Alexander Mandl
The shortest route, out of 61 quadrillion.
I put optimisation problems — planning, logistics, finance — onto quantum computers, and try to make them pick the good answer faster.
What I do
I study and implement optimization algorithms on quantum computers. These problems are frequently found in planning systems, finance, and various fields of engineering and generally aim to pick good solutions to a problem from large sets of possible candidate solutions. As an example, think of planning a mail-delivery route. The different houses can be visited in any arbitrary order, and my aim is to use the quantum computer to find the shortest possible route - or, in other words, the route of least travel cost.
Why it matters
Simply evaluating the travel cost of all possible routes for this problem is surprisingly hard: Just for 20 stops there are 60 822 550 204 416 000 possible routes to consider (that is ~61 quadrillion). Assuming it would take you 1ms to evaluate one route, it would take you about 2 million years to look at all of them to be sure you find the best one. This is where quantum computers come in: By evaluating all possible routes "at once" and slowly but surely discarding those of high travel cost, a quantum computer could help in solving such problems just a little bit faster.
Unfortunately, coaxing the quantum computer into doing just that is not a straightforward process, but this is where my research might prove beneficial.