%

increase in logical qubit lifetime

Read the case study

Given the complexity of the physics at play, being able to perform closed-loop optimization of a few physically motivated parameters of the quantum error correction protocol with Boulder Opal is very valuable to us.

Dany Lachance-Quirion
VP of Quantum Hardware
,
Nord Quantique
Northwestern University

Northwestern looks to the heart of the universe with robust quantum sensors

With Boulder Opal, Northwestern suppressed 5 different noise sources simultaneously with a single optimized robust control pulse for atom interferometry.

5

different noise sources can be suppressed simultaneously with a single optimized robust control pulse for atom interferometry.

Read the case study

The breadth and flexibility of Boulder Opal allowed us to create our own optimization scenario and obtain pulses robust to the five most relevant experimental noise sources at the same time! This will be crucial in the development of atomic interferometers to detect dark matter and gravitational waves at currently unexplored frequencies.

Zilin Chen
Postdoc
,
Northwestern University

Boulder Opal

Bring innovative quantum solutions to market
Alice & BobAtom ComputingChalmers UniversityNord QuantiqueNorthwestern UniversityPasqal

Frequently asked questions

Boulder Opal cloud licenses can accommodate an unlimited number of users. We provide recommendations for different license tiers for different group sizes to ensure that internal competition among users does not lead to computational delays.

Number of calculations can be run concurrently across multiple cloud-hosted machines to accelerate computation. Having a higher concurrency is useful when you want to speed up your calculations or share computational resources within your team.

Number of hours of running a single cloud-hosted CPU machine in a year. You can buy additional machine time to supplement your Essentials, Performance or Professional plan.

You can access a comprehensive documentation suite to help you on your journey, starting with Get started guide, and Tutorials.

A locally installed version of Boulder Opal can be provided upon request for circumstances mandating ultra-low latency in hardware communications.  We recommend the cloud instance for general computations, as cloud services can provide performance far exceeding the specifications of the local machine.

We have independently validated and published technical validation of key demonstrations on hardware through our research - this includes device-level demonstrations of improvements >10X.We have also established a range of hardware validations with our customers and R&D partners around the world, collected in our case studies.