Our users

Build the quantum future faster

We enable hardware researchers to push their work to the leading edge

Solutions for cloud quantum computing providers

Integrate quantum error correction into the most advanced quantum computing platforms

Quantum control is the critical enabling technology that’s powering the future of hardware - from quantum sensing to quantum computing.

Susceptibility to noise and error limits the range of achievable algorithms running on quantum coherent hardware.

We enable quantum error correction from the device level up and deliver the AI-driven hardware automation needed to realize the true abstraction of a quantum computer.

The world’s leading engineering teams rely on our infrastructure software and professional services to build error robustness and error correction into their systems, enabling them to deliver quantum advantage to their users.

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

Maximize hardware performance

R&D teams gain an advantage using our quantum control infrastructure software

>10X
Gate fidelity
>10X
System stability
>10X
Device homogeneity
>10X
Computational speed

Solutions for quantum R&D teams

The most powerful tools for automation and acceleration at the device level

We work with research teams to build stable and reliable quantum hardware without being held back by noise and hardware errors or labor-intensive manual operations.

We offer a complete suite of solutions that automate and accelerate the operation of quantum hardware - from computing to clocks, sensing to metrology. We focus on flexibility and convenience, delivering real value with minimal user effort.

Whether designing fast quantum logic gates with optimal control, combatting platform noise in a cold-atom sensor, or using AI to automate quantum computation hardware tuneup and calibration, our tools help users move faster and achieve more.

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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