Our users
Quantum learners, students, and researchers
Upskill and accelerate with expert tools to gain your own quantum advantage.
Solutions for students and professionals venturing into quantum
Access the leading quantum computing learning platform
Newcomers to quantum technology can go from zero background to programming real quantum computers with Black Opal - no PhD required!
Featuring interactive and accessible learning modules, students can gain practical skills in quantum computing in just minutes a day.
Black Opal is a multi-award-winning educational tool that provides all the required math taught alongside quantum fundamentals with the learner in mind.
It replaces lectures and passive videos with engaging content developed by the world’s largest team of quantum control engineers.
AI-based performance-management for application specialists and developers
Test and validate high-value quantum applications with ease
The best way to learn is by practicing on real quantum computers—but hardware errors have held specialists back.
Application specialists and algorithm designers use our AI-powered error-suppression tools to gain better insights from their application-research efforts, faster.
Fire Opal is an out-of-the-box solution for minimizing error and boosting algorithmic success on quantum computers. It’s natively integrated into the world’s leading platforms so you can connect directly into your development workflows.
Powered by AI-driven quantum control, it simplifies and automates error suppression in hardware and circuit execution—no hardware-level expertise required. With a single command, you can achieve more accurate, more reliable results so you can focus on advancing the applications that matter most to you.
Powerful tools for quantum researchers
“AI for quantum” to accelerate your research
We help researchers at all stages push the boundaries of quantum science with the world’s most powerful AI-powered quantum infrastructure software.
Hardware research students
Research students building quantum computers and quantum sensors deploy our powerful AI-based agents to calibrate quantum hardware and quantum gates automatically, design optimized control solutions that perform better in the face of imperfect hardware, and even pinpoint critical hardware issues.
Theoretical researchers
Researchers in quantum information, quantum sensing, and quantum control use our experimentally validated tools to explore and apply the most advanced concepts in quantum control in their work.
With a simple Python interface, our users can integrate industry-leading optimization engines and fully automated noise and error suppression tools right into their programming workflows, whether in numerics or cloud quantum computing hardware.
Real-world use cases
Improving quantum education outcomes with Black Opal at the University of Hull, UK
Enhancing student engagement and real-world understanding in quantum computing through intuitive and interactive learning with Black Opal.
85%
of students reported that Black Opal improved their overall learning outcomes when used alongside their university syllabus, and would recommend its use in future courses.
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Students who engaged with Black Opal as an active companion resource significantly boosted knowledge retention and ultimately understanding. Some of them even engaged further with quantum computing by choosing a final-year project in that field.
Dr David Benoit
Dr David Benoit
,
University of Hull, UK
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
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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
Dany Lachance-Quirion
,
Nord Quantique
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
Hayk Tepanyan
,
Blue Qubit
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
Marina Kudra
,
Chalmers University of Technology
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