@inproceedings{GabrielWittmannHackeretal., author = {Gabriel, Christian and Wittmann, Christoffer and Hacker, B. and Mauerer, Wolfgang and Huntington, E. and Sabuncu, M. and Marquardt, Christoph and Leuchs, Gerd}, title = {A high-speed secure quantum random number generator based on vacuum states}, series = {IEEE/OSA Conference on Lasers and Electro-Optics (CLEO), 06-11 May 2012, San Jose CA USA}, booktitle = {IEEE/OSA Conference on Lasers and Electro-Optics (CLEO), 06-11 May 2012, San Jose CA USA}, publisher = {Optical Society of America}, abstract = {A high-speed continuous-variable quantum random bit generator with an expected effective bit generation rate of up to 10 GBit/s is presented. The obtained bit sequences are truly random and unique, i.e. they cannot be known by an adversary.}, language = {en} } @inproceedings{SchmidbauerWinterspergerLobeetal., author = {Schmidbauer, Lukas and Wintersperger, Karen and Lobe, Elisabeth and Mauerer, Wolfgang}, title = {Polynomial Reduction Methods and their Impact on QAOA Circuits}, series = {IEEE International Conference on Quantum Software (QSW), 7-13 July 2024, Shenzhen, China}, booktitle = {IEEE International Conference on Quantum Software (QSW), 7-13 July 2024, Shenzhen, China}, doi = {10.1109/QSW62656.2024.00018}, pages = {35 -- 45}, abstract = {Abstraction layers are of paramount importance in software architecture, as they shield the higher-level formulation of payload computations from lower-level details. Since quantum computing (QC) introduces many such details that are often unaccustomed to computer scientists, an obvious desideratum is to devise appropriate abstraction layers for QC. For discrete optimisation, one such abstraction is to cast problems in quadratic unconstrained binary optimisation (QUBO) form, which is amenable to a variety of quantum approaches. However, different mathematically equivalent forms can lead to different behaviour on quantum hardware, ranging from ease of mapping onto qubits to performance scalability. In this work, we show how using higher-order problem formulations (that provide better expressivity in modelling optimisation tasks than plain QUBO formulations) and their automatic transformation into QUBO form can be used to leverage such differences to prioritise between different desired non-functional properties for quantum optimisation. Based on a practically relevant use-case and a graph-theoretic analysis, we evaluate how different transformation approaches influence widely used quantum performance metrics (circuit depth, gates count, gate distribution, qubit scaling), and also consider the classical computational efforts required to perform the transformations, as they influence possibilities for achieving future quantum advantage. Furthermore, we establish more general properties and invariants of the transformation methods. Our quantitative study shows that the approach allows us to satisfy different trade-offs, and suggests various possibilities for the future construction of general-purpose abstractions and automatic generation of useful quantum circuits from high-level problem descriptions.}, language = {en} } @misc{BroserFalterŁawrowskietal., author = {Broser, Christian and Falter, Thomas and Ławrowski, Robert Damian and Altenbuchner, Amelie and V{\"o}gele, Daniel and Koss, Claus and Schlamp, Matthias and Dunnweber, Jan and Steffens, Oliver and Heckner, Markus and Jaritz, Sabine and Schiegl, Thomas and Corsten, Sabine and Lauer, Norina and Guertler, Katherine and Koenig, Eric and Haug, Sonja and Huber, Dominik and Birkenmaier, Clemens and Krenkel, Lars and Wagner, Thomas and Justus, Xenia and Saßmannshausen, Sean Patrick and Kleine, Nadine and Weber, Karsten and Braun, Carina N. and Giacoppo, Giuliano and Heinrich, Michael and Just, Tobias and Schreck, Thomas and Schnabl, Andreas and Gilmore, Amador T{\´e}ran and Roeslin, Samuel and Schmid, Sandra and Wellnitz, Felix and Malz, Sebastian and Maurial, Andreas and Hauser, Florian and Mottok, J{\"u}rgen and Klettke, Meike and Scherzinger, Stefanie and St{\"o}rl, Uta and Heckner, Markus and Bazo, Alexander and Wolff, Christian and Kopper, Andreas and Westner, Markus and Pongratz, Christian and Ehrlich, Ingo and Briem, Ulrich and Hederer, Sebastian and Wagner, Marcus and Schillinger, Moritz and G{\"o}rlach, Julien and Hierl, Stefan and Siegl, Marco and Langer, Christoph and Hausladen, Matthias and Schreiner, Rupert and Haslbeck, Matthias and Kreuzer, Reinhard and Br{\"u}ckl, Oliver and Dawoud, Belal and Rabl, Hans-Peter and Gamisch, Bernd and Schmidt, Ottfried and Heberl, Michael and G{\"a}nsbauer, Bianca and Bick, Werner and Ellermeier, Andreas and Monkman, Gareth J. and Prem, Nina and Sindersberger, Dirk and Tschurtschenthaler, Karl and Aurbach, Maximilian and Dendorfer, Sebastian and Betz, Michael A. and Szecsey, Tamara and Mauerer, Wolfgang and Murr, Florian}, title = {Forschung 2018}, editor = {Baier, Wolfgang}, address = {Regensburg}, organization = {Ostbayerische Technische Hochschule Regensburg}, isbn = {978-3-9818209-5-9}, doi = {10.35096/othr/pub-1382}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-13826}, pages = {98}, subject = {Forschung}, language = {de} } @inproceedings{HoessParadisKazmanetal., author = {Hoess, Nicole and Paradis, Carlos and Kazman, Rick and Mauerer, Wolfgang}, title = {Does the Tool Matter? Exploring Some Causes of Threats to Validity in Mining Software Repositories}, series = {2025 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Montreal, QC, Canada, March, 4-7, 2025}, booktitle = {2025 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Montreal, QC, Canada, March, 4-7, 2025}, publisher = {IEEE}, isbn = {979-8-3315-3510-0}, doi = {10.1109/SANER64311.2025.00067}, pages = {645 -- 656}, abstract = {Software repositories are an essential source of information for software engineering research on topics such as project evolution and developer collaboration. Appropriate mining tools and analysis pipelines are therefore an indispensable precondition for many research activities. Ideally, valid results should not depend on technical details of data collection and processing. It is, however, widely acknowledged that mining pipelines are complex, with a multitude of implementation decisions made by tool authors based on their interests and assumptions. This raises the questions if (and to what extent) tools agree on their results and are interchangeable. In this study, we use two tools to extract and analyse ten large software projects, quantitatively and qualitatively comparing results and derived data to better understand this concern. We analyse discrepancies from a technical point of view, and adjust code and parametrisation to minimise replication differences. Our results indicate that despite similar trends, even simple metrics such as the numbers of commits and developers may differ by up to 500\%. We find that such substantial differences are often caused by minor technical details. We show how tool-level and data post-processing changes can overcome these issues, but find they may require considerable efforts. We summarise identified causes in our lessons learned to help researchers and practitioners avoid common pitfalls, and reflect on implementation decisions and their influence in ensuring obtained data meets explicit and implicit expectations. Our findings lead us to hypothesise that similar uncertainties exist in other analysis tools, which may limit the validity of conclusions drawn in tool-centric research.}, language = {en} } @incollection{CarbonelliFeldererJungetal., author = {Carbonelli, Cecilia and Felderer, Michael and Jung, Matthias and Lobe, Elisabeth and Lochau, Malte and Luber, Sebastian and Mauerer, Wolfgang and Ramler, Rudolf and Sch{\"a}fer, Ina and Schroth, Christoph}, title = {Challenges for Quantum Software Engineering: An Industrial Application Scenario Perspective}, series = {Quantum Software: Aspects of Theory and System Design}, booktitle = {Quantum Software: Aspects of Theory and System Design}, editor = {Exman, Iaakov and Perez-Castillo, Ricardo and Piattini, Mario and Felderer, Michael}, publisher = {Springer-Nature}, isbn = {978-3-031-64135-0}, doi = {10.1007/978-3-031-64136-7_12}, abstract = {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.}, language = {en} } @unpublished{AmmermannMauererSchaefer, author = {Ammermann, Joshua and Mauerer, Wolfgang and Sch{\"a}fer, Ina}, title = {Towards View-based Development of Quantum Software}, abstract = {Quantum computing is an interdisciplinary field that relies on the expertise of many different stakeholders. The views of various stakeholders on the subject of quantum computing may differ, thereby complicating communication. To address this, we propose a view-based quantum development approach based on a Single Underlying Model (SUM) and a supporting quantumIntegrated Development Environment (IDE). We highlight emerging challenges for future research.}, language = {en} } @misc{SchoenbergerScherzingerMauerer, author = {Sch{\"o}nberger, Manuel and Scherzinger, Stefanie and Mauerer, Wolfgang}, title = {Quantum Computing for DB - Applicability on Multi Query Optimization and Join Order Optimization}, series = {Fr{\"u}hjahrstreffen Fachgruppe Datenbanken in Potsdam, 2022}, journal = {Fr{\"u}hjahrstreffen Fachgruppe Datenbanken in Potsdam, 2022}, language = {en} } @inproceedings{SchoenbergerFranzScherzingeretal., author = {Sch{\"o}nberger, Manuel and Franz, Maja and Scherzinger, Stefanie and Mauerer, Wolfgang}, title = {Peel | Pile? Cross-Framework Portability of Quantum Software}, series = {2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C), 12-15 March 2022, Honolulu, HI, USA}, booktitle = {2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C), 12-15 March 2022, Honolulu, HI, USA}, publisher = {IEEE}, doi = {10.1109/ICSA-C54293.2022.00039}, abstract = {In recent years, various vendors have made quantum software frameworks available. Yet with vendor-specific frameworks, code portability seems at risk, especially in a field where hardware and software libraries have not yet reached a consolidated state, and even foundational aspects of the technologies are still in flux. Accordingly, the development of vendor-independent quantum programming languages and frameworks is often suggested. This follows the established architectural pattern of introducing additional levels of abstraction into software stacks, thereby piling on layers of abstraction. Yet software architecture also provides seemingly less abstract alternatives, namely to focus on hardware-specific formulations of problems that peel off unnecessary layers. In this article, we quantitatively and experimentally explore these strategic alternatives, and compare popular quantum frameworks from the software implementation perspective. We find that for several specific, yet generalisable problems, the mathematical formulation of the problem to be solved is not just sufficiently abstract and serves as precise description, but is likewise concrete enough to allow for deriving framework-specific implementations with little effort. Additionally, we argue, based on analysing dozens of existing quantum codes, that porting between frameworks is actually low-effort, since the quantum- and framework-specific portions are very manageable in terms of size, commonly in the order of mere hundreds of lines of code. Given the current state-of-the-art in quantum programming practice, this leads us to argue in favour of peeling off unnecessary abstraction levels.}, language = {en} } @unpublished{SchoenbergerTrummerMauerer, author = {Sch{\"o}nberger, Manuel and Trummer, Immanuel and Mauerer, Wolfgang}, title = {Quantum-Inspired Digital Annealing for Join Ordering}, series = {Proceedings of the VLDB Endowment}, journal = {Proceedings of the VLDB Endowment}, pages = {14}, abstract = {Finding the optimal join order (JO) is one of the most important problems in query optimisation, and has been extensively considered in research and practise. As it involves huge search spaces, approximation approaches and heuristics are commonly used, which explore a reduced solution space at the cost of solution quality. To explore even large JO search spaces, we may consider special-purpose software, such as mixed-integer linear programming (MILP) solvers, which have successfully solved JO problems. However, even mature solvers cannot overcome the limitations of conventional hardware prompted by the end of Moore's law. We consider quantum-inspired digital annealing hardware, which takes inspiration from quantum processing units (QPUs). Unlike QPUs, which likely remain limited in size and reliability in the near and mid-term future, the digital annealer (DA) can solve large instances of mathematically encoded optimisation problems today. We derive a novel, native encoding for the JO problem tailored to this class of machines that substantially improves over known MILP and quantum-based encodings, and reduces encoding size over the state-of-the-art. By augmenting the computation with a novel readout method, we derive valid join orders for each solution obtained by the (probabilistically operating) DA. Most importantly and despite an extremely large solution space, our approach scales to practically relevant dimensions of around 50 relations and improves result quality over conventionally employed approaches, adding a novel alternative to solving the long-standing JO problem.}, language = {en} } @unpublished{SchmidlDengMaetal., author = {Schmidl, Sebastian and Deng, Yangshen and Ma, Pingchuan and Sch{\"o}nberger, Manuel and Mauerer, Wolfgang}, title = {Reproducibility Report for ACM SIGMOD 2023 Paper: Ready to Leap (by Co-Design)? Join Order Optimisation}, abstract = {The paper "Ready to Leap (by Co-Design)? Join Order Optimisation on Quantum Hardware" proposes the first approach to solve the problem of join order optimization on quantum hardware. The authors characterize the applicability and limitations of current state-of-the-art quantum hardware, i. e. gate-based quantum computing and quantum annealing, for join ordering and recommend key improvements to the physical hardware to reach practical utility. Based on the provided database queries and QPU system processing data, we have been able to reproduce the original paper's key insights and quantum problem characteristics reported in its experimental section. The authors provided a self-contained and fully automated reproduction package, including data (database queries, statistics, and collected QPU processing data), experiment scripts, and plotting routines that allowed the identical reconstruction of the three main figures in the paper.}, language = {en} } @misc{SchoenbergerScherzingerMauerer, author = {Sch{\"o}nberger, Manuel and Scherzinger, Stefanie and Mauerer, Wolfgang}, title = {Applicability of Quantum Computing on Database Query Optimization}, series = {Fr{\"u}hjahrstreffen Fachgruppe Datenbanken in Potsdam (Poster Presentation)}, journal = {Fr{\"u}hjahrstreffen Fachgruppe Datenbanken in Potsdam (Poster Presentation)}, language = {en} } @article{SafiBandicNiedermeieretal., author = {Safi, Hila and Bandic, Medina and Niedermeier, Christoph and Almudever, Carmen G. and Feld, Sebastian and Mauerer, Wolfgang}, title = {Stacking the odds: full-stack quantum system design space exploration}, series = {EPJ Quantum Technology}, volume = {12}, journal = {EPJ Quantum Technology}, publisher = {Springer}, address = {Heidelberg}, doi = {10.1140/epjqt/s40507-025-00413-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-85157}, pages = {31}, abstract = {Design space exploration (DSE) plays an important role in optimising quantum circuit execution by systematically evaluating different configurations of compilation strategies and hardware settings. In this paper, we conduct a comprehensive investigation into the impact of various layout methods, qubit routing techniques, and optimisation levels, as well as device-specific properties such as different variants and strengths of noise and imperfections, the topological structure of qubits, connectivity densities, and back-end sizes. By spanning through these dimensions, we aim to understand the interplay between compilation choices and hardware characteristics. A key question driving our exploration is whether the optimal selection of device parameters, mapping techniques, comprising of initial layout strategies and routing heuristics can mitigate device induced errors beyond standard error mitigation approaches. Our results show that carefully selecting software strategies (e.g., mapping and routing algorithms) and tailoring hardware characteristics (such as minimising noise and leveraging topology and connectivity density) significantly improve the fidelity of circuit execution outcomes, and thus the expected correctness or success probability of the computational result. We provide estimates based on key metrics such as circuit depth, gate count and expected fidelity. Our results highlight the importance of hardware-software co-design, particularly as quantum systems scale to larger dimensions, and along the way towards fully error corrected quantum systems: Our study is based on computationally noisy simulations, but considers various implementations of quantum error correction (QEC) using the same approach as for other algorithms. The observed sensitivity of circuit fidelity to noise and connectivity suggests that co-design principles will be equally critical when integrating QEC in future systems. Our exploration provides practical guidelines for co-optimising physical mapping, qubit routing, and hardware configurations in realistic quantum computing scenarios.}, language = {en} } @inproceedings{FranzWinkerGroppeetal., author = {Franz, Maja and Winker, Tobias and Groppe, Sven and Mauerer, Wolfgang}, title = {Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation}, series = {2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 15-20 September 2024, Montreal, QC, Canada}, booktitle = {2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 15-20 September 2024, Montreal, QC, Canada}, publisher = {IEEE}, doi = {10.1109/QCE60285.2024.00055}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-76877}, pages = {409 -- 420}, abstract = {Identifying optimal join orders (JOs) stands out as a key challenge in database research and engineering. Owing to the large search space, established classical methods rely on approximations and heuristics. Recent efforts have successfully explored reinforcement learning (RL) for JO. Likewise, quantum versions of RL have received considerable scientific attention. Yet, it is an open question if they can achieve sustainable, overall practical advantages with improved quantum processors. In this paper, we present a novel approach that uses quantum reinforcement learning (QRL) for JO based on a hybrid variational quantum ansatz. It is able to handle general bushy join trees instead of resorting to simpler left-deep variants as compared to approaches based on quantum(-inspired) optimisation, yet requires multiple orders of magnitudes fewer qubits, which is a scarce resource even for post-NISQ systems. Despite moderate circuit depth, the ansatz exceeds current NISQ capabilities, which requires an evaluation by numerical simulations. While QRL may not significantly outperform classical approaches in solving the JO problem with respect to result quality (albeit we see parity), we find a drastic reduction in required trainable parameters. This benefits practically relevant aspects ranging from shorter training times compared to classical RL, less involved classical optimisation passes, or better use of available training data, and fits data-stream and low-latency processing scenarios. Our comprehensive evaluation and careful discussion delivers a balanced perspective on possible practical quantum advantage, provides insights for future systemic approaches, and allows for quantitatively assessing trade-offs of quantum approaches for one of the most crucial problems of database management systems.}, language = {en} } @article{KruegerMauerer, author = {Kr{\"u}ger, Tom and Mauerer, Wolfgang}, title = {Out of the Loop: Structural Approximation of Optimisation Landscapes and non-Iterative Quantum Optimisation}, series = {Quantum}, volume = {9}, journal = {Quantum}, publisher = {Verein zur F{\"o}rderung des Open Access Publizierens in den Quantenwissenschaften}, doi = {10.22331/q-2025-11-06-1903}, pages = {32}, abstract = {The Quantum Approximate Optimisation Algorithm (QAOA) is a widely studied quantum-classical iterative heuristic for combinatorial optimisation. While QAOA targets problems in complexity class NP, the classical optimisation procedure required in every iteration is itself known to be NP-hard. Still, advantage over classical approaches is suspected for certain scenarios, but nature and origin of its computational power are not yet satisfactorily understood. By introducing means of efficiently and accurately approximating the QAOA optimisation landscape from solution space structures, we derive a new algorithmic variant of unit-depth QAOA for two-level Hamiltonians (including all problems in NP): Instead of performing an iterative quantum-classical computation for each input instance, our non-iterative method is based on a quantum circuit that is instance-independent, but problem-specific. It matches or outperforms unit-depth QAOA for key combinatorial problems, despite reduced computational effort. Our approach is based on proving a long-standing conjecture regarding instance-independent structures in QAOA. By ensuring generality, we link existing empirical observations on QAOA parameter clustering to established approaches in theoretical computer science, and provide a sound foundation for understanding the link between structural properties of solution spaces and quantum optimisation.}, language = {de} } @inproceedings{SchoenbergerTrummerMauerer, author = {Sch{\"o}nberger, Manuel and Trummer, Immanuel and Mauerer, Wolfgang}, title = {Large-Scale Multiple Query Optimisation with Incremental Quantum(-Inspired) Annealing}, series = {Proceedings of the ACM on Management of Data}, volume = {3}, booktitle = {Proceedings of the ACM on Management of Data}, number = {4}, publisher = {ACM}, doi = {10.1145/3749171}, pages = {25}, abstract = {Multiple-query optimization (MQO) seeks to reduce redundant work across query batches. While MQO offers opportunities for dramatic performance improvements, the problem is NP-hard, limiting the sizes of problems that can be solved on generic hardware. We propose to leverage specialized hardware solvers for optimization, such as Fujitsu's Digital Annealer (DA), to scale up MQO to problem sizes formerly out of reach. We present a novel incremental processing approach that combines classical computation with DA acceleration. By efficiently partitioning MQO problems into sets of partial problems, and by applying a dynamic search steering strategy that reapplies initially discarded information to incrementally process individual problems, our method overcomes capacity limitations, and scales to extremely large MQO instances (up to νm1000 queries). A thorough and comprehensive empirical evaluation finds our method substantially outperforms existing approaches. Our generalisable framework lays the ground for other database use-cases on quantum-inspired hardware, and bridges towards future quantum accelerators.}, language = {en} } @unpublished{KruegerMauerer, author = {Kr{\"u}ger, Tom and Mauerer, Wolfgang}, title = {Out of the Loop: Structural Approximation of Optimisation Landscapes and non-Iterative Quantum Optimisation}, pages = {20}, abstract = {The Quantum Approximate Optimisation Algorithm (qaoa) is a widely studied quantum-classical iterative heuristic for combinatorial optimisation. While qaoa targets problems in complexity class NP, the classical optimisation procedure required in every iteration is itself known to be NP-hard. Still, advantage over classical approaches is suspected for certain scenarios, but nature and origin of its computational power are not yet satisfactorily understood. By introducing means of efficiently and accurately approximating the qaoa optimisation landscape from solution space structures, we derive a new algorithmic variant: Instead of performing an iterative quantum-classical computation for each input instance, our non-iterative method is based on a quantum circuit that is instance-independent, but problem-specific. It matches or outperforms unit-depth qaoa for key combinatorial problems, despite reduced computational effort. Our approach is based on proving a long-standing conjecture regarding instance-independent structures in qaoa. By ensuring generality, we link existing empirical observations on qaoa parameter clustering to established approaches in theoretical computer science, and provide a sound foundation for understanding the link between structural properties of solution spaces and quantum optimisation.}, language = {en} } @incollection{Mauerer, author = {Mauerer, Wolfgang}, title = {Quantum Software = Quantum minus Software?}, series = {Dagstuhl Reports : Quantum Software Engineering : Report from Dagsthul Seminar 24512}, volume = {14}, booktitle = {Dagstuhl Reports : Quantum Software Engineering : Report from Dagsthul Seminar 24512}, number = {12}, editor = {Ali, Shaukat and Barzen, Johanna and Delgado, Andrea and M{\"u}ller, Hausi A. and Murillo, Juan Manuel}, publisher = {Dagstuhl Publishing}, doi = {10.4230/DagRep.14.12.63}, url = {http://nbn-resolving.de/urn:nbn:de:0030-drops-230469}, pages = {73 -- 74}, abstract = {The Dagstuhl Seminar 24512 on "Quantum Software Engineering" was held from December 15 to 20, 2024. It brought together 26 participants from industry and academia from 13 different countries, including senior and junior researchers as well as practitioners in the field of Quantum Software Engineering. The aim of the seminar was to advance software engineering methods and tools for the engineering of hybrid quantum systems by promoting personal interaction and open discussion among researchers who are already working in this emerging area of knowledge. The first day of the seminar was devoted to the topic "When software engineering meets quantum mechanics", while the second day focused on "Quantum software engineering and its challenges." During both days, 16 invited presentations were given. The rest of the seminar was organized into three working groups to address the topics "Quantum Software Design, Modelling and Architecturing", "Adaptive Hybrid Quantum Systems", and "Quantum Software Quality Assurance". The seminar was a very fruitful experience for all participants both in terms of scientific outcomes and in terms of the personal relationships that were generated to jointly address future experiences.}, language = {en} } @misc{MauererJoblinTamburrietal., author = {Mauerer, Wolfgang and Joblin, Mitchell and Tamburri, Damian Andrew and Paradis, Carlos and Kazman, Rick and Apel, Sven}, title = {In Search of Socio-Technical Congruence: A Large-Scale Longitudinal Study [Data set]}, doi = {10.5281/zenodo.4766388}, language = {en} } @misc{MauererScherzinger, author = {Mauerer, Wolfgang and Scherzinger, Stefanie}, title = {Nullius in Verba - Reproducibility Tutorial [Data set]}, doi = {10.5281/zenodo.4730023}, abstract = {Reproduction package (docker image) for the ICDE 2021 tutorial "Nullius in Verba".}, language = {en} } @misc{SchmidbauerLobeSchaeferetal., author = {Schmidbauer, Lukas and Lobe, Elisabeth and Sch{\"a}fer, Ina and Mauerer, Wolfgang}, title = {It's Quick to be Square: Fast Quadratisation for Quantum Toolchains [Data set]}, doi = {10.5281/zenodo.14245588}, abstract = {Many of the envisioned use-cases for quantum computers involve optimisation processes. While there are many algorithmic primitives to perform the required calculations, all eventually lead to quantum gates operating on quantum bits, with an order as determined by the structure of the objective function and the properties of target hardware. When the structure of the problem representation is not aligned with structure and boundary conditions of the executing hardware, various overheads to degrade the computation may arise, possibly negating any possible quantum advantage. Therefore, automatic transformations of problem representations play an important role in quantum computing when descriptions (semi-)targeted at humans must be cast into forms that can be executed on quantum computers. Mathematically equivalent formulations are known to result in substantially different non-functional properties depending on hardware, algorithm and detail properties of the problem. Given the current state of noisy-intermediate scale quantum hardware (NISQ), these effects are considerably more pronounced than in classical computing. Likewise, efficiency of the transformation itself is relevant because possible quantum advantage may easily be eradicated by the overhead of transforming between representations. In this paper we consider a specific class of higher-level representations (polynomial unconstrained binary optimisation problems), and devise novel automatic transformation mechanisms into widely used quadratic unconstrained binary optimisation problems that substantially improve efficiency and versatility over the state of the art. We also identify what influence factors of lower-level details can be abstracted away in the transformation process, and which details must be made available to higher-level abstractions.}, language = {en} } @misc{SchmidbauerMauerer, author = {Schmidbauer, Lukas and Mauerer, Wolfgang}, title = {SAT Strikes Back: Parameter and Path Relations in Quantum Toolchains [Data set]}, doi = {10.5281/zenodo.15464391}, abstract = {In the foreseeable future, toolchains for quantum computing should offer automatic means of transforming a high level problem formulation down to a hardware executable form. Thereby, it is crucial to find (multiple) transformation paths that are optimised for (hardware specific) metrics. We zoom into this pictured tree of transformations by focussing on k-SAT instances as input and their transformation to QUBO, while considering structure and characteristic metrics of input, intermediate and output representations. Our results can be used to rate valid paths of transformation in advance—also in automated (quantum) toolchains. We support the automation aspect by considering stability and therefore predictability of free parameters and transformation paths. Moreover, our findings can be used in the manifesting era of error correction (since considering structure in a high abstraction layer can benefit error correcting codes in layers below). We also show that current research is closely linked to quadratisation techniques and their mathematical foundation.}, language = {en} } @inproceedings{RamsauerLohmannMauerer, author = {Ramsauer, Ralf and Lohmann, Daniel and Mauerer, Wolfgang}, title = {Reliable Pre-Integration Tracking of Commits on Mailing Lists}, series = {Invited Talk at Safety Summit at Embedded Linux Conference Europe (ELCE18)}, booktitle = {Invited Talk at Safety Summit at Embedded Linux Conference Europe (ELCE18)}, address = {Edinburgh, Scotland}, language = {en} } @unpublished{EichenseherFranzWolffetal., author = {Eichenseher, Vincent and Franz, Maja and Wolff, Christian and Mauerer, Wolfgang}, title = {Pattern or Not? QAOA Parameter Heuristics and Potentials of Parsimony}, doi = {10.48550/arXiv.2510.08153}, pages = {22}, abstract = {Structured variational quantum algorithms such as the Quantum Approximate Optimisation Algorithm (QAOA) have emerged as leading candidates for exploiting advantages of near-term quantum hardware. They interlace classical computation, in particular optimisation of variational parameters, with quantum-specific routines, and combine problem-specific advantages -- sometimes even provable -- with adaptability to the constraints of noisy, intermediate-scale quantum (NISQ) devices. While circuit depth can be parametrically increased and is known to improve performance in an ideal (noiseless) setting, on realistic hardware greater depth exacerbates noise: The overall quality of results depends critically on both, variational parameters and circuit depth. Although identifying optimal parameters is NP-hard, prior work has suggested that they may exhibit regular, predictable patterns for increasingly deep circuits and depending on the studied class of problems. In this work, we systematically investigate the role of classical parameters in QAOA performance through extensive numerical simulations and suggest a simple, yet effective heuristic scheme to find good parameters for low-depth circuits. Our results demonstrate that: (i) optimal parameters often deviate substantially from expected patterns; (ii) QAOA performance becomes progressively less sensitive to specific parameter choices as depth increases; and (iii) iterative component-wise fixing performs on par with, and at shallow depth may even outperform, several established parameter-selection strategies. We identify conditions under which structured parameter patterns emerge, and when deviations from the patterns warrant further consideration. These insights for low-depth circuits may inform more robust pathways to harnessing QAOA in realistic quantum compute scenarios.}, language = {en} } @unpublished{GierischMauerer, author = {Gierisch, Vincent and Mauerer, Wolfgang}, title = {QEF: Reproducible and Exploratory Quantum Software Experiments}, doi = {10.48550/arXiv.2511.04563}, pages = {12}, abstract = {Commercially available Noisy Intermediate-Scale Quantum (NISQ) devices now make small hybrid quantum-classical experiments practical, but many tools hide configuration or demand ad-hoc scripting. We introduce the Quantum Experiment Framework (QEF): A lightweight framework designed to support the systematic, hypothesis-driven study of quantum algorithms. Unlike many existing approaches, QEF emphasises iterative, exploratory analysis of evolving experimental strategies rather than exhaustive empirical evaluation of fixed algorithms using predefined quality metrics. The framework's design is informed by a comprehensive review of the literature, identifying principal parameters and measurement practices currently reported in the field. QEF captures all key aspects of quantum software and algorithm experiments through a concise specification that expands into a Cartesian product of variants for controlled large-scale parameter sweeps. This design enables rigorous and systematic evaluation, as well as precise reproducibility. Large sweeps are automatically partitioned into asynchronous jobs across simulators or cloud hardware, and ascertain full hyper-parameter traceability. QEF supports parameter reuse to improve overall experiment runtimes, and collects all metrics and metadata into a form that can be conveniently explored with standard statistical and visualisation software. By combining reproducibility and scalability while avoiding the complexities of full workflow engines, QEF seeks to lower the practical barriers to empirical research on quantum algorithms, whether these are designed for current NISQ devices or future error-corrected quantum systems.}, language = {en} } @inproceedings{SchoenbergerTrummerMauerer, author = {Sch{\"o}nberger, Manuel and Trummer, Immanuel and Mauerer, Wolfgang}, title = {Hybrid Mixed Integer Linear Programming for Large-Scale Join Order Optimisation}, series = {Proceedings of the VLDB Endowment}, volume = {19}, booktitle = {Proceedings of the VLDB Endowment}, number = {3}, publisher = {VLDB Endowment}, doi = {10.14778/3778092.3778097}, pages = {348 -- 360}, abstract = {Finding optimal join orders is among the most crucial steps to be performed by query optimisers. Though extensively studied in data management research, the problem remains far from solved: While query optimisers rely on exhaustive search methods to determine ideal solutions for small problems, such methods reach their limits once queries grow in size. Yet, large queries become increasingly common in real-world scenarios, and require suitable methods to generate efficient execution plans. While a variety of heuristics have been proposed for large-scale query optimisation, they suffer from degrading solution quality as queries grow in size, or feature highly sub-optimal worst-case behavior, as we will show. We propose a novel method based on the paradigm of mixed integer linear programming (MILP): By deriving a novel MILP model capable of optimising arbitrary bushy tree structures, we address the limitations of existing MILP methods for join ordering, and can rely on highly optimised MILP solvers to derive efficient tree structures that elude competing methods. To ensure optimisation efficiency, we embed our MILP method into a hybrid framework, which applies MILP solvers precisely where they provide the greatest advantage over competitors, while relying on more efficient methods for less complex optimisation steps. Thereby, our approach gracefully scales to extremely large query sizes joining up to 100 relations, and consistently achieves the most robust plan quality among a large variety of competing join ordering methods.}, language = {en} } @article{SchmidbauerLobeSchaeferetal., author = {Schmidbauer, Lukas and Lobe, Elisabeth and Schaefer, Ina and Mauerer, Wolfgang}, title = {It's Quick to be Square: Fast Quadratisation for Quantum Toolchains}, series = {ACM Transactions on Quantum Computing}, volume = {7}, journal = {ACM Transactions on Quantum Computing}, number = {2}, publisher = {ACM}, doi = {10.1145/3800943}, pages = {46}, abstract = {Many of the envisioned use-cases for quantum computers involve optimisation processes. While there are many algorithmic primitives to perform the required calculations, all eventually lead to quantum gates operating on quantum bits, with an order as determined by the structure of the objective function and the properties of target hardware. When the structure of the problem representation is not aligned with structure and boundary conditions of the executing hardware, various overheads degrading the computation may arise, possibly negating any possible quantum advantage. Therefore, automatic transformations of problem representations play an important role in quantum computing when descriptions (semi-)targeted at humans must be cast into forms that can be "executed" on quantum computers. Mathematically equivalent formulations are known to result in substantially different non-functional properties depending on hardware, algorithm and detail properties of the problem. Given the current state of noisy intermediate-scale quantum (NISQ) hardware, these effects are considerably more pronounced than in classical computing. Likewise, efficiency of the transformation itself is relevant because possible quantum advantage may easily be eradicated by the overhead of transforming between representations. In this paper, we consider a specific class of higher-level representations, that is, PUBOs, and devise novel automatic transformation mechanisms into widely used QUBOs that substantially improve efficiency and versatility over the state of the art. In addition, we conduct a comprehensive investigation of industry-relevant problem formulations and their conversion into a quantum-specific representation, identifying significant obstacles in scaling behaviour and demonstrating how these can be circumvented.}, language = {en} }