Our users

Gain your own quantum advantage

Tools to help you build your career in the quantum industry

Solutions for students and professionals

Learn quantum computing

Black Opal is an 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.

Solutions for research students and PhD candidates

Advanced tools for advanced research

Accelerate quantum research efforts using the world’s most advanced quantum control 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.

Algorithm researchers

Application specialists and algorithm designers use our automated error suppression tools to gain better insights from their research efforts, faster. Now you can get the most out of cloud quantum computers without any specialized knowledge of error suppression technology, and zero configuration required.

Fire Opal is an out-of-the-box solution for minimizing error and boosting algorithmic success on quantum computers. It packages a comprehensive suite of best-in-class AI-driven quantum control techniques into a simple tool, letting you suppress errors in hardware and circuit execution with a single command.

Real-world use cases

>180X
This groundbreaking application of autonomous quantum sensors in space exploration will be invaluable in leveraging extraterrestrial resources to establish permanent human bases on the Moon, Mars and beyond.
Steven Marshall, Premier of South Australia
>10X
We used Qiskit Pulse and Q-CTRL’s Boulder Opal to run error-robust quantum gates on a five-qubit IBM Quantum Canary processor delivering better value for users
>200X
We could see all trains, busses, ferries, trams and motorways essentially ‘talking to each other’ to find out where customers are and deploy resources where needed.
Andrew Constance, Minister for Transport and Roads
<1PPM
The team at Q-CTRL was able to rapidly develop a professionally engineered machine learning solution that allowed us to make sense from our data and gain real insights into how to improve our hardware.
Dr. Cornelius Hempel
>8X
It was really easy to go from code to experiments 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 at Chalmers
7X
Q-CTRL’s work has the potential to significantly improve algorithmic performance and hardware stability in quantum processors.
Alex Hill, Rigetti
5
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!
Zilin Chen, Postdoc at Northwestern University
>2,500X
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 & Co-Founder at Quanscient
12X
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, Army Research Officer, SO1 Quantum Technologies, Australian Army
14%
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 Quantum Hardware

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