A classical computer – like the one you’re reading this article on – can process and manipulate numbers, text, and images. All this information boils down to bits, strings of ones and zeroes, that have to be processed in sequence.
Quantum computers are different. “They can literally have several thoughts in their head simultaneously”. That’s OsloMet professor Sølve Selstø. He says this power allows quantum computers to process information in a very different way from classical computing. A way that can give us solutions to problems that are way beyond classical computers.
But that’s only if researchers can come up with new algorithms that can use that power.
The curse of complexity
Figuring out how to take advantage of quantum computers is a multi-billion kroner question. The Quantum Hub at OsloMet where Selstø works joined this effort in 2021 with Norway’s first quantum computers – appropriately named ‘Hugin’ and ‘Munin’, thought and mind – after Odin’s ravens. OsloMet is now involved with three of the four big quantum centers in Norway along with big players like Simula and Sintef.
These computers, and the algorithms behind them, can potentially solve problems that are far too complex for even the biggest super computers.
Problems that cover everything from understanding how atoms move to optimizing global shipping logistics. These problems are so difficult to solve because they have so many variables, which means more calculations to consider.
“It’s like if you are trying to solve a maze. For every junction you add, you double the complexity because you double the potential paths you need to check out.”
If researchers can figure out how to make it work, quantum computers could end up being very good at solving these hugely complex systems.
If you're clever, you can devise ways of harnessing this power, but coming up with such ingenious algorithms is far from trivial.– Professor Sølve Selstø
Selstø is working on a type of quantum computing called ‘quantum annealing’ that takes advantage of the natural properties of quantum mechanics to solve problems.
He explains that in nature, quantum systems like atoms and molecules tend to naturally end up in what is called the ‘ground state’. Just like how a ball on a hill will come to rest at the lowest point, problems in a quantum computer will settle on the lowest energy solution.
For a problem like shipping, that solution is a route that minimizes carbon dioxide, fuel, and other costs.
This is potentially a very powerful technological solution to very complex problems.
Encoding the solution
Using quantum annealing, Selstø says “if you can somehow encode the solution to your problem into a quantum system – a solution that you don't know, a complicated, hard solution – if you can somehow encode that into the physics of your system, then you can solve it.”
Quantum computers provide the tools to solve these complex problems, but Selstø says encoding that solution is the hard part. How do we exploit this massive computational potential? How can we invent ways of processing information that are genuinely superior?
This has proven to be quite difficult. Many people are trying very hard to come up with good and new ways of doing just that.
Quantum computers aren’t just better at solving these kinds of problems than classical computers, they’re an entirely new way of processing. That means we need to find new methods of programming them.
“If you're clever,” says Selstø, “you can devise ways of harnessing this power, but coming up with such ingenious algorithms is far from trivial and I wish we had more examples of them.”
Selstø says that unfortunately, most of the big breakthrough algorithms for quantum computers – like the famous Shor’s Algorithm which can break encryption – were discovered in the 1990s.
Crossing a river for answers
Selstø’s latest attempt at creating the next quantum algorithm is based on finding the optimal way to cross a river.
Using his background in atomic physics and a self-described “excitement for genuine nerding”, Selstø proposed a question: “what is the optimal way to cross a river and end up directly across from where you started?” This may seem simple, but once you start considering different currents and the many paths across the river, it can get very complex.
These theoretical questions are how researchers like Selstø and his graduate students think about new approaches to quantum computing. He makes equations to model simple versions of the problem on a classical computer.
In this scenario, at each step across the river you have three options: up river, straight across, or down river. Again, quantum computing has an advantage because it can use ‘trits’, the three-part version of traditional computer bits.
Unfortunately, this turned out to not be one of the exponentially complex problems that quantum computing excels at. Still, by exploring this problem he learned something fundamental about quantum approaches.
Part of finding quantum solutions is figuring out how many steps the computer needs to take because this determines whether it can be done in a reasonable amount of time. In this case, a classical computer could solve it in a reasonable amount of time, so no quantum algorithm needed.
Leaping forward
While Selstø is a little disappointed that the river crossing problem didn’t lead to any genuine quantum advantage, he says finding a classical solution is still important and the whole thing was a good learning experience.
He will continue to focus on the fundamental problems of quantum computing.
He is joining a new center with doctoral students and other researchers who will investigate how quantum computers can solve chemistry problems, come up with new cancer treatments, and even address hardware questions like error correction and interference problems.
For his part, Selstø is happy to continue his dream of doing the fundamental theoretical work of trying to come up with implementations that will lead to solving real problems further down the line.
