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    <title language="eng">Reproducibility Report for ACM SIGMOD 2023 Paper: Ready to Leap (by Co-Design)? Join Order Optimisation</title>
    <abstract language="eng">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&#13;
allowed the identical reconstruction of the three main figures in the paper.</abstract>
    <identifier type="url">https://www.lfdr.de/Publications/2024/SIGMOD_ARI_2023___Paper_37.pdf</identifier>
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    <author>Sebastian Schmidl</author>
    <author>Yangshen Deng</author>
    <author>Pingchuan Ma</author>
    <author>Manuel Schönberger</author>
    <author>Wolfgang Mauerer</author>
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    <title language="eng">Applicability of Quantum Computing on Database Query Optimization</title>
    <parentTitle language="eng">Frühjahrstreffen Fachgruppe Datenbanken in Potsdam (Poster Presentation)</parentTitle>
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    <author>Manuel Schönberger</author>
    <author>Stefanie Scherzinger</author>
    <author>Wolfgang Mauerer</author>
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    <pageNumber>31</pageNumber>
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    <volume>12</volume>
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    <title language="eng">Stacking the odds: full-stack quantum system design space exploration</title>
    <abstract language="deu">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.</abstract>
    <parentTitle language="deu">EPJ Quantum Technology</parentTitle>
    <identifier type="doi">10.1140/epjqt/s40507-025-00413-7</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-85157</identifier>
    <note>Corresponding author der OTH Regensburg: Hila Safi</note>
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    <author>Hila Safi</author>
    <author>Medina Bandic</author>
    <author>Christoph Niedermeier</author>
    <author>Carmen G. Almudever</author>
    <author>Sebastian Feld</author>
    <author>Wolfgang Mauerer</author>
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    <title language="eng">Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation</title>
    <abstract language="eng">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.&#13;
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.&#13;
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.</abstract>
    <parentTitle language="eng">2024 IEEE International Conference on Quantum Computing and Engineering (QCE),  15-20 September 2024,  Montreal, QC, Canada</parentTitle>
    <identifier type="doi">10.1109/QCE60285.2024.00055</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-76877</identifier>
    <note>Corresponding author der OTH Regensburg: Maja Franz</note>
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    <language>deu</language>
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    <volume>9</volume>
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    <title language="deu">Out of the Loop: Structural Approximation of Optimisation Landscapes and non-Iterative Quantum Optimisation</title>
    <abstract language="deu">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.&#13;
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.&#13;
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.</abstract>
    <parentTitle language="deu">Quantum</parentTitle>
    <identifier type="doi">10.22331/q-2025-11-06-1903</identifier>
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    <author>Tom Krüger</author>
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    <title language="eng">Large-Scale Multiple Query Optimisation with Incremental Quantum(-Inspired) Annealing</title>
    <abstract language="eng">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.&#13;
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.</abstract>
    <parentTitle language="eng">Proceedings of the ACM on Management of Data</parentTitle>
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    <author>Manuel Schönberger</author>
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    <title language="eng">Out of the Loop: Structural Approximation of Optimisation Landscapes and non-Iterative Quantum Optimisation</title>
    <abstract language="eng">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.</abstract>
    <identifier type="arxiv">2408.06493</identifier>
    <note>er Aufsatz wurde peer-reviewed veröffentlicht und ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/start/3/rows/10/sortfield/score/sortorder/desc/searchtype/simple/query/out+of+the+loop/docId/8843</note>
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    <author>Tom Krüger</author>
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    <title language="eng">Quantum Software = Quantum minus Software?</title>
    <abstract language="eng">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.</abstract>
    <parentTitle language="eng">Dagstuhl Reports : Quantum Software Engineering : Report from Dagsthul Seminar 24512</parentTitle>
    <identifier type="doi">10.4230/DagRep.14.12.63</identifier>
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    <author>Wolfgang Mauerer</author>
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    <title language="eng">In Search of Socio-Technical Congruence: A Large-Scale Longitudinal Study [Data set]</title>
    <identifier type="doi">10.5281/zenodo.4766388</identifier>
    <note>Archive of the accompanying website including all datasets for "In Search of Socio-Technical Congruence: A Large-Scale Longitudinal Study" (IEEE Transactions on Software Engineering): https://doi.org/10.1109/TSE.2021.3082074</note>
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    <author>Wolfgang Mauerer</author>
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    <title language="eng">Nullius in Verba - Reproducibility Tutorial [Data set]</title>
    <abstract language="eng">Reproduction package (docker image) for the ICDE 2021 tutorial "Nullius in Verba".</abstract>
    <identifier type="doi">10.5281/zenodo.4730023</identifier>
    <note>In Verbindung mit dem Konferenzbeitrag: Nullius in Verba: Reproducibility for Database Systems Research, Revisited - https://doi.org/10.1109/ICDE51399.2021.00270</note>
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    <title language="eng">It's Quick to be Square: Fast Quadratisation for Quantum Toolchains [Data set]</title>
    <abstract language="eng">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.&#13;
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.</abstract>
    <identifier type="doi">10.5281/zenodo.14245588</identifier>
    <note>Paper: 10.48550/arXiv.2411.19934&#13;
Software: https://github.com/lfd/Fast_Quadratisation</note>
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    <author>Elisabeth Lobe</author>
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    <author>Wolfgang Mauerer</author>
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    <title language="eng">SAT Strikes Back: Parameter and Path Relations in Quantum Toolchains [Data set]</title>
    <abstract language="eng">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.&#13;
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)&#13;
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&#13;
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.</abstract>
    <identifier type="doi">10.5281/zenodo.15464391</identifier>
    <note>Repositoriy URL: https://github.com/lfd/QSW25-SAT-Strikes-Back</note>
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    <title language="eng">Reliable Pre-Integration Tracking of Commits on Mailing Lists</title>
    <parentTitle language="eng">Invited Talk at Safety Summit at Embedded Linux Conference Europe (ELCE18)</parentTitle>
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    <author>Ralf Ramsauer</author>
    <author>Daniel Lohmann</author>
    <author>Wolfgang Mauerer</author>
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    <title language="eng">Pattern or Not? QAOA Parameter Heuristics and Potentials of Parsimony</title>
    <abstract language="eng">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.</abstract>
    <identifier type="doi">10.48550/arXiv.2510.08153</identifier>
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    <author>Vincent Eichenseher</author>
    <author>Maja Franz</author>
    <author>Christian Wolff</author>
    <author>Wolfgang Mauerer</author>
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    <title language="eng">QEF: Reproducible and Exploratory Quantum Software Experiments</title>
    <abstract language="eng">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.&#13;
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.&#13;
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.&#13;
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.</abstract>
    <identifier type="doi">10.48550/arXiv.2511.04563</identifier>
    <identifier type="arxiv">2511.04563</identifier>
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    <author>Vincent Gierisch</author>
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    <title language="eng">Hybrid Mixed Integer Linear Programming for Large-Scale Join Order Optimisation</title>
    <abstract language="eng">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.&#13;
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.</abstract>
    <parentTitle language="eng">Proceedings of the VLDB Endowment</parentTitle>
    <identifier type="doi">10.14778/3778092.3778097</identifier>
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    <author>Manuel Schönberger</author>
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    <title language="eng">It’s Quick to be Square: Fast Quadratisation for Quantum Toolchains</title>
    <abstract language="eng">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.&#13;
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.</abstract>
    <parentTitle language="eng">ACM Transactions on Quantum Computing</parentTitle>
    <identifier type="doi">10.1145/3800943</identifier>
    <note>Preprint ebenfalls auf OPUS veröffentlicht: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/7937</note>
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    <author>Lukas Schmidbauer</author>
    <author>Elisabeth Lobe</author>
    <author>Ina Schaefer</author>
    <author>Wolfgang Mauerer</author>
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    <title language="eng">Towards System-Level Quantum-Accelerator Integration</title>
    <abstract language="eng">Quantum computers are often treated as experimental add-ons that are loosely coupled to classical infrastructure through high-level interpreted languages and cloud-like orchestration. However, future deployments in both, high-performance computing (HPC) and embedded environments, will demand tighter integration for lower latencies, stronger determinism, and architectural consistency, as well as to implement error correction and other tasks that require tight quantum-classical interaction as generically as possible.&#13;
We propose a vertically integrated quantum systems architecture that treats quantum accelerators and processing units as peripheral system components. A central element is the Quantum Abstraction Layer (QAL) at operating system kernel level. It aims at real-time, low-latency, and high-throughput interaction between quantum and classical resources, as well as robust low-level quantum operations scheduling and generic resource management. It can serve as blueprint for orchestration of low-level computational components "around" a QPU (and inside a quantum computer), and across different modalities.&#13;
We present first results towards such an integrated architecture, including a virtual QPU model based on QEMU. The architecture is validated through functional emulation on three base architectures (x86_64, ARM64, and RISC-V), and timing-accurate FPGA-based simulations. This allows for a realistic evaluation of hybrid system performance and quantum advantage scenarios. Our work lays the ground for a system-level co-design methodology tailored for the next generation of quantum-classical computing.</abstract>
    <identifier type="doi">10.48550/arXiv.2507.19212</identifier>
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    <author>Ralf Ramsauer</author>
    <author>Wolfgang Mauerer</author>
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    <title language="eng">Towards Real-World System-Level Integration of Quantum Accelerators: A Hardware/Software Co-Design Approach</title>
    <abstract language="eng">This work-in-progress explores architectural and systemic foundations for integrating quantum accelerators into heterogeneous computing environments. We propose and implement a modular architecture where Quantum Processing Units (QPUs) operate as peripheral devices, supporting pulse-level control interfaces and high-level circuit execution offloading, while internally managing compilation, transpilation, and scheduling. To enable efficient quantum-classical orchestration, we introduce a Quantum Abstraction Layer (QAL) at the operating system level to enable seamless communication, resource management, and integration with existing software frameworks. Our two-step design approach begins with validating the architecture through simulations in virtualised environments. We then implement an FPGA-based surrogate supporting both result- and timing-accurate modes, enabling full-stack emulation and performance evaluation in the absence of physical quantum hardware. This platform supports extensible and rapid prototyping, Hardware/Software Co-Design, and allows for investigations on the practical quantum advantage under realistic system-level constraints of various use cases. We aim for applicability by hardware vendors, facilitating early development even before physical quantum processors are available.</abstract>
    <parentTitle language="eng">INFORMATIK; Lecture Notes in Informatics (LNI);  GI Quantum Computing Workshop. Potsdam. 16.–19. September 2025</parentTitle>
    <identifier type="doi">10.18420/inf2025_158</identifier>
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    <author>Ralf Ramsauer</author>
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    <title language="deu">It's Quick to be Square: Fast Quadratisation for Quantum Toolchains</title>
    <abstract language="deu">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, i.e. 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.</abstract>
    <identifier type="arxiv">2411.19934</identifier>
    <note>Der Aufsatz wurde peer-reviewed veröffentlicht und ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/9006</note>
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    <licence>Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell -  Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Lukas Schmidbauer</author>
    <author>Elisabeth Lobe</author>
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    <author>Wolfgang Mauerer</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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    <title language="eng">Oops!... I did it again. Conclusion (In-)Stability in Quantitative Empirical Software Engineering: A Large-Scale Analysis</title>
    <abstract language="eng">Context: Mining software repositories is a popular means to gain insights into a software project's evolution, monitor project health, support decisions and derive best practices. Tools supporting the mining process are commonly applied by researchers and practitioners, but their limitations and agreement are often not well understood.&#13;
Objective: This study investigates some threats to validity in complex tool pipelines for evolutionary software analyses and evaluates the tools' agreement in terms of data, study outcomes and conclusions for the same research questions.&#13;
Method: We conduct a lightweight literature review to select three studies on collaboration and coordination, software maintenance and software quality from high-ranked venues, which we formally replicate with four independent, systematically selected mining tools to quantitatively and qualitatively compare the extracted data, analysis results and conclusions.&#13;
Results: We find that numerous technical details in tool design and implementation accumulate along the complex mining pipelines and can cause substantial differences in the extracted baseline data, its derivatives, subsequent results of statistical analyses and, under specific circumstances, conclusions.&#13;
Conclusions: Users must carefully choose tools and evaluate their limitations to assess the scope of validity in an adequate way. Reusing tools is recommended. Researchers and tool authors can promote reusability and help reducing uncertainties by reproduction packages and comparative studies following our approach.</abstract>
    <identifier type="doi">10.48550/arXiv.2510.06844</identifier>
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    <author>Nicole Höß</author>
    <author>Carlos Paradis</author>
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    <title language="eng">TWiDDle: Twirling and Dynamical Decoupling, and Crosstalk Noise Modeling</title>
    <abstract language="eng">Crosstalk remains a major source of correlated error in quantum systems, yet lacks a precise, community-wide definition - hindering systematic analysis and mitigation. This paper introduces a model-driven approach to crosstalk characterisation through three architecture-inspired noise models: (1) simultaneous two-qubit gate execution, (2) shared qubit interference, and (3) proximity-induced noise from shared control or readout hardware. These models act as both diagnostic tools and building blocks for crosstalk-aware quantum programming. We assess their impact across a broad benchmark suite - quantum simulation, Grover's algorithm, and fault-tolerant primitives like surface, Shor, and Steane codes - and evaluate two mitigation techniques: dynamical decoupling and Pauli twirling. While both are discussed in literature, only dynamical decoupling consistently enhances fidelity across noise types. Our work links low-level noise effects to high-level software engineering, underscoring the role of hardware-software co-design in scalable quantum computing. Model-based, hardware-aware design flows and composable noise abstractions improve error mitigation and program portability. Integrating such strategies into the toolchain is essential for building resilient quantum programs under realistic noise conditions.</abstract>
    <parentTitle language="deu">2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque</parentTitle>
    <identifier type="doi">10.1109/QCE65121.2025.10313</identifier>
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    <author>Hila Safi</author>
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