Singapore state fund backs Irish physicist's super-computing startup

Dr Joe Fitzsimons, a theoretical physicist who studied at UCD and Oxford University, has recruited nine other specialists in the field to work with him in the Asian island state, which is often lauded as one of the world's most successful economies.

His firm, Horizon Quantum Computing, has raised seed funding from SG Innovate and five other venture capital firms.

A typical seed funding round for a software startup might be up to €2.5m. Fitzsimons declined to reveal how much the firm has raised, only confirming that it was less than €6m.

Quantum computing involves the storing and processing of vast amounts of information faster, and using less energy than conventional computing.

It could process information a million or more times faster than with existing methods.

Horizon aims to make it easier for software developers to harness the full power of quantum computing without requiring them to have a PhD.

"We're building these programming tools because you can't run conventional computer code on a quantum computer and expect it to perform faster. You need to harness quantum interference to see any advantage. This needs new instructions, and is quite counter-intuitive," Fitzsimons said.

"We're trying to abstract the computational model so that software developers won't need a background in quantum computing in order to work with it."

He said the firm would raise a series A round in the near future, declining to put a timeframe on it, adding that Dublin would be among the locations under consideration when Horizon seeks to open its second office, for which it would need to hire graduate and PhD level software developers.

Singapore is among the top seven centres globally for quantum computing, he said, adding: "I've enjoyed a lot of support here, having been a national research foundation fellow.

"There are hundreds of people working in the sector here, and my Horizon recruits all live within commuting distance of my office."

Quantum computing will lead to more accurate results from modelling with larger datasets, in a shorter time, he said.

Within the next decade, it has applications in machine learning and artificial intelligence, in computer simulations - for example for a self-driving car learning the behaviour of other road users.

It also has uses in computational food dynamics and mapping the construction of molecules. In geophysics, it could be used to map where gas, oil and minerals are likely to be located.