The State of Quantum Computing Today

Interview with Professor Cristian Calude by Alex Chapple

IBM quantum computer - Photo credit IBM

Quantum computers are a new class of computers that have been receiving a lot of media attention in the last decade. These computers' underlying structures are entirely different from the modern computers we're all familiar with, which

are known as "classical computers". The underlying architecture of classical computers is based on "classical physics, " which is the macroscopic physics we experience in our daily lives.

In contrast, quantum computers, like the name suggests, manipulate quantum behaviours to do computations. In classical computers, the information is stored as bits, which take on values of either 1 or 0. Quantum computers are built on qubits (quantum bits). Instead of taking on 1 or 0 as their value, they take on both simultaneously (Yes, freaky I know). So if you have ten quantum bits, 2 states are being represented at the same given time.

Because of this, quantum computers promise to be exponentially quicker at certain computing tasks and may revolutionise fields like computational biology, cryptography, quantum chemistry, quantum simulations, and more.

These computers have certainly been gaining traction from the media, most notably when two years ago Google claimed to be the first to achieve "quantum supremacy". Quantum supremacy, also known as quantum advantage, is a term coined by California Institute of Technology Professor John Preskill. It is the notion that a quantum computer can compute things that a modern classical computer cannot in a meaningful amount of time. Perhaps what drives the most media attention is the multi-billion dollar investments companies such as Google, IBM, and Microsoft and large governments like the United States, China, and the UK are putting into research and engineering. In December 2018, the United States Congress passed the National Quantum Initiative Act, which aimed to advance quantum technologies in the next ten years by further supporting research and engineering. It seems as though governments and large tech companies around the world are betting heavily on a future filled with quantum technologies, but is the hype and media attention around quantum computing justified?

The following is a conversation I had with Professor Cristian Calude from the School of Computer Science. Professor Calude is the director of the Centre for Discrete Mathematics and Theoretical Computer Science, and a research consultant for the Quantum Computing Research Initiatives at Lockheed Martin, USA. We talked about the state of quantum computing today, where it may be heading, and why the media attention that quantum computing is getting may not be for the right reasons.

How does your research tie in with quantum computing?

I'm a mathematician and a theoretical computer scientist with interests in quantum physics and computing. All my papers in quantum areas have been done jointly with physicists (Professor Karl Svozil from Vienna is my longest collaborator) to ensure that the physics is correct. Initially we used finite automata with outputs to model quantum phenomena. For example, we've described Bell's inequalities with finite automata.

(Finite automata are simple idealised machines used to recognise patterns)

In the last ten years, I was involved in two quantum projects. One was to study quantum annealing, because we've got support to use the D-Wave machines. It makes a huge difference when you work in quantum computing if you have access or not to a real quantum computer.

(D-Wave is a Canadian quantum computing company based in Burnaby, British Columbia, Canada. They use a particular technique called quantum annealing to solve problems. The technique finds the global minimum of a particular function by manipulating a quantum system).

So you look at the machine and say, what can you do with it? Is there something useful one can do with it? How far can one push the limits of the machine?

The other project is connected with my work for many years in algorithmic information theory, a very beautiful and powerful mathematical theory of randomness. So at some stage, I said `quantum randomness is believed to be the best form of real life randomness, so is algorithmic information theory relevant to understand it?’ I have been also interested in quantum randomness because physicists believe that quantum randomness is perfect randomness while mathematically there is no perfect randomness, so one should only look at degrees of randomness.

We also proposed protocols for quantum random generators and proved theoretically that they are better than any pseudo-random generators. We were fortunate that a lab at University of Queensland led by Professor Arakady Fedorov did the experiments. We published the protocols, and the physicists published the experiments.

We were very interested in the experimental results because one is a theoretical protocol written on paper, and the other is an experiment that cannot be done under ideal conditions. We developed tests for assessing the quality of the quantum random bits generated in the lab and analysed to what extent theoretical results are reflected in the experimental results.

Why does and doesn't quantum computing deserve the media attention it gets?

Well, I am not a media expert, but I have some guesses. There are many promises about quantum computing, which, assuming that the dreams come true (which I don't believe they will) will change many technologies that are used today. Encryption and security are examples. So, if you are a government or a big IT company with lots of money, you cannot afford to leave the competition to develop a technology which can be used against you, even if there are very few solid arguments that it will. Google cannot accept that Microsoft can do it, and Americans cannot accept that the Chinese can do it, and vice versa. So in a word, it's driven by fear. It has escalated into a huge race, and none of the big actors are bold enough to stop. But this race cannot continue forever if critical results are not delivered.

For the time being, the media is a very strong supporter of the field because writing about this race will bring readers and, like most businesses, the media is channelled on making a profit.

Yes, I agree with that. When I read stuff about quantum computing, especially if it's from less reputable news websites, it's so clear that they're sending false hope because quantum computing is not very close to being what they think it is.

They don't know what it is in the first instance.

Can quantum computers really solve the problems that the media is saying it will solve?

I should probably say, first of all, that even in an ideal scenario, quantum computers can compute much less than classical computers. This is because quantum computers can compute only total functions. If you have a function that divides two integers, X divided by Y, you have to exclude the possibility to divide by zero. So you can't return an answer for X divided by zero. That is undefined and illegal. This kind of test, which is trivial for classical computers, cannot be performed by any quantum computer.

Let me give you a picture. Let's imagine the Pacific Ocean is a set of all mathematical problems. How many of them can be solved by classical computers? A small drop. Most of them cannot be solved with any classical computer. From this drop, only a smaller part can be solved by quantum computing.

So what's the point of quantum computing? The only justification is in this small area where quantum computers can solve problems of practical interest. If these problems could be solved with quantum computing tremendously faster than with classical computers, then the effort would be justified.

In the early 80s the American physicist Richard Feynman and the Russian mathematician Yurin Manin came with the idea of quantum computing. Both of them were talking about simulations and Feynman said `look, I have this kind of quantum system I want to simulate and I know that I can simulate it with a classical computer, but it will take an exponential time. Can I do it faster?’ And Manin said that it's possible if the machine is quantum itself.

But Manin noticed something even deeper. He said that to simulate a quantum system, a classical machine needs to understand a lot of quantum theory and incorporate it into the program, and this takes time to develop and run. But a quantum computer will not need this because it is already based on the same quantum principles, so that it will be faster. It's a shortcut.

Quantum computing is intrinsically interdisciplinary. You have people from engineering with their cultures, businesses with their cultures, mathematicians with their own, programmers with their own, etc. It's a very young field, and it doesn't have its own sound culture.

A 128 qubit D-Wave processor. This is one of their earlier models, currently they have systems with up to 5000 qubits. - Photo credit to D-Wave

Yes, it's an interesting field like you said because it's so young. There are many engineering problems, physics problems, and mathematical problems.

Yeah, lots of problems, I'm not saying that this field is not interesting or exciting. And there will be benefits, possibly not those discussed so much in the media. For example the idea of "de-quantisation", where you take a fast quantum algorithm, find a way to rewrite it for classical computers and obtain a much faster classical algorithm than the current algorithms.

The hype for quantum computing is damaging because if you claim things you cannot prove or deliver, at some stage people will say, oh, that's not serious. This will be detrimental for the field.

To change the topic: there are many ways, many different architectures for building quantum computers. Google uses superconducting qubits, others like ion Q use ion traps, and there are many other ways. I know Microsoft recently thought of giving up on their topological qubit because its engineering was too complicated.

That one is from a mathematical point of view the most interesting… If the engineers feel that this is beyond the capability of the current technology, maybe it's best to shelve it, maybe for 20 years, and then look at it again.

Which type do you believe is most promising or will be the most fruitful.

Well, I don't know, you cannot predict even the past, and you're asking me to predict the future. I think that quantum annealing, which is the form D-Wave machines use, will survive many years and be fruitful just because they take a more pragmatic attitude.

So their architecture is to use thousands of weaker (less connected) qubits, as opposed to using 50 well connected (strong) qubits like Google's qubits.

So you say they have weaker qubits: true, but this is an advantage. They use qubits that are weaker (meaning fewer problems, in particular with error correction), but strong enough to solve problems.

I was amazed by the engineering decisions made by D-Wave even before we started working with them. One was to solve one single problem. It's a discrete optimisation problem, but this problem is generic, so many practical problems can be reformulated as instances of this problem and solved by D-Wave. This makes a controversial decision a smart choice.

My next question is: what are you most sceptical about the field of quantum computing in general?

Well, I am sadly sceptical about the hype. I fear that it will attract people for the wrong reasons, mostly because of fashion and money. I have seen this trend in the late 90s when there was a strong interest in a field called structural complexity. It attracted lots of young people, producing papers and PhDs. Many results are correct, but without meaning. And then after 15 years, nobody reads those papers, they had to switch fields.

My last question is sort of on the more optimistic side. Suppose we're in the future, and there is a perfect quantum machine that you can use. What kind of computation would you like to do on it?

Well, I would like to test the Riemann hypothesis.

I read somewhere that with 2000 perfect qubits you can prove the Riemann hypothesis.

Oh, if you find that article, please send it to me: I'm interested.