@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} } @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{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} } @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{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} } @inproceedings{ThelenMauerer, author = {Thelen, Simon and Mauerer, Wolfgang}, title = {Predict and Conquer: Navigating Algorithm Trade-Offs with Quantum Design Automation}, 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}, address = {Los Alamitos, USA}, doi = {10.1109/QCE65121.2025.00071}, pages = {591 -- 602}, abstract = {Combining quantum computers with classical compute power has become a standard means for developing algorithms and heuristics that are, eventually, supposed to beat any purely classical alternatives. While in-principle advantages for solution quality or runtime are expected for increasingly many approaches, substantial challenges remain: Non-functional properties like runtime or solution quality of many suggested approaches are not yet fully understood, and need to be explored empirically. This, in turn, makes it unclear which approach is best suited for a given problem. Accurately predicting behaviour and properties of quantum-classical algorithms opens possibilities for software abstraction layers, which in turn can automate decisionmaking for algorithm selection and parametrisation. While such techniques find frequent use in classical high-performance computing, they are still mostly absent from quantum software toolchains. In this paper, we present a methodology (accompanied by a reproducible reference implementation) to perform algorithm selection based on desirable non-functional requirements. This greatly simplifies decision-making processes for end users. Based on meta-information annotations at the source code level, our framework traces key characteristics of quantum-classical heuristics and algorithms, and uses this information to predict the most suitable approach and its parameters for given computational challenges and their non-functional requirements. As combinatorial optimisation is a very extensively studied aspect of quantumclassical systems, we perform a comprehensive case study based on numerical simulations of algorithmic approaches to implement and validate our ideas. We develop statistical models to quantify the influence of various factors on non-functional properties, and establish predictions for optimal algorithmic choices without manual user effort. We argue that our methodology generalises to problem classes beyond combinatorial optimisation, such as Hamiltonian optimisation, and lays a foundation for integrated software layers for quantum design automation.}, 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{GutbrodRauberPalm, author = {Gutbrod, Max and Rauber, David and Palm, Christoph}, title = {Improving Generalization in Mitotic Cell Detection via Domain Transformations}, series = {Bildverarbeitung f{\"u}r die Medizin 2025: Proceedings, German Conference on Medical Image Computing, L{\"u}beck March 15-17, 2026}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2025: Proceedings, German Conference on Medical Image Computing, L{\"u}beck March 15-17, 2026}, editor = {Handels, Heinz and Breininger, Katharina and Deserno, Thomas M. and Maier, Andreas and Maier-Hein, Klaus H. and Palm, Christoph and Tolxdorff, Thomas}, publisher = {Springer Vieweg}, address = {Wiesbaden}, doi = {10.1007/978-3-658-51100-5_71}, pages = {362 -- 367}, abstract = {We address domain generalization (DG) in mitotic-cell (MC) detection by combining a β-variational autoencoder (VAE) for domain transformations with feature-space alignment together with an object detector. The β-VAE synthesizes domain-transformed images, and the detector is trained to map originals and their transformed counterparts to equal representations. On the MIDOG++ dataset, this approach improves out-of-domain detection F1 scores by 7 and 3 percentage points compared to the color-variation augmentation and stain-normalization baselines. Results further suggest that morphology shifts hinder generalization more than stain shifts.}, subject = {K{\"u}nstliche Intelligenz}, language = {en} } @inproceedings{WeinzierlSchulz, author = {Weinzierl, Stefan and Schulz, Carsten}, title = {Digitaler Zwilling einer Doppelschlag-Verlitzmaschine : Digital twin of a double twist stranding machine}, series = {5. VDI-Fachtagung Schwingungen 2025}, booktitle = {5. VDI-Fachtagung Schwingungen 2025}, publisher = {VDI Verlag}, isbn = {9783181024638}, doi = {10.51202/9783181024638-271}, pages = {271 -- 288}, abstract = {Die Methode der Mehrk{\"o}rpersimulation und die Finite-Elemente-Methode gewinnen aufgrund immer leistungsf{\"a}higerer Rechentechnik in Forschung und Entwicklung zunehmend an Bedeutung. Heutzutage k{\"o}nnen komplexe Systeme mit diesen Methoden virtuell simuliert und multiphysikalisch untersucht werden. Insbesondere im Entwicklungsprozess f{\"u}hrt deren Einsatz aufgrund der damit verbundenen Zeit- und Kosteneinsparungen zu einem entscheidenden Wettbewerbsvorteil. Im Rahmen dieser Arbeit wird ein digitaler Zwilling einer bestehenden Doppelschlag-Verlitzmaschine erstellt. Ziel ist die virtuelle Durchf{\"u}hrung von Untersuchungen und Schwingungsanalysen. Die wichtigsten Komponenten werden mit flexiblen Eigenschaften unter der Verwendung der Finite-Elemente-Methode integriert, um die Schwingungsf{\"a}higkeit des Systems zu simulieren. Um die Effizienz der Simulation zu erh{\"o}hen, werden die flexiblen K{\"o}rper auf ein modales Ersatzmodell reduziert. Dar{\"u}ber hinaus wird die Nachgiebigkeit der Lagerpunkte durch Streifigkeitsmatrizen abgebildet und analysiert. F{\"u}r die Untersuchung des Hochlaufs und des Dauerbetriebes mit unterschiedlichen Maschinenkonfigurationen wurde ein Auswerteverfahren entwickelt, das die Reproduzierbarkeit und den Vergleich zwischen den einzelnen Tests erm{\"o}glicht. Abschließend erfolgt durch den Abgleich mit realen Messungen die Validierung des digitalen Zwillings, wodurch dessen Qualit{\"a}t gesichert und die Vergleichbarkeit zur realen Maschine gew{\"a}hrleistet wird.}, language = {de} }