What can we learn from applications for the development of quantum computing?

Although the development of quantum computing hardware and software is progressing fast with many papers appearing on arXiv daily, the advantage of using quantum computing for real-life (industry and academic) applications remains unclear. In principle, quantum computing is expected to lead to disruptive changes in a variety of different industries - e.g., quantum computing could help to accelerate solving combinatorial optimization problems as appearing in the logistics and in supply chains or could speed up the drug development. Present quantum computers remain to be limited in the number of qubits, the connectivity and are affected by noise – with the consequence that so far only small quantum algorithms could be tested on these devices. But we see now increasing progress in the direction of fault-tolerant quantum computers being made with multiple experiments demonstrating first logical qubits. This raises hope in having error-corrected quantum computers available in foreseeable future and thus allowing to perform longer computations on quantum computers as well. Still, given the complexity of hardware, software and algorithm development causes the need to consider all of these aspects in a co-design manner to drive quantum computing technologies forward. Specifically, looking at the capabilities of quantum algorithms and hardware from the application side provides us important information into which direction we should develop the technology further. For example, considering the application of quantum computing to medical imaging tells us that the interplay between classical and quantum computers need to be further optimized to enable a speedy execution of algorithms. Such benchmarking applications arise both on the academic as well as on the industrial side. Efforts are being made to formalize this work in a structured development of application-centric benchmarks that then explicitly also test all aspects of the interplay between quantum hardware, software and algorithms.
This talk will illustrate this topic via concrete examples.