Meet Frank Leymann, Our First Kurt Gödel Visiting Professor
Frank explains the potential and challenges of quantum computing and why he moved back to academia after many years in industry.
Quantum computers are becoming a reality. But what exactly is quantum computing?
Quantum Computing is an entirely new kind of computing. If you take a look at computers, the sizes of the elements of a computer are getting smaller and smaller and reach the size of an atom. This is the smallest element that you can use to build a classical computer. To increase computer power, you must get smaller. That means you go into an area where then quantum effects take control. This is what you call quantum computing—you build computers that use quantum effects.
Where do you see the potential and the challenges of this new technology?
First of all, today’s challenges are computers that are called NISQ computers: noisy intermediate-scale quantum computers. They are noisy because the essential elements of a quantum computer—called a qubit, a quantum bit—are unstable and live only for a very short point in time. To get these qubits more stable is the technological challenge we face. The same is true for the fundamental operations of a quantum computer which are called gates. The gates also are erroneous: they are disturbed from the outside. Getting these gates more stable and error-free is the second fundamental technological issue we encounter. There are vendors like IBM, Intel, and Google who are building quantum computers. The hope for me as a software person is that they are under the control of the technology, and over the next couple of years, they will stabilize it. If you take a look at roadmaps that IBM and Google rolled out, they say that they will have error-corrected quantum computers in about a decade. For me, as a software person, this would be heaven.
Another challenge is that you program quantum computers very differently from how you program classical computers. With classical computers, you have a programming language, but if you program a quantum computer, you have to do linear algebra, meaning pure mathematics.
The advantages of the quantum effects are the significant speed-up of many of today’s algorithms. There are exponentially faster algorithms than classical algorithms, and you have higher precision in many areas you cannot achieve by a classical algorithm. Another attractive advantage is that a quantum computer requires very little energy because its operations are reversible. You only need a minimum of energy to perform a computation once the quantum computers are advanced—today, they still need a lot of power for cooling down. There exist other approaches for running quantum computers with room temperature. If we arrive at this stage and require only very little energy for operating a computing system, this will be extremely interesting for our environment. A social aspect and a threat I see in quantum computing is that you have algorithms able to crack keys for accessing your bank account or buy at your favourite online shop. The security of these transactions is based on keys, but quantum algorithms can easily crack the keys. As soon as quantum computers are powerful, some people think in five years, some in ten years, there is no longer any secret: You can decrypt documents extremely fast. This is a significant threat, and companies must understand how to protect themselves against these security issues. The world will look very different if quantum computers are powerful enough to execute these algorithms long enough.
From your point of view, are there currently obstacles or difficulties in dealing with quantum computers? How they have to be stored etc.
You need gigantic refrigerators, and the temperature at which so-called superconducting computers are running is much colder than the universe, extremely cold; we are talking about millikelvin. This requires a lot of power for cooling the computers down. There are other technologies like trapped irons that can work at higher temperatures. Physicists are experimenting and use diamonds to realise these qubits, but this is the future yet. Todays’ machines have these technological problems, and the research prototypes are far from being industrialised. It will take many, many years until quantum computers will work at room temperature.
Where is the difference in programming quantum computers from classical computers? Where do you see the implications for the curriculum?
It is pretty evident that the students must learn a lot more mathematics. They need to study the basics of physics, too, to understand why specific steps in writing a program make sense. You don’t need to be a physicist to program quantum computers, but you need to know a lot of mathematics, and the curriculum must be changed accordingly. We require new lectures for quantum informatics, like quantum programming and quantum algorithms. I’m giving lectures and seminars in quantum machine learning because artificial intelligence has many advantages if you solve them on a quantum computer. Whenever you dive into particular technologies of today’s computer science, they are impacted by quantum computing. This is what we need to find out: where are the impacts severe enough to change the lectures and the curriculum in different areas like AI, optimization and so forth.
Are we going to use quantum computers in everyday life, and will they replace the classic computer?
No. They won’t replace classical computers, but they will be specialized devices used in particular domains like machine learning, optimization, medicine, in material science. Today, quantum computers are used for inventing new materials, like new batteries for building electronically powered cars. You need batteries that last long enough to travel for more than 200 km. Quantum computers are used for simulating these new materials. Quantum computers will always be only a part of the computation; you always need classical computers and quantum computers, so we talk about hybrid quantum-classical computing. It will live on a classical computer, then you dive into a quantum computer to do some particular computations, and then you interpret the results again via a classical computer. This is the thinking we need to teach students: they need to understand classical computers and quantum computers. So we don’t make classical computers obsolete, and we don’t need to throw all our curriculum away, but we need to have special new lectures to teach this new thinking. The world will be more complex for the students.
Can you give some application examples of quantum computers, like how can they be used, for example, in digital humanities, finances, in the medical field?
I mentioned material science as one concrete application. If you want to invent new molecules for pharmaceuticals or new materials for batteries, this is a typical application. I am running a project called PlanQK, where a bunch of industry partners are coming from finance or logistics. We have applications in optimization, portfolio analysis, risk analysis, fraud detection—this is what we are using quantum computers for. They are also used in the area of machine learning for clustering. We are also running a digital humanities project to analyse costumes: the effects of costumes on a person watching a movie. Navigation would be another example. If you want to avoid thunderstorms while flying in a plane, extreme fast rerouting is required, so we can use it for this purpose—there are different applications we are running in this PlanQK project.
You were appointed IBM Distinguished Engineer and spent many years in the industry, hold many patents. What is your advice to people who want to found a start-up?
Be smart! To get accurate advice, you need to think for hours… Founding a start-up is a tricky thing. If you want to go to the industry, you need to have a broad background, and if you’re going to found a company, you must have a business idea, and you have to be interested in other aspects than computer science. Take a look at the real world, define the problems, and then apply the computer science you learned at university to a very concrete problem. Try to find people who are not computer scientists but specialized in a particular domain like medicine or finance to join you. Then build the prototype and go with it to a venture capitalist to convince them to get money.
And what is your advice to students who want to stay in academia?
If you want to stay in academia, my advice is: First, get a solid theoretical background and then find interesting new areas. Second, don’t invest in fashionable topics, but look at the long-standing problems in computer science. Third, focus on these problems and solve them to get your PhD and your habilitation.
What made you move back to academia after all these years in the industry?
I always make a joke—it was the midlife crisis! I was 20 years with IBM and would never like to miss this experience. I had outstanding colleagues there, but at some point in time, I found out that you always do the very same. You get a problem, you solve it, you need to build a product that makes money, so there was nothing new. Then I met a couple of people at TU Wien like Schahram Dustdar, and they convinced me that university is very nice. Then I got an offer that I couldn’t refuse at the University of Stuttgart. I founded a new institute, and I love to work with young people. To sum it up, after 20 years it was time for a change. I always recommend good students: don’t be eager and leave university after your Bachelor or Master degree, because then you need to work in the industry for forty years. It gets boring, at least after twenty years. I often convince students, and they say, okay, this is a good idea, I never thought about it before, and I would like to get a PhD with you. Stay at the university as long as you can. This is fun, this is where you can have an impact, and then you can go to industry, which will get boring.
What are your plans for the future, and what are your plans for the Kurt Gödel Visiting Professorship here in Vienna?
I already work together with people from TU Wien, like Schahram Dustdar, Eva Kühn, and Gerti Kappel and we want to extend this. It is a good idea to have more time. What I look forward to is spending a couple of weeks per year at TU Wien Informatics, work with the people. It would also be a good idea to meet physicists, meet people from domains where we see application potentials and try to develop joint ideas for research projects or papers. I will also give the KGVP lecture on quantum informatics, which an exercise will accompany.
- The Power of Quantum Computing by Frank Leymann
- The Bitter Truth About Quantum Algorithms in the NISQ Era by Frank Leymann
- From Digital Humanities to Quantum Humanities by Johanna Barzen
- “Verschränkung durchbricht Schranken” by Frank Leymann