@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} } @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} } @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} } @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{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} } @unpublished{RamsauerMauerer, author = {Ramsauer, Ralf and Mauerer, Wolfgang}, title = {Towards System-Level Quantum-Accelerator Integration}, doi = {10.48550/arXiv.2507.19212}, pages = {6}, abstract = {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. 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. 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.}, language = {en} } @inproceedings{RamsauerBielmeierMauerer, author = {Ramsauer, Ralf and Bielmeier, Benno and Mauerer, Wolfgang}, title = {Towards Real-World System-Level Integration of Quantum Accelerators: A Hardware/Software Co-Design Approach}, series = {INFORMATIK; Lecture Notes in Informatics (LNI); GI Quantum Computing Workshop. Potsdam. 16.-19. September 2025}, booktitle = {INFORMATIK; Lecture Notes in Informatics (LNI); GI Quantum Computing Workshop. Potsdam. 16.-19. September 2025}, publisher = {Gesellschaft f{\"u}r Informatik e.V.}, doi = {10.18420/inf2025_158}, pages = {1761 -- 1765}, abstract = {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.}, language = {en} } @inproceedings{SafiNiedermeierMauerer, author = {Safi, Hila and Niedermeier, Christoph and Mauerer, Wolfgang}, title = {TWiDDle: Twirling and Dynamical Decoupling, and Crosstalk Noise Modeling}, series = {2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque}, booktitle = {2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque}, publisher = {IEEE}, doi = {10.1109/QCE65121.2025.10313}, pages = {162 -- 168}, abstract = {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.}, language = {en} } @unpublished{PeriyasamyUfrechtSchereretal., author = {Periyasamy, Maniraman and Ufrecht, Christian and Scherer, Daniel D. D. and Mauerer, Wolfgang}, title = {CutReg: A loss regularizer for enhancing the scalability of QML via adaptive circuit cutting}, doi = {10.48550/arXiv.2506.14858}, pages = {4}, abstract = {Whether QML can offer a transformative advantage remains an open question. The severe constraints of NISQ hardware, particularly in circuit depth and connectivity, hinder both the validation of quantum advantage and the empirical investigation of major obstacles like barren plateaus. Circuit cutting techniques have emerged as a strategy to execute larger quantum circuits on smaller, less connected hardware by dividing them into subcircuits. However, this partitioning increases the number of samples needed to estimate the expectation value accurately through classical post-processing compared to estimating it directly from the full circuit. This work introduces a novel regularization term into the QML optimization process, directly penalizing the overhead associated with sampling. We demonstrate that this approach enables the optimizer to balance the advantages of gate cutting against the optimization of the typical ML cost function. Specifically, it navigates the trade-off between minimizing the cutting overhead and maintaining the overall accuracy of the QML model, paving the way to study larger complex problems in pursuit of quantum advantage}, language = {en} } @article{StroblFranzKuehnetal., author = {Strobl, Melvin and Franz, Maja and K{\"u}hn, Eileen and Mauerer, Wolfgang and Streit, Achim}, title = {QML-Essentials: A Framework for Working with Quantum Fourier Models}, series = {Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki}, journal = {Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki}, publisher = {IEEE}, doi = {10.1109/QSW67625.2025.00035}, pages = {238 -- 243}, abstract = {In this work, we propose a framework in the form of a Python package, specifically designed for the analysis of Quantum Machine Learning models. This framework is based on the PennyLane simulator and facilitates the evaluation and training of Variational Quantum Circuits. It provides additional functionality ranging from the ability to add different types of noise to the classical simulation, over different parameter initialisation strategies, to the calculation of expressibility and entanglement for a given model. As an intrinsic property of Quantum Fourier Models, it provides two methods for calculating the corresponding Fourier spectrum: one via the Fast Fourier Transform and another analytical method based on the expansion of the expectation value using trigonometric polynomials. It also provides a set of predefined approaches that allow a fast and straightforward implementation of Quantum Machine Learning models. With this framework, we extend the PennyLane simulator with a set of tools that allow researchers a more convenient start with Quantum Fourier Models and aim to unify the analysis of Variational Quantum Circuits.}, language = {en} } @article{MaschekSchwittallaFranzetal., author = {Maschek, Stefan Raimund and Schwittalla, J{\"u}rgen and Franz, Maja and Mauerer, Wolfgang}, title = {Make Some Noise! Measuring Noise Model Quality in Real-World Quantum Software}, series = {Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki}, journal = {Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki}, publisher = {IEEE}, doi = {10.1109/QSW67625.2025.00010}, pages = {11}, abstract = {Noise and imperfections are among the prevalent challenges in quantum software engineering for current NISQ systems. They will remain important in the post-NISQ area, as logical, error-corrected qubits will be based on software mechanisms. As real quantum hardware is still limited in size and accessibility, noise models for classical simulation-that in some cases can exceed dimensions of actual systems-play a critical role in obtaining insights into quantum algorithm performance, and the properties of mechanisms for error correction and mitigation. We present, implement and validate a tunable noise model building on the Kraus channel formalism on a large scale quantum simulator system (Qaptiva). We use empirical noise measurements from IBM quantum (IBMQ) systems to calibrate the model and create a realistic simulation environment. Experimental evaluation of our approach with Greenberger-Horne-Zeilinger (GHZ) state preparation and QAOA applied to an industrial usecase validate our approach, and demonstrate accurate simulation of hardware behaviour at reasonable computational cost. We devise and utilise a method that allows for determining the quality of noise models for larger problem instances than is possible with existing metrics in the literature. To identify potentials of future quantum software and algorithms, we extrapolate the noise model to future partially fault-tolerant systems, and give insights into the interplay between hardware-specific noise modelling and hardware-aware algorithm development.}, language = {en} } @unpublished{FranzStroblChaichenetsetal., author = {Franz, Maja and Strobl, Melvin and Chaichenets, Leonid and K{\"u}hn, Eileen and Streit, Achim and Mauerer, Wolfgang}, title = {Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models}, doi = {10.48550/arXiv.2506.09527}, pages = {32}, abstract = {Variational quantum algorithms have received substantial theoretical and empirical attention. As the underlying variational quantum circuit (VQC) can be represented by Fourier series that contain an exponentially large spectrum in the number of input features, hope for quantum advantage remains. Nevertheless, it remains an open problem if and how quantum Fourier models (QFMs) can concretely outperform classical alternatives, as the eventual sources of non-classical computational power (for instance, the role of entanglement) are far from being fully understood. Likewise, hardware noise continues to pose a challenge that will persist also along the path towards fault tolerant quantum computers. In this work, we study VQCs with Fourier lenses, which provides possibilities to improve their understanding, while also illuminating and quantifying constraints and challenges. We seek to elucidate critical characteristics of QFMs under the influence of noise. Specifically, we undertake a systematic investigation into the impact of noise on the Fourier spectrum, expressibility, and entangling capability of QFMs through extensive numerical simulations and link these properties to training performance. The insights may inform more efficient utilisation of quantum hardware and support the design of tailored error mitigation and correction strategies. Decoherence imparts an expected and broad detrimental influence across all Ans{\"a}tze. Nonetheless, we observe that the severity of these deleterious effects varies among different model architectures, suggesting that certain configurations may exhibit enhanced robustness to noise and show computational utility.}, language = {en} } @article{FranzSchoenbergerStrobletal., author = {Franz, Maja and Sch{\"o}nberger, Manuel and Strobl, Melvin and K{\"u}hn, Eileen and Streit, Achim and Zurita, P{\´i}a and Diefenthaler, Markus and Mauerer, Wolfgang}, title = {From Hope to Heuristic: Realistic Runtime Estimates for Quantum Optimisation in NHEP}, series = {EPJ Web of Conferences; 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)}, volume = {337}, journal = {EPJ Web of Conferences; 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)}, publisher = {EDP Sciences}, doi = {10.1051/epjconf/202533701282}, pages = {8}, abstract = {Noisy Intermediate-Scale Quantum (NISQ) computers, despite their limitations, present opportunities for near-term quantum advantages in Nuclear and High-Energy Physics (NHEP) when paired with specially designed quantum algorithms and processing units. This study focuses on core algorithms that solve optimization problems through the quadratic Ising or Quadratic Unconstrained Binary Optimisation model, specifically Quantum Annealing and the Quantum Approximate Optimisation Algorithm (QAOA). In particular, we estimate runtimes and scalability for the task of particle Track Reconstruction (TR), a key computing challenge in NHEP, and investigate how the classical parameter space in QAOA, along with techniques like a Fourieranalysis based heuristic, can facilitate future quantum advantages. The findings indicate that lower frequency components in the parameter space are crucial for effective annealing schedules, suggesting that heuristics can improve resource efficiency while achieving near-optimal results. Overall, the study highlights the potential of NISQ computers in NHEP and the significance of co-design approaches and heuristic techniques in overcoming challenges in quantum algorithms.}, language = {en} } @inproceedings{SchmidbauerMauerer, author = {Schmidbauer, Lukas and Mauerer, Wolfgang}, title = {SAT Strikes Back: Parameter and Path Relations in Quantum Toolchains}, series = {Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki}, booktitle = {Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki}, publisher = {IEEE}, doi = {10.1109/QSW67625.2025.00021}, pages = {104 -- 115}, 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{KruegerMauerer, author = {Kr{\"u}ger, Tom and Mauerer, Wolfgang}, title = {Quantum Dark Magic: Efficiency of Intermediate Non-Stabiliserness}, series = {2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August- 05 September 2025, Albuquerque}, booktitle = {2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August- 05 September 2025, Albuquerque}, publisher = {IEEE}, doi = {10.1109/QCE65121.2025.10461}, pages = {592 -- 593}, abstract = {While quantum systems are know to possess inherent computational advantages over classical computers, constructing algorithms that harness such advantage remains an open challenge. Non-stabiliserness (i.e., traversal of states outside the Clifford orbit), is a necessary condition, as de-quantisation is otherwise possible. Nevertheless, an excess of non-stabiliserness is also known to not be advantageous. In this paper, we present an approach to understanding the efficient use of non-stabiliser states by tracking their behaviour across various algorithms. Our techniques reveal different efficiencies in the use of non-stabiliserness, leading us to hypothesise that greater classical optimisation degrees of freedom can introduce unnecessary non-stabiliser consumption, which becomes costly with error correction.}, language = {en} } @inproceedings{SchmidbauerRiofrioHeinrichetal., author = {Schmidbauer, Lukas and Riofr{\´i}o, Carlos A. and Heinrich, Florian and Junk, Vanessa and Schwenk, Ulrich and Husslein, Thomas and Mauerer, Wolfgang}, title = {Path Matters: Industrial Data Meet Quantum Optimization}, series = {2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque}, booktitle = {2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque}, publisher = {IEEE}, doi = {10.1109/QCE65121.2025.00230}, pages = {2101 -- 2111}, abstract = {Real-world optimization problems must undergo a series of transformations before becoming solvable on current quantum hardware. Even for a fixed problem, the number of possible transformation paths-from industry-relevant formulations through binary constrained linear programs (BILPs), to quadratic unconstrained binary optimization (QUBO), and finally to a hardware-executable representation-is remarkably large. Each step introduces free parameters, such as Lagrange multipliers, encoding strategies, slack variables, rounding schemes or algorithmic choices-making brute-force exploration of all paths intractable. In this work, we benchmark a representative subset of these transformation paths using a realworld industrial production planning problem with industry data: the optimization of work allocation in a press shop producing vehicle parts. We focus on QUBO reformulations and algorithmic parameters for both quantum annealing (QA) and the Linear Ramp Quantum Approximate Optimization Algorithm (LR-QAOA). Our goal is to identify a reduced set of effective configurations applicable to similar industrial settings. Our results show that QA on D-Wave hardware consistently produces near-optimal solutions, whereas LR-QAOA on IBM quantum devices struggles to reach comparable performance. Hence, the choice of hardware and solver strategy significantly impacts performance. The problem formulation and especially the penalization strategy determine the solution quality. Most importantly, mathematically-defined penalization strategies are equally successful as hand-picked penalty factors, paving the way for automated QUBO formulation. Moreover, we observe a strong correlation between simulated and quantum annealing performance metrics, offering a scalable proxy for predicting QA behavior on larger problem instances.}, language = {en} } @inproceedings{BielmeierRamsauerYoshidaetal., author = {Bielmeier, Benno and Ramsauer, Ralf and Yoshida, Takahiro and Mauerer, Wolfgang}, title = {From Tracepoints to Timeliness: a Semi-Markov Framework for Predictive Runtime Analysis}, series = {IEEE 31th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), 20-22 August 2025, Singapore}, booktitle = {IEEE 31th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), 20-22 August 2025, Singapore}, publisher = {IEEE}, doi = {10.1109/RTCSA66114.2025.00021}, pages = {114 -- 125}, abstract = {Detecting and resolving violations of temporal constraints in real-time systems is both, time-consuming and resource-intensive, particularly in complex software environments. Measurement-based approaches are widely used during development, but often are unable to deliver reliable predictions with limited data. This paper presents a hybrid method for worst-case execution time estimation, combining lightweight runtime tracing with probabilistic modelling. Timestamped system events are used to construct a semi-Markov chain, where transitions represent empirically observed timing between events. Execution duration is interpreted as time-to-absorption in the semi-Markov chain, enabling worst-case execution time estimation with fewer assumptions and reduced overhead. Empirical results from real-time Linux systems indicate that the method captures both regular and extreme timing behaviours accurately, even from short observation periods. The model supports holistic, low-intrusion analysis across system layers and remains interpretable and adaptable for practical use.}, language = {en} }