Oxford-based QuantrolOx has raised £1.4m in a seed funding round to develop its artificial intelligence (AI) software that tunes and stabilises quantum computers.
The Oxford University spinout is aiming to improve the slow load up time of quantum computers using machine learning.
While quantum computers are much quicker at solving certain problems than a traditional computer, they take much longer to set up, resulting in shorter use times.
Quantum computers use qubits, or quantum bits, instead of binary bits to store units of information. When booting a quantum computer, these qubits currently require human expertise to set up before the machine can be used. As quantum computers use more and more qubits, this problem will become increasingly important as the computers will require more time and people to set them up.
Founded in 2021 by Andrew Briggs, Vishal Chatrath, Professor Natalia Ares and Dominic Lennon, QuantrolOx is creating hardware-agnostic software that can automate the tuning of qubits.
Its seed funding, announced last week, was led by Nielsen Ventures and Hoxton Ventures. Voima Ventures and Remus Capital provided further capital, along with angel investors Dr Hermann Hauser, and Laurent Caraffa.
Charles Seely, partner, Hoxton Ventures said: “Successful tuning, optimising and stabilising of many thousands of qubits, regardless of their variability, requires intelligent automation. Current solutions that depend on human expertise are not good enough and will not scale.”
QuantrolOx wants its software to run on any quantum computer but is currently focusing on solid-state qubits.
“I am excited to be backing a world-class team and a technology that has the potential of establishing itself as a category leader in the new and rapidly growing quantum ecosystem,” said Niels Nielsen of Nielsen Ventures.
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