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Quantum computing

Build the quantum platforms of the future. Everything you need to automate and optimize quantum hardware performance at scale.

Unlock real-world quantum computing, 1,000x faster

Quantum computers have the potential to solve problems that are practically impossible on even today’s supercomputers. But before this cutting edge technology can achieve the first commercial demonstration of quantum advantage, quantum computers will need to become much more capable.

We tackle the biggest challenges that the quantum computing industry faces and improve performance by over 1,000X. We do this by unlocking enhanced performance at scale and helping customers bring solutions to market more efficiently — ensuring quantum computing delivers real value to end users.

Solutions for research

Build the future of quantum computing

Errors are the Achilles Heel of quantum computers. Dealing with them is our mission. Making quantum computing useful starts at the bottom of the stack at the hardware-software interface.

We have pioneered the development of quantum infrastructure firmware to stabilize quantum hardware and build autonomy, so benefits flow all the way to end users. And we provide advanced R&D tools to help you realize this layer.

Boulder Opal provides everything you need to improve and automate the performance of hardware for quantum computing - empowering R&D teams to accelerate roadmaps and release more capable hardware.

This means greater computational capabilities, delivered sooner.

Solutions for algorithm developers

See the light in the dark with automated performance optimization

Suppressing errors requires a deep understanding of the physical and engineering details of quantum hardware. It has been a specialist’s game, limited to a handful of research teams who could make quantum processors achieve things few others could.

Algorithm developers and researchers have been stuck with inferior performance, slowing them down. Most quantum computer programmers just want the hardware to perform better - that’s exactly what we deliver.

Fire Opal is an out-of-the-box solution for minimizing error and boosting algorithmic success on quantum computers. It delivers effective error suppression technology for quantum computers as a simple, fully automated solution suitable for any user.

Leverage Fire Opal across supported quantum processors to gain meaningful insights from today's quantum hardware that were previously impossible to achieve.

Independently validated to demonstrate up to 9,000x performance improvement over existing techniques, Fire Opal maximizes the success of quantum algorithms without any user intervention, hardware knowledge, or configuration required.

Solutions for platform vendors

Unleash latent performance in quantum hardware

Deliver greater value and improved usability to your end-users and improve the competitiveness of your platform using tools validated to improve algorithmic success up to 9,000x and to directly increase quantum volume on real hardware.

Q-CTRL Embedded delivers effective error suppression technology for quantum computers as a simple, fully automated solution integrated directly into your hardware platform.

It builds on your existing stack and interface, offering customers a performance-managed solution that gives maximum achievable performance for their algorithms - all with zero settings or configuration.

Q-CTRL Embedded offers a comprehensive workflow from algorithm input in a supported intermediate representation (QASM), and invisibly delivers optimal compilation, error-aware transpilling, and effective error suppression.

With advanced AI-driven gate optimization, circuit-level error suppression, and measurement-error mitigation, Q-CTRL Embedded automatically optimizes any quantum circuit's execution on your hardware, enabling new outcomes for your users that were previously out of reach.

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.


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.


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

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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.


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
Q-CTRL Partner

Reducing quantum compute costs 2,500X with Fire Opal

With Fire Opal a financial company was able to run algorithms on more cost-effective hardware systems while achieving results comparable to more premium systems


Reduction of quantum compute cost

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We wanted to challenge Fire Opal’s capabilities by running a quite complex, unoptimized circuit. The results were extremely promising. The only comparable results we’ve seen have come from hardware that is currently too expensive to run extensive tests on.

Dr. Valtteri Lahtinen
Chief Scientific Officer
Q-CTRL Partner

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