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.

Desktop and mobile view of the Black Opal user interface
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.

quantum stacks image

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

University of Hull, UK

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.

Read the case study

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
Senior Lecturer in Molecular Physics and Astrochemistry
,
University of Hull, UK
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

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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
VP of Quantum Hardware
,
Nord Quantique
Australian Army

Improving Army logistics with quantum computing

With Fire Opal, the Australian Army tested and validated a quantum computing solution on real hardware that promises to outperform their existing methods.

12X

improvement in the likelihood of finding an optimal solution with Fire Opal over the default hardware execution

Read the case study

Optimally routing 120 convoys can take more than a month of classical computation. The Australian Army is evaluating the potential of quantum computing to provide improvements; however, it’s been difficult to validate the feasibility of a quantum solution due to hardware noise. With Fire Opal, an algorithmic enhancement software, we are able to achieve results on quantum computers that build confidence in our quantum roadmap.

Marcus Doherty
Australian Reserve Officer
,
Australian Army
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
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Make quantum technology useful
Alice & BobAtom ComputingChalmers UniversityIBM QuantumImperial College LondonION QNorthwestern UniversityRigetti