TY - CHAP A1 - Mauerer, Wolfgang ED - Exman, Iaakov ED - Perez-Castillo, Ricardo ED - Piattini, Mario ED - Felderer, Michael T1 - Superoperators for Quantum Software Engineering T2 - Quantum Software: Aspects of Theory and System Design N2 - As implementations of quantum computers grow in size and maturity, the question of how to program this new class of machines is attracting increasing attention in the software engineering domain. Yet, many questions from how to design expressible quantum languages augmented with formal semantics via implementing appropriate optimizing compilers to abstracting details of machine properties in software systems remain challenging. Performing research at this intersection of quantum computing and software engineering requires sufficient knowledge of the physical processes underlying quantum computations, and how to model these. In this chapter, we review a superoperator-based approach to quantum dynamics, as it can provide means that are sufficiently abstract, yet concrete enough to be useful in quantum software and systems engineering, and outline how it is used in several important applications in the field. KW - quantum computing KW - quantum software engineering KW - software development KW - software engineering Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-64136-7_3 SN - 978-3-031-64136-7 PB - Springer Nature ER - TY - CHAP A1 - Safi, Hila A1 - Wintersperger, Karen A1 - Mauerer, Wolfgang T1 - Influence of HW-SW-Co-Design on Quantum Computing Scalability T2 - 2023 IEEE International Conference on Quantum Software (QSW), Chicago, IL, USA, 02-08 July 2023 N2 - The use of quantum processing units (QPUs) promises speed-ups for solving computational problems. Yet, current devices are limited by the number of qubits and suffer from significant imperfections, which prevents achieving quantum advantage. To step towards practical utility, one approach is to apply hardware-software co-design methods. This can involve tailoring problem formulations and algorithms to the quantum execution environment, but also entails the possibility of adapting physical properties of the QPU to specific applications. In this work, we follow the latter path, and investigate how key figures— circuit depth and gate count—required to solve four cornerstone NP-complete problems vary with tailored hardware properties. Our results reveal that achieving near-optimal performance and properties does not necessarily require optimal quantum hardware, but can be satisfied with much simpler structures that can potentially be realised for many hardware approaches.m Using statistical analysis techniques, we additionally identify an underlying general model that applies to all subject problems. This suggests that our results may be universally applicable to other algorithms and problem domains, and tailored QPUs can find utility outside their initially envisaged problem domains. The substantial possible improvements nonetheless highlight the importance of QPU tailoring to progress towards practical deployment and scalability of quantum software. KW - quantum computing KW - software engineering KW - hardware-software co-design KW - quantum algorithm performance analysis KW - scalability of quantum applications Y1 - 2023 SN - 979-8-3503-0479-4 U6 - https://doi.org/10.1109/QSW59989.2023.00022 SP - 104 EP - 115 PB - IEEE ER - TY - CHAP A1 - Carbonelli, Cecilia A1 - Felderer, Michael A1 - Jung, Matthias A1 - Lobe, Elisabeth A1 - Lochau, Malte A1 - Luber, Sebastian A1 - Mauerer, Wolfgang A1 - Ramler, Rudolf A1 - Schäfer, Ina A1 - Schroth, Christoph ED - Exman, Iaakov ED - Perez-Castillo, Ricardo ED - Piattini, Mario ED - Felderer, Michael T1 - Challenges for Quantum Software Engineering: An Industrial Application Scenario Perspective T2 - Quantum Software: Aspects of Theory and System Design N2 - Quantum software is becoming a key enabler for applying quantum computing to industrial use cases. This poses challenges to quantum software engineering in providing efficient and effective means to develop such software. Eventually, this must be reliably achieved in time, on budget, and in quality, using sound and well-principled engineering approaches. Given that quantum computers are based on fundamentally different principles than classical machines, this raises the question if, how, and to what extent established techniques for systematically engineering software need to be adapted. In this chapter, we analyze three paradigmatic application scenarios for quantum software engineering from an industrial perspective. The respective use cases center around (1) optimization and quantum cloud services, (2) quantum simulation, and (3) embedded quantum computing. Our aim is to provide a concise overview of the current and future applications of quantum computing in diverse industrial settings. We derive presumed challenges for quantum software engineering and thus provide research directions for this emerging field. KW - industrial use cases KW - quantum computing KW - quantum software engineering KW - software development KW - software engineering Y1 - 2024 SN - 978-3-031-64135-0 SN - 978-3-031-64136-7 U6 - https://doi.org/10.1007/978-3-031-64136-7_12 PB - Springer-Nature ER -