Abstraction, precision and rigour make modern science an essential contributor to technical and social progress. These qualities, however, often go hand in hand with a tendency towards hyper-specialisation. The exchange of ideas between seemingly far apart fields, but increasingly also between neighbouring disciplines, suffers in consequence.
Our research intends to counter this tendency. Through highly interdisciplinary ways of thinking and working that are not aligned on traditional scientific taxonomy, we link seemingly unconnected ideas, exploit similarities, and connect strengths.
New applications of quantum computing must be identified by determining sweet spots for their beneficial application. Boundary conditions and constraints of the system/use-case. There is no benefit from the application of quantum computing for the sake of using the technology; research must be goal-oriented and result-oriented. Use-case and application must be first-class ingredients of a research effort.
Quantum processing units will become part of complex, software intensive systems, yet it will not be possible, unlike with classical CPUs, to abstract most of their individual characteristics and assume uniform future hardware fully accessible via generic interfaces. To retain the strengths of decades of engineering progress and insights, QPU-extended systems should be based on open components are extended and modified by vertical, cross-cutting and carefully engineered changes throughout the entire software stack, using architectural co-design/ to account for peculiarities of hardware and software.
Building software-intensive, quantum augmented systems is a socio-technical challenge. Software-intensive systems are among the most complex engineering artefacts created by humans, and complexity arises from the interaction of thousands of developers, and from interrelations between tens of thousands of technical artefacts. State and evolution of these systems must be understood. Based on prior research that has established deep quantitative insights based on statistical modelling and network science, these insights must be extended to quantum software and systems engineering.