Q-CTRL raises US$290 million to make quantum computing useful
IBM engineers in Germany working on the IBM Quantum System One in Ehningen, Germany (photo: IBM Research)
Australian quantum technology company Q-CTRL has raised US$290 million in a Series C led by Salesforce Ventures. Its software is designed to help researchers get reliable results from today’s quantum computers, an ambition it put to the test by simulating how electrons interact on an IBM processor.
The Sydney-based company grew out of quantum physicist Michael J. Biercuk’s research at the University of Sydney and was founded in 2017. It announced the round on 12 November at a valuation above US$1 billion, with significant participation from Bullhound Capital and Affinity Partners. Australia’s National Reconstruction Fund Corporation invested A$70 million to support research and development and help Q-CTRL expand its local workforce.
How Fire Opal makes quantum processors easier to use
The software at the centre of Q-CTRL’s computing business is Fire Opal. Quantum processors run calculations by applying a sequence of operations to qubits, their basic units of information. Small errors can accumulate as that sequence gets longer, until they obscure the result. Fire Opal adapts the operations to the processor running them to reduce the effect of those errors.
IBM offers Q-CTRL’s Dynamics Simulator in beta to customers on eligible Quantum Platform plans. A materials researcher can specify a supported physical model, its starting conditions and what they want to measure. The software builds the instructions for the processor and returns estimates of how the chosen properties change over time, saving the researcher from having to design the quantum circuit.
What the IBM benchmark showed
To see how far the approach could go, Q-CTRL used up to 120 qubits to simulate a one-dimensional version of the Fermi–Hubbard model, which physicists use to study how electrons move and interact in materials. In May, the company reported that the quantum processor took minutes where its chosen classical method took more than 100 hours. In the revised preprint, the researchers describe a speed-up of nearly three orders of magnitude near the limit of the range in which the two methods agreed.
That comparison changed when Roman Rausch and colleagues accelerated the classical calculation using graphics processors and symmetries in the model. In a June preprint, they reported a runtime of about 100 minutes at a level of approximation comparable to Q-CTRL’s classical benchmark, narrowing the estimated speed-up to roughly 36-fold on that comparison. With a more demanding calculation, they also obtained results for a longer stretch of simulated time than Q-CTRL’s experiment covered. This is important for materials research, where a faster answer is valuable if it meets the accuracy the experiment requires.
Navigation brings in revenue while computing develops
Q-CTRL applies its expertise in sensitive hardware to a second market. Its Ironstone Opal system uses quantum sensors to help aircraft estimate their position when signals from the Global Positioning System (GPS) are disrupted. The company says it is deploying the system with Airbus and reported in July that the equipment met the RTCA DO-160 standard for environmental testing, which covers conditions such as vibration and electromagnetic interference. Q-CTRL’s funding announcement gives no figures for the scale of deployment.
Salesforce Ventures says navigation already generates revenue through defence and aerospace contracts. Q-CTRL names Lockheed Martin as a partner for autonomous platforms, and Lockheed Martin Ventures returned as an investor in the Series C.
The company also sells Black Opal, an interactive training platform for employers, educators and individual learners. Its courses take learners from basic quantum concepts to building and running circuits.
The latest funding gives Q-CTRL room to find out where Fire Opal fits into the work of a materials lab. For a research team, the choice of computer is part of a larger decision about how to spend its time and budget. A simulation earns its place when it produces a result the team trusts enough to act on. For Q-CTRL, making quantum computing useful could come down to a decision made in an ordinary lab meeting about which experiment to run next.
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