Our users

Power development teams with quantum control tools

The quantum computing revolution is here – we have built the tools to make it practical

Solutions for quantum development and software engineering teams

Improve algorithmic speed and performance

Realizing useful computations on quantum computers requires overcoming the true bottleneck in the field: instability and error. Hardware error remains the roadblock on the path to achieving true quantum advantage - including users of cloud quantum computers.

Quantum computers are not like conventional machines. Conventional computers can run for almost a billion years without suffering a hardware fault, but qubits in quantum computers can fail in less than a second.

Our users leverage our quantum control infrastructure software to build and deploy real-world quantum applications by simple, seamless, and automated integration of error suppression in their quantum workflows.

Up to 9,000X
algorithmic enhancement on cloud quantum computers

Solutions for algorithm researchers

Streamline quantum workflows

Teams with full exposure to the inner workings of quantum computing hardware have had an unfair advantage. We are changing that for our users.

Quantum algorithm researchers seamlessly pass algorithms through our tools and then execute them on cloud hardware. They achieve better algorithmic success and faster execution, all without needing to worry about the hardware.

We enable you to develop and execute error-robust quantum applications for quantum computers now and in the future, enabling scalable development. AI engines autonomously optimize quantum algorithms at the gate and circuit level to deliver the maximum performance achievable in hardware.

Make quantum computing practical with simple Python developer tools so you can focus on building the future, not fixing the hardware.

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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Make quantum technology useful