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.
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 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 tools so you can focus on building the future, not fixing the hardware.Contact us
Navigational stability improvement with hybrid quantum navigation system.
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
Gate-level hardware improvement with Q-CTRL robust gates.
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.
Improvement in algorithmic success with Q-CTRL solutions.
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
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
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