Our users

Quantum hardware suppliers

Bring quantum hardware to market faster with control design and automation software and native error suppression

Solutions for quantum hardware manufacturers

Empowering hardware teams to solve
their biggest challenges

Quantum hardware manufacturers are building the underlying devices and need the right tools to design high-performing products, automate their operations, and scale their organizations.

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



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

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.

Solutions for quantum hardware providers

Unleash latent hardware performance

Quantum hardware providers are taking complete quantum computing systems and surfacing them as a service on the cloud for broader, more affordable access.

They need tools to maximize the performance and impact of those devices for their clients. Quantum computing end-users are seeking maximum quality of service combined with simplicity when choosing a provider.



Deliver more value to your customers with fully integrated performance management for quantum computing platforms.

Fire Opal offers fully-automated error suppression technology that integrates directly with your platform.



Building on your existing stack and interface, you can offer your customers frictionless performance management as a simple option to unlock the full potential of your platform.

Real-world use cases

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
Blue Qubit

Enabling data loading for quantum machine learning with Fire Opal

BlueQubit demonstrated groundbreaking loading of complex distribution information onto 20 qubits for a QML application by using our error suppression product.

8X

Better performance in terms of Total Variational Distance (TVD), which measures the deviation from perfect data loading.

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As we develop novel techniques to solve some of the quantum industry’s hardest challenges, Fire Opal is an essential tool to reduce the impact of hardware noise and demonstrate successful results with deeper and wider circuits.

Hayk Tepanyan
Chief Technology Officer
,
Blue Qubit
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.

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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
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.

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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
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Make quantum technology useful
Alice & BobAtom ComputingChalmers UniversityIBM QuantumImperial College LondonION QNorthwestern UniversityRigetti