Quantum computing is already making waves, but it is far from being ready for series production: the technology is still in the early stages of development and is already arousing high expectations. Are these legitimate? In which practical fields of application is quantum computing already being used, and why is it worth dealing with the topic now?
Industrial applications for quantum technology
Although the technology is already making waves, it is still a long way from being ready for series production: Quantum computing is still in the early stages of development but is already arousing high expectations. Are these legitimate? In which practical fields of application is quantum computing already being used, and why is it worth dealing with the topic now?
The problem: How quantum computing works takes work to understand. Regular reporting on this gives at least an approximate picture of the advantages of quantum computers: a quadratic to an exponential increase in computing speed compared to traditional computers, not for all problems, but specific issues. The question arises about how practically relevant the technology is for industrial companies today or shortly.
Quantum Inspired Algorithms
Advances in quantum computing are not just about hardware or simply increasing the number of qubits. On the contrary: It also depends on the algorithms supporting how quantum computers calculate. Unique algorithms suitable for quantum computers are required to use the quantum advantage.
Today, while quantum technology is not yet advanced enough to offer an advantage in real-world problems, it is worth taking a fresh look at already known – and supposedly solved – issues—a rare opportunity to start from scratch and be inspired by how quanta work.
An example should illustrate how quickly processes can come to a standstill and why this sometimes cannot be solved at short notice: An airport is a complex ecosystem in which countless factors influence each other. Powerful computing technology calculates the optimal process, which can take several hours every day (or at night). Even a tiny change, a delay or cancellation of an airplane, ensures the schedule is no longer optimal. To be able to react quickly enough, an enormous amount of computing capacity would be required. In practice, this means that little needs to be optimally rescheduled: the delayed aircraft now has to be parked outside, long distances for the passengers and luggage and further delays are the results. That takes time, money, resources and – if you transfer the example to manufacturing companies – possibly the customer. Optimization tasks of this type with many parameters often cannot be solved conventionally in the short computing time required by reality.
With the help of quantum computing, experts want to develop new solutions. Most processes of this type can be abstracted mathematically. Quantum algorithms are based on different mathematical concepts than traditional computing technology. For example, the famous Shor algorithm, which the MIT mathematician Peter Shor described in 1994 and thus gave quantum computing the necessary boost, breaks down large numbers into their prime number factors. He doesn’t just test all the options that would take too long. To put it simply, the algorithm looks for the period of a function that allows conclusions to be drawn about the result.
As soon as quantum technology is sufficiently developed, the calculation can be carried out in a fraction of the time previously required, thanks to quantum superpositions. So far, the most significant number factored with the Shor algorithm is 21 – this is not yet an absolute quantum advantage. Nevertheless, many technical reports already point out that this threatens the security of most encryption methods currently in use since they use prime number factors for encryption.
For optimization questions, such as those in the example of the airport, researchers work with the Quantum Approximate Optimization Algorithm (QAOA). As a hybrid algorithm, it combines classical and quantum mathematical concepts and, to put it simply, tries to find the best solution to a problem from a multitude of possible solutions. Specific criteria are specified to approach the optimum. The first, more minor, real optimization problems could be solved with QAOA so that tangible benefits can be expected shortly.
Research Is Committed To Quantum Computing
Even if the hardware for quantum computing has only had limited performance, those interested can already experiment with quantum algorithms today. The Quantum Learning Machine (QLM) from the digitization service provider Atos, for example, is a development environment made of classic hardware and software that simulates qubits and their way of calculating in a hardware-agnostic manner.
Basic algorithms and models are already stored on the platform, so that quantum mechanical calculations can be described and tested using classical mathematics. Working intensively with quantum algorithms makes it possible to develop better classical algorithms, which can already be a worthwhile result.
For example, such a QLM is used at the European nuclear research organisation, CERN (Conseil Européen pour la Recherche Nucléaire). The research institute has set up numerous projects as part of its Quantum Technology Initiative ( CERN QTI ) to advance research into the quantum advantage of high-energy physics. In a roadmapCERN has defined the research areas and milestones for the next few years: In addition to establishing cooperation between research institutes and companies worldwide as well as primary research, the evaluation of concrete business cases and performance benchmarks are also part of the self-imposed tasks. In March 2021, the Leibniz-Rechenzentrum (LRZ) of the Bavarian Academy of Sciences opened its Quantum Integration Center (QIC). Scientists working on quantum computing can use the infrastructure for their research.
The Federal Ministry of Education and Research (BMBF) also supports the research and development of quantum technology with funding, announces innovation competitions and is involved with the Quantum Futur Academy to train experts. With its supporting program, the federal government wants to bring together and promote the potential of politics, business and science. The goal is to harness the benefits of quantum technology for industrial applications. Almost 3 billion euros are available for this from various pots. In addition, the Federal Ministry of Economics and Climate Protection (BMWK) has a total of 740 million euros available for the quantum computing initiative of the DLR (German Aerospace Center). DLR uses this to finance its research and awards research and development contracts to companies in Germany and abroad. Funding programs have also been set up at the EU level.
Practical Areas Of Application
The fact that the research institutes have taken up the cause of quantum computing and that total funding is available are essential steps to using this technology. But companies are also getting involved and using the research results as inspiration. For example, Atos created the Quantum Advisory Board – a council of renowned experts who meet regularly and exchange information on current developments.
The Finnish-German company IQM Quantum Computers receives prominent support for its board of directors from the chairman of the board and the chief operating officer of the pharmaceutical research company BioNTech. Well-known companies such as BASF, BMW, Bosch and Siemens join forcesQuantum Technology and Application Consortium (QUTAC) to bring industry-relevant, quantum-based applications to market. The Quantum Industry Consortium (QuIC) sees itself as a representative of European providers and users of quantum technology. The non-profit association brings together large companies, SMEs, investors and start-ups and aims to increase the competitiveness and economic growth of the European quantum technology industry.
The life sciences, chemical industry, logistics and production sectors, and the financial sector, in particular, are hoping for measurable successes with quantum computing shortly. For example, technology should accelerate the development of drugs and even make individualization possible. By simulating molecular structures and their interactions, new drugs could be developed faster with the help of intelligent algorithms. The airport example above shows how quickly traditional algorithms reach their limits, even if only one variable changes. For example, work is being done on optimizing investment portfolios in the financial sector. Here, too, the influencing factors and interactions are unmanageable.
Conclusion: Start Getting Excited About Quantum Computing Today
It will undoubtedly be some time before there is software that solves quantum-based problems “off the shelf”. But because technology is elusive and requires a new way of thinking and approaching problems, it is worth dealing with it now.
Funding, educational initiatives, simulation applications, and comprehensive communication from research institutions can be starting points and motivation. The practice of this still entirely theoretical topic thrives above all on the lively participation of leading technology providers and organizations.