In 2018, George Gesek, the CEO of NOVARION Systems, gave The Paypers readers an insightful introduction to quantum computing that is worthy of a follow-up.

Mr Gesek shared some interesting thoughts on how quantum computing will impact the financial services industry, and as the technology is evolving rapidly and we have just reached the fourth industrial revolution, we thought it was high time to take a closer look at the latest developments in quantum computing.

In 2018, NOVARION Systems began testing quantum computing for optimised workflows and predictive models for market behaviour at some of its client banks. Can you share some of your insights with our readers as you test this emerging technology?

At this early stage, software engineers are beginning to learn the programming paradigms of quantum computing. Right now, we see a big problem not only with the new technology itself, but also with the lack of trained quantum computer scientists in all industries, including the financial sector. For example, one of our biggest financial clients has around 1000 IT specialists, 800 of whom are software engineers, 60 of whom are already working in artificial intelligence. However, none of the 800 software engineers are familiar with programming a quantum computer.

One could argue that this situation is due to the fact that we still lack hardware for universal purposes, but facts tell us a different story: there are already more than 100 different quantum computer simulators with quantum programming languages that can easily be added to the most popular classical programming languages. You can find a detailed list here:

Even more so, the following illustration from the Quantum World Association shows that to understand the programming paradigms of quantum computation, a software engineer does not need to dive into quantum gates or even the underlying hardware capabilities, but can start at the top of the pyramid, with Quantum Universal Languages.

In the 1930s, Alan Turing used precise logic in a formal system to show that a conventional computer is capable of computing any algorithm – including quantum algorithms! The only difference is that the number of calculation steps (speed) varies greatly. Therefore, today we can simulate a quantum computer with around 30 qubits with affordable high-performance computer systems. This is good enough for industry to test their first quantum computing programs. Therefore, I encourage any software development department with more than 10 members to experiment with Quantum Computation with the free tools first!

For the financial industry, the most promising yet achievable areas of successful quantum computing are any applications involving Monte Carlo simulations. This is because the nature of these algorithms is based on probability functions that are in the realm of native quantum computing. Such applications are in particular risk analysis, market forecasting or portfolio optimisation.

In a second step, we can imagine applying quantum algorithms to machine learning systems, e.g. for credit scoring.

While quantum computing promises to accelerate technological progress in many areas, it also poses some challenging problems. The biggest threat arises from extreme computing power, which compromises even the most advanced encryption methods and security measures for classical data. Have technology companies begun to analyse this problem and find solutions?

Currently, some cybersecurity companies see quantum computation as a threat to their implementations of encryption methods and suggest that they understand how powerful a quantum computer must be to breach their security. However, since the threat posed is not imminent (which it is not, let’s assume within the next 3 years), most development departments are not taking action to develop new, post quantum secure methods.

Overall, even though the security industry is more or less aware of this threat expected from the new class of computing power of quantum computers, it remains in an observation mode. This is because big companies – such as IBM and Google – are telling the world that they would need millions of qubits to break through the security that has already been implemented, as the following graph from Google shows:

Nevertheless, the above picture is valid if we assume that both the qubits are loaded with many errors and the algorithm in question requires error-free qubits. As soon as there is a technology where these assumptions are no longer necessary, the risk of a global collapse of our encryption and other algorithmic cyber security systems would be immediate. Incidentally, this is indicated by the blue area in the image above as “? short-term applications” that are still unknown.

Kiran Bhagotra, CEO of Protectbox, mentioned in an article in Wired magazine that “in 2019, quantum computers could break the blockchain”. How do you comment on this?

This article shows one of the reasons why companies should invest in Post Quantum Security now. Because we really don’t know when the breakthrough with serious security implications will happen. The only thing we know about this breakthrough is its certainty of arrival!

How will the conversations/developments around quantum computing evolve in 2019? How will the technology dominate this space, both industry-wise and geographically – Europe and the US (or perhaps Asia)?

This is another question that no one in the quantum technology space can answer, because there are already so many players on the set that we need a full-fledged quantum computer to analyse them.

However, what we have seen in the last 24 months – in the field of quantum technology in general and quantum computing in particular – is a tenfold (or more) growth in the people, financial and technological resources involved. Moreover, governments and policy makers are promising great efforts to lead the key technology of the 21st century. However, no one can predict the outcome, as no one knows where or when the breakthrough will happen – it may already be happening in a lab somewhere, and we may not have heard about it yet.

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