Quantum computers promise to do many things that conventional computers cannot. But they face a big obstacle: instability.
“If you look at classic computers, they are very stable. They will stay on for years as long as there is power,” says Vishal Chatrath, CEO and co-founder of Oxford-based startup QuantrolOx.
Quantum computers, on the other hand, require constant manual tuning, which is time consuming and difficult. As a result, they spend much more time being tuned than actually being used.
QuantrolOx wants to automate this process using machine learning. Its software monitors and adjusts dozens of different parameters every microsecond, helping to increase the useful life of computers. It runs on classical computers and is designed to scale with quantum computers.
It has just raised 10.5 million euros from the European Innovation Council (EIC) – which says the company is “of strategic importance to EU sovereignty in quantum computing” – and will use the money to support its product launch in 2023.
Of the total investment, 2.5 million euros are grants that the company will receive up front, and 8 million euros will be available for the startup in exchange for equity at a later date, and can be unlocked when it receives matching investments from other sources – EIC will match the venture capital investment up to €8 million, and this can be spread over multiple rounds. So if in the future QuantrolOx were to raise €10 million, it would only need to raise €5 million from the VCs, and that would be matched by €5 million from the EIC – the 3 million remaining euros will be accessible in the same way at a later date. .
QuantrolOx raised £1.4m in a funding round led by Nielsen Ventures and Hoxton Ventures earlier this year and has 17 employees.
The current state of quantum computing
Quantum computing is now where classical computers were in the 60s and 70s, and countries around the world are racing to establish the standards that will be used as the quantum industry grows.
Today, working quantum computers have just over 100 qubits of processing power, but in the future they will have thousands or even millions of qubits. Manual tuning simply cannot accommodate these numbers.
According to Chatrath, the EIC’s funding program is well suited to the needs of deep tech companies, which typically have a harder time raising equity capital than startups in other tech sectors. Particularly in Europe, investors tend to be reluctant to invest in deeptech startups first – the availability of matching funding can make a risky deeptech startup more attractive.
“It is more difficult to attract capital for deeptech in Europe than in the United States. Such support from the EU is a great way to reduce investment risk,” Chatrath told Sifted.
Clear Rodríguez Fernández is Sifted’s Berlin-based deeptech journalist. Follow her on LinkedIn here.