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

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 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.

See how Black Opal works

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.

See how Boulder Opal works

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.

See how Fire Opal works

Real-world use cases

>180X

Navigational stability improvement.

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

Gate-level hardware improvement.

We used Qiskit Pulse and Q-CTRL’s Boulder Opal to run error-robust quantum gates on a five-qubit IBM Quantum Canary processor. These results show just how powerful pulse-level control can be for programming a quantum computer over the cloud.

>200X

Improvement in algorithmic success.

This was a rare opportunity for some of our leading transport innovators and quantum computing experts to come together to tackle complex transport network management and congestion problems.

Andrew Constance, Minister for Transport and Roads

<1PPM

Sensitivity error-source identification during quantum logic.

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

Reduction in gate duration.

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 at Chalmers

Improvement in gate robustness to amplitude miscalibration.

Q-CTRL’s work has the potential to significantly improve algorithmic performance and hardware stability in quantum processors.

Alex Hill, Rigetti