@article{VuLitzelKoch2026, author = {Vu, Thi Huong and Litzel, Ida and Koch, Thorsten}, title = {Similarity-based fuzzy clustering scientific articles: potentials and challenges from mathematical and computational perspectives}, volume = {10}, journal = {Journal of Nonlinear and Variational Analysis}, number = {2}, publisher = {Biemdas}, arxiv = {http://arxiv.org/abs/2506.04045}, doi = {https://doi.org/10.23952/jnva.10.2026.2.8}, pages = {381 -- 401}, year = {2026}, abstract = {Fuzzy clustering, which allows an article to belong to multiple clusters with soft membership degrees, plays a vital role in analyzing publication data. This problem can be formulated as a constrained optimization model, where the goal is to minimize the discrepancy between the similarity observed from data and the similarity derived from a predicted distribution. While this approach benefits from leveraging state-of-the-art optimization algorithms, tailoring them to work with real, massive databases like OpenAlex or Web of Science - containing about 70 million articles and a billion citations - poses significant challenges. We analyze potentials and challenges of the approach from both mathematical and computational perspectives. Among other things, second-order optimality conditions are established, providing new theoretical insights, and practical solution methods are proposed by exploiting the structure of the problem. Specifically, we accelerate the gradient projection method using GPU-based parallel computing to efficiently handle large-scale data.}, language = {en} } @article{HartmannJoesterSchuetteetal.2026, author = {Hartmann, Carsten and J{\"o}ster, Annika and Sch{\"u}tte, Christof and Sikorski, Alexander and Weber, Marcus}, title = {Importance sampling of unbounded random stopping times: computing committor functions and exit rates without reweighting}, arxiv = {http://arxiv.org/abs/2601.01489}, year = {2026}, abstract = {Rare events in molecular dynamics are often related to noise-induced transitions between different macroscopic states (e.g., in protein folding). A common feature of these rare transitions is that they happen on timescales that are on average exponentially long compared to the characteristic timescale of the system, with waiting time distributions that have (sub)exponential tails and infinite support. As a result, sampling such rare events can lead to trajectories that can be become arbitrarily long, with not too low probability, which makes the reweighting of such trajectories a real challenge. Here, we discuss rare event simulation by importance sampling from a variational perspective, with a focus on applications in molecular dynamics, in particular the computation of committor functions. The idea is to design importance sampling schemes that (a) reduce the variance of a rare event estimator while controlling the average length of the trajectories and (b) that do not require the reweighting of possibly very long trajectories. In doing so, we study different stochastic control formulations for committor and mean first exit times, which we compare both from a theoretical and a computational point of view, including numerical studies of some benchmark examples.}, language = {en} } @article{DietrichvonTycowiczBrandletal.2026, author = {Dietrich, Laura and von Tycowicz, Christoph and Brandl, Michael and Mayer, Julius and Baunack, Lohengrin and Schmidt, Iris}, title = {Project WEAR: Developing a methodological framework for functional analysis on stone tools through controlled experiments and computational modelling of shape transformations through use}, journal = {Antiquity}, year = {2026}, abstract = {The WEAR project is developing an integrative methodology to analyse and predict use-related shape transformation of Neolithic stone axes from Central Europe with mathematical methods and experimental archaeology.}, language = {en} } @article{AbouHamdanJanaColometal.2026, author = {Abou Hamdan, Loubnan and Jana, Aloke and Colom, R{\´e}mi and Aboujoussef, Nour and Carlson, Cooper and Overvig, Adam and Binkowski, Felix and Burger, Sven and Genevet, Patrice}, title = {A Complex-Frequency Framework for Kerker Unidirectionality in Photonic Resonators}, doi = {10.21203/rs.3.rs-8444305/v1}, year = {2026}, language = {en} } @article{CarusoSentefAttaccaliteetal.2026, author = {Caruso, Fabio and Sentef, Michael and Attaccalite, Claudio and Bonitz, Michael and Draxl, Claudia and De Giovannini, Umberto and Eckstein, Martin and Ernstorfer, Ralph and Fechner, Michael and Gr{\"u}ning, Myrta and H{\"u}bener, Hannes and Joost, Jan-Philip and Juraschek, Dominik and Karrasch, Christoph and Marvin Kennes, Dante and Latini, Simone and Lu, I-Te and Neufeld, Ofer and Perfetto, Enrico and Rettig, Laurenz and Rodrigues Pel{\´a}, Ronaldo and Rubio, Angel and Rudzinski, Joseph and Ruggenthaler, Michael and Sangalli, Davide and Sch{\"u}ler, Michael and Shallcross, Samuel and Sharma, Sangeeta and Stefanucci, Gianluca and Werner, Philipp}, title = {The 2025 Roadmap to Ultrafast Dynamics: Frontiers of Theoretical and Computational Modelling}, volume = {9}, journal = {J. Phys. Mater.}, number = {1}, arxiv = {http://arxiv.org/abs/2501.06752}, doi = {10.1088/2515-7639/ae1165}, year = {2026}, language = {en} } @inproceedings{YousefianDonatiSikorskietal.2026, author = {Yousefian, Maryam and Donati, Luca and Sikorski, Alexander and Weber, Marcus and R{\"o}blitz, Susanna}, title = {Exploring Metastable Dynamics of Gene Regulatory Networks with ISOKANN}, volume = {15959}, booktitle = {Computational Methods in Systems Biology. CMSB 2025}, doi = {10.1007/978-3-032-01436-8_8}, pages = {126 -- 149}, year = {2026}, abstract = {Stochastic dynamical systems like gene regulatory networks (GRNs) often exhibit behavior characterized by metastable sets (representing cellular phenotypes), in which trajectories remain for long times, whereas switches between these sets in the phase space are rare events. One way to capture these rare events is to infer the system's long-term behavior from the spectral characteristics (eigenvalues and eigenvectors) of its Koopman operator. For GRNs, the Koopman operator is based on the chemical master equation (CME), which provides a precise mathematical modeling framework for stochastic GRNs. Since the CME is typically analytically intractable, methods based on discretizing the CME operator have been developed. However, determining the number and location of metastable sets in the phase space as well as the transition rates between them remains computationally challenging, especially for large GRNs with many genes and interactions. A promising alternative method, called ISOKANN (invariant subspaces of Koopman operators with artificial neural networks) has been developed in the context of molecular dynamics. ISOKANN uses a combination of the power iteration and neural networks to learn the basis functions of an invariant subspace of the Koopman operator. In this paper, we extend the application of ISOKANN to the CME operator and apply it to two small GRNs: a genetic toggle switch model and a model for macrophage polarization. Our work opens a new field of application for the ISOKANN algorithm and demonstrates the potential of this algorithm for studying large GRNs.}, language = {en} } @article{WidlerKaminskaMartinsetal.2026, author = {Widler, Valeria and Kaminska, Barbara and Martins, Andre C. R. and Puga-Gonzalez, Ivan}, title = {An Investigation into the Causal Mechanism of Political Opinion Dynamics: A Model of Hierarchical Coarse-Graining with Community-Bounded Social Influence}, journal = {Computational Social Science of Social Cohesion and Polarization}, edition = {Computational Social Science of Social Cohesion and Polarization}, publisher = {Springer, Cham.}, arxiv = {http://arxiv.org/abs/2504.00877}, doi = {10.1007/978-3-032-01373-6_10}, pages = {225 -- 256}, year = {2026}, abstract = {The increasing polarization in democratic societies is an emergent outcome of political opinion dynamics. Yet, the fundamental mechanisms behind the formation of political opinions, from individual beliefs to collective consensus, remain unknown. Understanding that a causal mechanism must account for both bottom-up and top-down influences, we conceptualize political opinion dynamics as hierarchical coarse-graining, where microscale opinions integrate into a macro-scale state variable. Using the CODA (Continuous Opinions Discrete Actions) model, we simulate Bayesian opinion updating, social identity-based information integration, and migration between social identity groups to represent higher-level connectivity. This results in coarse-graining across micro, meso, and macro levels. Our findings show that higher-level connectivity shapes information integration, yielding three regimes: independent (disconnected, local convergence), parallel (fast, global convergence), and iterative (slow, stepwise convergence). In the iterative regime, low connectivity fosters transient diversity, indicating an informed consensus. In all regimes, time-scale separation leads to downward causation, where agents converge on the aggregate majority choice, driving consensus. Critically, any degree of coherent higher-level information integration can overcome misalignment via global downward causation. The results highlight how emergent properties of the causal mechanism, such as downward causation, are essential for consensus and may inform more precise investigations into polarized political discourse.}, language = {en} } @misc{FrankeSeeligerStomporetal.2026, author = {Franke, Fabian and Seeliger, Frank and Stompor, Tomasz and Wawra, Steffen}, title = {K{\"u}nstliche Intelligenz in Bibliotheken}, volume = {13}, journal = {o-bib. Das offene Bibliotheksjournal}, number = {1}, issn = {2363-9814}, doi = {https://doi.org/10.5282/o-bib/6231}, pages = {1 -- 6}, year = {2026}, abstract = {Der Bibliotheksverbund Bayern und der Kooperative Bibliotheksverbund Berlin-Brandenburg haben in einem gemeinsamen Ideenworkshop im Mai 2025 Potenziale, Herausforderungen, Projekteans{\"a}tze und Handlungsbedarfe bei Anwendung K{\"u}nstlicher Intelligenz in Bibliotheken analysiert und diskutiert. F{\"u}r die Handlungsfelder Interne Gesch{\"a}ftsg{\"a}nge, Bibliotheksdienste, Forschungsnahe Dienste, Informationskompetenz und Analyse von Nutzungsdaten wurden Bedarfe identifiziert, Projektideen entwickelt und Handlungsempfehlungen formuliert.}, language = {de} } @article{RongChenKochetal.2026, author = {Rong, Guoyang and Chen, Ying and Koch, Thorsten and Honda, Keisuke}, title = {Assessing data quality in citation analysis: A case study of web of science and Crossref}, volume = {20}, journal = {Journal of Informetrics}, number = {1}, publisher = {Elsevier BV}, issn = {1751-1577}, doi = {10.1016/j.joi.2026.101775}, year = {2026}, language = {en} } @article{GonnermannMuellerHaaseLeinsetal.2026, author = {Gonnermann-M{\"u}ller, Jana and Haase, Jennifer and Leins, Nicolas and Igel, Moritz and Fackeldey, Konstantin and Pokutta, Sebastian}, title = {FACET: Multi-Agent AI Supporting Teachers in Scaling Differentiated Learning for Diverse Students}, journal = {arXiv}, arxiv = {http://arxiv.org/abs/2601.22788}, doi = {https://arxiv.org/abs/2601.22788}, year = {2026}, abstract = {Classrooms are becoming increasingly heterogeneous, comprising learners with diverse performance and motivation levels, language proficiencies, and learning differences such as dyslexia and ADHD. While teachers recognize the need for differentiated instruction, growing workloads create substantial barriers, making differentiated instruction an ideal that is often unrealized in practice. Current AI educational tools, which promise differentiated materials, are predominantly student-facing and performance-centric, ignoring other aspects that shape learning outcomes. We introduce FACET, a teacher-facing multi-agent framework designed to address these gaps by supporting differentiation that accounts for motivation, performance, and learning differences. Developed with educational stakeholders from the outset, the framework coordinates four specialized agents, including learner simulation, diagnostic assessment, material generation, and evaluation within a teacher-in-the-loop design. School principals (N = 30) shaped system requirements through participatory workshops, while in-service K-12 teachers (N = 70) evaluated material quality. Mixed-methods evaluation demonstrates strong perceived value for inclusive differentiation. Practitioners emphasized both the urgent need arising from classroom heterogeneity and the importance of maintaining pedagogical autonomy as a prerequisite for adoption. We discuss implications for future school deployment and outline partnerships for longitudinal classroom implementation.}, language = {en} } @article{AndresArconesWeiserKoutsourelakisetal.2026, author = {Andr{\´e}s Arcones, Daniel and Weiser, Martin and Koutsourelakis, Phaedon-Stelios and Unger, J{\"o}rg F.}, title = {Embedded Model Form Uncertainty Quantification with Measurement Noise for Bayesian Model Calibration}, volume = {7}, journal = {Data-Centric Engineering}, arxiv = {http://arxiv.org/abs/2410.12037}, doi = {10.1017/dce.2025.10035}, year = {2026}, abstract = {A key factor in ensuring the accuracy of computer simulations that model physical systems is the proper calibration of their parameters based on real-world observations or experimental data. Inevitably, uncertainties arise, and Bayesian methods provide a robust framework for quantifying and propagating these uncertainties to model predictions. Nevertheless, Bayesian methods paired with inexact models usually produce predictions unable to represent the observed datapoints. Additionally, the quantified uncertainties of these overconfident models cannot be propagated to other Quantities of Interest (QoIs) reliably. A promising solution involves embedding a model inadequacy term in the inference parameters, allowing the quantified model form uncertainty to influence non-observed QoIs. This paper introduces a more interpretable framework for embedding the model inadequacy compared to existing methods. To overcome the limitations of current approaches, we adapt the existing likelihood models to properly account for noise in the measurements and propose two new formulations designed to address their shortcomings. Moreover, we evaluate the performance of this inadequacy-embedding approach in the presence of discrepancies between measurements and model predictions, including noise and outliers. Particular attention is given to how the uncertainty associated with the model inadequacy term propagates to the QoIs, enabling a more comprehensive statistical analysis of prediction's reliability. Finally, the proposed approach is applied to estimate the uncertainty in the predicted heat flux from a transient thermal simulation using temperature bservations.}, language = {en} } @misc{VanaretLeyffer2026, author = {Vanaret, Charlie and Leyffer, Sven}, title = {Implementing a unified solver for nonlinearly constrained optimization}, arxiv = {http://arxiv.org/abs/2406.13454}, year = {2026}, abstract = {SQP and interior-point methods (also referred to as Lagrange-Newton methods) typically share key algorithmic components, such as strategies for computing descent directions and mechanisms that promote global convergence. Building on this insight, we introduce a unifying framework with eight building blocks that abstracts the workflows of Lagrange-Newton methods. We then present Uno, a modular C++ solver that implements our unifying framework and allows the automatic combination of a wide range of strategies with no programming effort from the user. Uno is meant to (1) organize mathematical optimization strategies into a coherent hierarchy; (2) offer a wide range of efficient and robust methods that can be compared for a given instance; (3) enable researchers to experiment with novel optimization strategies; and (4) reduce the cost of development and maintenance of multiple optimization solvers. Uno's software design allows user to compose new customized solvers for emerging optimization areas such as robust optimization or optimization problems with complementarity constraints, while building on reliable nonlinear optimization techniques. We demonstrate that Uno is highly competitive against state-of-the-art solvers filterSQP, IPOPT, SNOPT, MINOS, LANCELOT, LOQO, and CONOPT on a subset of 429 small problems from the CUTE collection. Uno is available as open-source software under the MIT license at this https URL and via its C, Julia, Python, Fortran, and AMPL interfaces.}, language = {en} } @article{MehrmannJohnyEbbinghausetal.2026, author = {Mehrmann, Carolin and Johny, Jacob and Ebbinghaus, Petra and Hammerschmidt, Martin and Das, Ankita and Wei, Xin and Tesch, Marc F. and Rabe, Martin}, title = {Nano IR spectroscopy on Silicon-Supported Organic-Inorganic Hybrid Materials}, journal = {Phys. Chem. Chem. Phys.}, publisher = {Royal Society of Chemistry (RSC)}, doi = {10.1039/D5CP03815D}, year = {2026}, language = {en} } @inproceedings{PedersenLindnerRehfeldtetal.2026, author = {Pedersen, Jaap and Lindner, Niels and Rehfeldt, Daniel and Koch, Thorsten}, title = {Comparing Branching Rules for the Quota Steiner Tree Problem with Interference}, booktitle = {Operations Research Proceedings 2025}, year = {2026}, abstract = {Branching decisions play a crucial role in branch-and-bound algorithms for solving combinatorial optimization problems. In this paper, we investigate several branching rules applied to the Quota Steiner Tree Problem with Interference (QSTPI). The Quota Steiner Tree Problem (QSTP) generalizes the classical Steiner Tree Problem (STP) in graphs by seeking a minimum-cost tree that connects a subset of profit-associated vertices whose cumulative profit meets or exceeds a given quota. The QSTPI introduces interference among vertices: Selecting certain vertices simultaneously reduces their individual contributions to the overall profit. This problem arises, for example, in positioning and connecting wind turbines, where turbines possibly shadow other turbines, reducing their energy yield. Unlike classical STP variants, large QSTPI instances require significantly more branching to compute provably optimal solutions. In contrast to branching on variables, we utilize the combinatorial structure of the QSTPI by branching on the graph's vertices. We adapt classical and problem-specific branching rules and present a comprehensive computational study comparing the effectiveness of these branching strategies.}, language = {en} } @article{BrenceBrummerDercksenetal.2026, author = {Brence, Blaž and Brummer, Josephine and Dercksen, Vincent J. and {\"O}zel, Mehmet Neset and Kulkarni, Abhishek and Wolterhoff, Neele and Prohaska, Steffen and Hiesinger, Peter Robin and Baum, Daniel}, title = {Semi-automatic geometrical reconstruction and analysis of filopodia dynamics in 4D two-photon microscopy images}, volume = {27}, journal = {BMC Bioinformatics}, doi = {10.1186/s12859-026-06385-4}, year = {2026}, abstract = {Background: Filopodia are thin and dynamic membrane protrusions that play a crucial role in cell migration, axon guidance, and other processes where cells explore and interact with their surroundings. Historically, filopodial dynamics have been studied in great detail in 2D in cultured cells, and more recently in 3D culture as well as living brains. However, there is a lack of efficient tools to trace and track filopodia in 4D images of complex brain cells. Results: To address this issue, we have developed a semi-automatic workflow for tracing filopodia in 3D images and tracking the traced filopodia over time. The workflow was developed based on high-resolution data of photoreceptor axon terminals in the in vivo context of normal Drosophila brain development, but devised to be applicable to filopodia in any system, including at different temporal and spatial scales. In contrast to the pre-existing methods, our workflow relies solely on the original intensity images without the requirement for segmentation or complex preprocessing. The workflow was realized in C++ within the Amira software system and consists of two main parts, dataset pre-processing, and geometrical filopodia reconstruction, where each of the two parts comprises multiple steps. In this paper, we provide an extensive workflow description and demonstrate its versatility for two different axo-dendritic morphologies, R7 and Dm8 cells. Finally, we provide an analysis of the time requirements for user input and data processing. Conclusion: To facilitate simple application within Amira or other frameworks, we share the source code, which is available at https://github.com/zibamira/filopodia-tool.}, language = {en} } @inproceedings{ScheltenChristgauSchulteetal.2026, author = {Schelten, Niklas and Christgau, Steffen and Schulte, Anton and Schnor, Bettina and Signer, Hannes and Stabernack, Benno}, title = {A Flexible Open-Source Framework for FPGA-based Network-Attached Accelerators using SpinalHDL}, booktitle = {Architecture of Computing Systems - 39th International Conference, ARCS 2026, Mainz, Germany, March 24-26, 2026, Proceedings.}, year = {2026}, abstract = {Domain-specific accelerators are increasingly vital in heterogeneous computing systems, driven by the demand for higher computational capacity and especially energy efficiency. Network-attached FPGAs promise a scalable and flexible alternative to closely coupled FPGAs for integrating accelerators into computing environments. While the advantages of specialized hardware implementations are apparent, traditional hardware development and integration remain time-consuming and complex. We present an open-source framework which combines a hardware shell with supporting software libraries, which enables fast development and deployment of FPGA-based network-attached accelerators. In contrast to traditional approaches using VHDL or Verilog, we leverage generative programming with SpinalHDL, providing a flexible hardware description with multi-level abstractions. This work eases the integration of accelerators into existing network infrastructures and simplifies adaptation to different FPGAs, eliminating complex and lengthy top-level hardware descriptions.}, language = {en} } @inproceedings{FrankeHamacherManns2026, author = {Franke, Paula and Hamacher, Kay and Manns, Paul}, title = {Minimizing and Maximizing the Shannon Entropy for Fixed Marginals}, booktitle = {Operations Research Proceedings 2025}, year = {2026}, abstract = {The mutual information (MI) between two random variables is an important correlation measure in data analysis. The Shannon entropy of a joint probability distri- bution is the variable part under fixed marginals. We aim to minimize and maximize it to obtain the largest and smallest MI possible in this case, leading to a scaled MI ratio for better comparability. We present algorithmic approaches and optimal solutions for a set of problem instances based on data from molecular evolution. We show that this allows us to construct a sensible, systematic correction to raw MI values.}, language = {en} } @inproceedings{DingerGerberGnypetal.2026, author = {Dinger, Patrick and Gerber, Anja and Gnyp, Anna and von Hagel, Frank and Hohmann, Georg and Krause, Celia and Wagner, Sarah and Winkler, Alexander}, title = {Sammlungsdaten als Forschungsdaten in den Digital Humanities}, booktitle = {Book of Abstracts - DHd 2026}, doi = {10.5281/zenodo.18702753}, pages = {69 -- 74}, year = {2026}, language = {de} } @article{AbdelRelleKirchartzetal.2026, author = {Abdel, Dilara and Relle, Jacob and Kirchartz, Thomas and Jaap, Patrick and Fuhrmann, J{\"u}rgen and Burger, Sven and Becker, Christiane and J{\"a}ger, Klaus and Farrell, Patricio}, title = {How nanotextured interfaces influence the electronics in perovskite solar cells}, journal = {EES Sol.}, arxiv = {http://arxiv.org/abs/2506.10691}, doi = {10.1039/D5EL00208G}, year = {2026}, language = {en} } @inproceedings{KochKempkeLindneretal.2026, author = {Koch, Thorsten and Kempke, Nils-Christian and Lindner, Niels and Mehl, Lukas and Wetzel, Manuel and Zittel, Janina}, title = {High-Performance Robust Energy System Planning with Storage: A Single-LP Approach}, booktitle = {Proceedings of URBSENSE 2026 - 1st International Workshop on URBan SENSEmaking and Intelligence for Safer Cities}, year = {2026}, language = {en} } @article{HadjidimitriouKochLippietal.2026, author = {Hadjidimitriou, Natalia Selini and Koch, Thorsten and Lippi, Marco and Petkovic, Milena and Mamei, Marco}, title = {Spatial analysis of COVID-19 and the Russia-Ukraine war impacts on natural gas flows using statistical and machine learning models}, volume = {29}, journal = {World Wide Web}, number = {2}, publisher = {Springer Science and Business Media LLC}, issn = {1386-145X}, doi = {https://doi.org/10.1007/s11280-025-01402-7}, year = {2026}, language = {en} } @misc{KempkeMaherRehfeldtetal.2026, author = {Kempke, Nils-Christian and Maher, Stephen John and Rehfeldt, Daniel and Gleixner, Ambros and Koch, Thorsten and Uslu, Svenja}, title = {Distributed Parallel Structure-Aware Presolving for Arrowhead Linear Programs}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-103034}, year = {2026}, abstract = {We present a structure-aware parallel presolve framework specialized to arrowhead linear programs (AHLPs) and designed for high-performance computing (HPC) environments, integrated into the parallel interior point solver PIPS-IPM++. Large-scale LPs arising from automated model generation frequently contain redundancies and numerical pathologies that necessitate effective presolve, yet existing presolve techniques are primarily serial or structure-agnostic and can become time-consuming in parallel solution workflows. Within PIPS-IPM++, AHLPs are stored in distributed memory, and our presolve builds on this to apply a highly parallel, distributed presolve across compute nodes while keeping communication overhead low and preserving the underlying arrowhead structure. We demonstrate the scalability and effectiveness of our approach on a diverse set of AHLPs and compare it against state-of-the-art presolve implementations, including PaPILO and the presolve implemented within Gurobi. Even on a single machine, our presolve significantly outperforms PaPILO by a factor of 18 and Gurobi's presolve by a factor of 6 in terms of shifted geometric mean runtime, while reducing the problems by a similar amount to PaPILO. Using a distributed compute environment, we outperform Gurobi's presolve by a factor of 13.}, language = {en} } @article{SatoKochLe2026, author = {Sato, Mako and Koch, Thorsten and Le, Thi Thai}, title = {Influence of frictional drag on Kelvin-Helmholtz instability in viscous fluids}, volume = {38}, journal = {Physics of Fluids}, number = {1}, publisher = {AIP Publishing}, address = {Physics of Fluids}, doi = {10.1063/5.0306177}, year = {2026}, abstract = {The Kelvin-Helmholtz instability arises at the interface between two fluid layers with a tangential velocity discontinuity, significantly impacting the safety of systems in industrial applications. Despite extensive studies, many theoretical analyses neglect viscosity and frictional drag due to the complexity of solving the dispersion equation. However, including these effects is crucial, as viscosity alters the growth rate of the instability, while frictional drag influences energy dissipation and momentum transfer. In this study, these effects are incorporated into both finite and infinite flows. The assumption of a potential flow combined with a dissipation method is employed to derive the dispersion equation, providing a more tractable approach than direct calculation methods. The results indicate that, in the case of infinite flows, the frictional drag suppresses the growth of the instability for long waves (small wavenumber k) but enhances it for short waves (large k). In contrast, the surface tension dominates, while the frictional drag only slightly affects the growth rate in the case of finite flows bounded by solid walls.}, language = {en} } @article{RayaMorenoDaschFarahanietal.2026, author = {Raya-Moreno, Mart{\´i} and Dasch, Noah Alexy and Farahani, Nasrin and Gonzalez Oliva, Ignacio and Gulans, Andris and Hossain, Manoar and Kleine, Hannah and Kuban, Martin and Lubeck, Sven and Maurer, Benedikt and Pavone, Pasquale and Peschel, Fabian and Popova-Gorelova, Daria and Qiao, Lu and Richter, Elias and Rigamonti, Santiago and Rodrigues Pel{\´a}, Ronaldo and Sinha, Kshitij and Speckhard, Daniel T. and Tillack, Sebastian and Tumakov, Dmitry and Hong, Seokhyun and Uzulis, Janis and Voiculescu, Mara and Vona, Cecilia and Yang, Mao and Draxl, Claudia}, title = {An exciting approach to theoretical spectroscopy}, arxiv = {http://arxiv.org/abs/2601.11388}, year = {2026}, language = {en} } @inproceedings{BorndoerferJocasWeiser2026, author = {Bornd{\"o}rfer, Ralf and Jocas, Arturas and Weiser, Martin}, title = {An Eikonal Approach for Globally Optimal Free Flight Trajectories}, arxiv = {http://arxiv.org/abs/2603.11830}, year = {2026}, abstract = {We present an eikonal-based approach that is capable of finding a continuous globally optimal trajectory for an aircraft in a stationary wind field. This minimizes emissions and fuel consumption. If the destination is close to a cut locus of the associated Hamilton-Jacobi-Bellman equation, small numerical discretization errors can lead to selecting a merely locally optimal trajectory and missing the globally optimal one. Based on finite element error estimates, we construct a trust region around the cut loci in order to guarantee uniqueness of trajectories for destinations sufficiently far from cut loci.}, language = {en} } @article{KruegerDopslaffManleyetal.2026, author = {Kr{\"u}ger, Jan and Dopslaff, Sven and Manley, Phillip and Bergmann, Detlef and K{\"o}ning, Rainer and Dai, Gaoliang and Hahm, Kai and Schneider, Philipp-Immanuel and Hammerschmidt, Martin and Zschiedrich, Lin and Bosse, Harald and Bodermann, Bernd}, title = {Photomask linewidth measurement comparison including an improved model-based through-focus measurement approach}, volume = {37}, journal = {Meas. Sci. Technol.}, doi = {10.1088/1361-6501/ae44bb}, pages = {095004}, year = {2026}, language = {en} } @article{NgokinghaTchoutoMehlKhomeijaniFarahanietal.2026, author = {Ngokingha Tchouto, Mireille and Mehl, Julia and Khomeijani Farahani, Saeed and Baum, Daniel and Duda, Georg}, title = {Novel image registration approach for combining 2D Osterix and collagen bundles images with 3D µCT}, volume = {10}, journal = {Journal of Bone and Mineral Research}, number = {3}, doi = {10.1093/jbmrpl/ziag009}, year = {2026}, language = {en} } @article{QiaoRodriguesPelaDraxl2026, author = {Qiao, Lu and Rodrigues Pel{\´a}, Ronaldo and Draxl, Claudia}, title = {First-principles approach to ultrafast pump-probe spectroscopy in solids}, arxiv = {http://arxiv.org/abs/2509.07612}, year = {2026}, language = {en} } @article{delRazoLammaMerbis2026, author = {del Razo, Mauricio and Lamma, Tommaso and Merbis, Wout}, title = {Field theories and quantum methods for stochastic reaction-diffusion systems}, volume = {98}, journal = {Rev. Mod. Phys.}, arxiv = {http://arxiv.org/abs/2409.13377}, doi = {10.1103/9qlw-gyd7}, year = {2026}, abstract = {Complex systems are composed of many particles or agents that move and interact with one another. In most real-world applications, these systems involve a varying number of particles/agents that change due to interactions with the environment or their internal dynamics. The underlying mathematical framework to model these systems must incorporate the spatial transport of particles/agents and their interactions, as well as changes to their copy numbers, all of which can be formulated in terms of stochastic reaction-diffusion processes. However, the standard probabilistic representation of these processes can be overly complex because of the combinatorial aspects arising due to the non-linear interactions and varying particle numbers. In this manuscript, we review the main field theory representations of stochastic reaction-diffusion systems, which handle these issues "under-the-hood''. First, we focus on bringing techniques familiar to theoretical physicists —such as second quantization, Fock space, path integrals and quantum field theory— back into the classical domain of reaction-diffusion systems. We demonstrate how various field theory representations, which have evolved historically, can all be unified under a single basis-independent representation. We then extend existing quantum-based methods and notation to work directly on the level of the unifying representation, and we illustrate how they can be used to consistently obtain previous known results in a more straightforward manner, such as numerical discretizations and relations between model parameters at multiple scales. Throughout the work, we contextualize how these representations mirror well-known models of chemical physics depending on their spatial resolution, as well as the corresponding macroscopic (large copy number) limits. The framework presented here may find applications in a diverse set of scientific fields, including physical chemistry, theoretical ecology, epidemiology, game theory and socio-economical models of complex systems, specifically in the modeling and multi-scale simulation of complex systems with varying numbers of particles/agents. The presentation is done in a self-contained educational and unifying manner such that it can be followed by researchers across several fields.}, language = {en} } @article{SubramaniamHubigSchenkletal.2026, author = {Subramaniam, Jayant Shanmugam and Hubig, Michael and Schenkl, Sebastian and Muggenthaler, Holger and Springer, Steffen and Weiser, Martin and Sudau, Jakob and Shah, Faisal and Mall, Gita}, title = {Reconstructing sudden ambient temperature changes for forensic death time estimation using temperatures in two closed compartments: Proof of concept}, journal = {International Journal of Legal Medicine}, year = {2026}, abstract = {Ambient temperature TA has a strong impact on temperature-based time since death estimation (TTDE). Frequently TA is lowered instantaneously at some time t0 from a previous value TA0 to TA1 < TA0 by, e.g., opening a window or a door. We aim at reconstructing TA0 and t0. TTDE literature suggests temperature measurements in closed compartments such as cupboards or neighboring rooms, where TA0 could have been 'preserved' after t0. We aim to estimate t0 and TA0 from temperature measurements TZ(t) in closed compartments Z at times t > t0. We obtain promising results assuming Newtonian cooling for boxes filled with air, heaps of clothes, or books in two different experimental scenarios. Two different parameter estimators, (TA0^, t0^) based on four temperature measurements and (TA0*, t0*) for 4N measurements were tested. Our results in a climate chamber were partially appropriate for TTDE input. A decline at time t0 from TA0 = 22.5°C ↓ TA1 = 14°C was reconstructed at t = t0 + 95min with relative deviations ρt0^ = 27\% and ρTA0^ = 19\% relative to t - t0 and TA0 - TA1 respectively, for N = 1 with span Δt = 50min. For N = 200 in a time interval [t0 + 95min, t0 + 295min] we found ρt0^ = 5\% and ρTA0^ = 11\% with the same Δt. Further research is necessary to guarantee applicability in routine casework, in particular with respect to more elaborate cooling models, estimation algorithms, and evaluation localization.}, language = {en} } @article{VillaniAndresArconesUngeretal.2026, author = {Villani, Paolo and Andr{\´e}s Arcones, Daniel and Unger, J{\"o}rg F. and Weiser, Martin}, title = {Gaussian mixture models for model improvement}, arxiv = {http://arxiv.org/abs/2603.15101}, year = {2026}, abstract = {Modeling complex physical systems such as they arise in civil engineering applications requires finding a trade-off between physical fidelity and practicality. Consequently, deviations of simulation from measurements are ubiquitous even after model calibration due to the model discrepancy, which may result from deliberate modeling decisions, ignorance, or lack of knowledge. If the mismatch between simulation and measurements are deemed unacceptable, the model has to be improved. Targeted model improvement is challenging due to a non-local impact of model discrepancies on measurements and the dependence on sensor configurations. Many approaches to model improvement, such as Bayesian calibration with additive mismatch terms, gray-box models, symbolic regression, or stochastic model updating, often lack interpretability, generalizability, physical consistency, or practical applicability. This paper introduces a non-intrusive approach to model discrepancy analysis using mixture models. Instead of directly modifying the model structure, the method maps sensor readings to clusters of physically meaningful parameters, automatically assigning sensor readings to parameter vector clusters. This mapping can reveal systematic discrepancies and model biases, guiding targeted, physics-based refinements by the modeler. The approach is formulated within a Bayesian framework, enabling the identification of parameter clusters and their assignments via the Expectation-Maximization (EM) algorithm. The methodology is demonstrated through numerical experiments, including an illustrative example and a real-world case study of heat transfer in a concrete bridge.}, language = {en} } @inproceedings{ScheltenChristgauHutzleretal.2026, author = {Schelten, Niklas and Christgau, Steffen and Hutzler, Merit and Kreowsky, Philipp and De Lucia, Marco and Schnor, Bettina and Signer, Hannes and Spazier, Johannes and Stabernack, Benno and Yahdzhyiev, Serhii}, title = {Using FPGA-based Network-Attached Accelerators for Energy-Efficient AI Training in HPC Datacenters}, booktitle = {2026 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)}, year = {2026}, abstract = {FPGA-based Network-Attached Accelerators offer a disaggregated alternative to closely-coupled FPGAs or GPUs, but their adoption is very limited due to missing hardware/software frameworks. However, the usability and energy-efficiency of FPGAs for HPC use-cases has been demonstrated previously. Yet, the support by HPC infrastructure for those devices is lacking behind other accelerators. This paper addresses this shortcoming and demonstrates a full-stack approach that seamlessly integrates Network-Attached Accelerators in HPC datacenters and allows flexible and scalable usage of FPGAs. The presented work includes the according framework, integration steps and a show-case application from the geoscience domain. We evaluate our approach by comparing the training of a Physics-Informed Neural Network on the NAA against two GPU implementations. The NAA reduces total energy consumption by about 50\% and 17\% compared to the Keras and CUDA implementation, respectively. These results demonstrate that FPGA-based NAAs can be successfully integrated into HPC environments and are a viable path toward more energy-efficient AI training.}, language = {en} } @inproceedings{SenguptaKuşLietal.2026, author = {Sengupta, Agniva and Ku{\c{s}}, Dilara and Li, Jianning and Zachow, Stefan}, title = {Globally Optimal Pose from Orthographic Silhouettes}, year = {2026}, abstract = {We solve the problem of determining the pose of known shapes in R^3 from their unoccluded silhouettes. The pose is determined up to global optimality using a simple yet under-explored property of the area-of-silhouette: its continuity w.r.t trajectories in the rotation space. The proposed method utilises pre-computed silhouette-signatures, modelled as a response surface of the area-of-silhouettes. Querying this silhouette-signature response surface for pose estimation leads to a strong branching of the rotation search space, making resolution-guided candidate search feasible. Additionally, we utilise the aspect ratio of 2D ellipses fitted to projected silhouettes as an auxiliary global shape signature to accelerate the pose search. This combined strategy forms the first method to efficiently estimate globally optimal pose from just the silhouettes, without being guided by correspondences, for any shape, irrespective of its convexity and genus. We validate our method on synthetic and real examples, demonstrating significantly improved accuracy against comparable approaches.}, language = {en} } @article{KresseSikorskiChewleetal.2026, author = {Kresse, Jakob and Sikorski, Alexander and Chewle, Surahit and Sunkara, Vikram and Weber, Marcus}, title = {Revealing the Atomistic Mechanism of Rare Events in Molecular Dynamics}, volume = {22}, journal = {Journal of Chemical Theory and Computation}, number = {5}, arxiv = {http://arxiv.org/abs/2511.15514}, doi = {10.1021/acs.jctc.5c01906}, pages = {2380 -- 2389}, year = {2026}, abstract = {Interpretable reaction coordinates are essential for understanding rare conformational transitions in molecular dynamics. The Atomistic Mechanism Of Rare Events in Molecular Dynamics (AMORE-MD) framework enhances interpretability of deep-learned reaction coordinates by connecting them to atomistic mechanisms, without requiring any a priori knowledge of collective variables, pathways, or endpoints. Here, AMORE-MD employs the ISOKANN algorithm to learn a neural membership function χ representing the dominant slow process, from which transition pathways are reconstructed as minimum-energy paths aligned with the gradient of χ, and atomic contributions are quantified through gradient-based sensitivity analysis. Iterative enhanced sampling further enriches transition regions and improves coverage of rare events enabling recovery of known mechanisms and chemically interpretable structural rearrangements at atomic resolution for the M{\"u}ller-Brown potential, alanine dipeptide, and the elastin-derived hexapeptide VGVAPG.}, language = {en} } @inproceedings{RiccardiLindner2026, author = {Riccardi, Gabor and Lindner, Niels}, title = {On The Minimum-Weight Forward (Weakly) Fundamental Cycle Basis Problem in Directed Graphs}, booktitle = {International Network Optimization Conference 2026 (INOC 2026)}, year = {2026}, abstract = {The cycle space of a directed graph is generated by a cycle basis, where, in general, cycles are allowed to have both forward and backward arcs. In a forward cycle, all arcs have to follow the given direction. We study the existence, structure, and computational complexity of minimum-weight forward cycle bases in directed graphs. We give a complete structural characterization of digraphs that admit weakly fundamental (and hence integral) forward cycle bases, showing that this holds if and only if every block is either strongly connected or a single arc. We further provide an easily verifiable characterization of when a strongly connected digraph admits a forward fundamental cycle basis, proving that such a basis exists if and only if the set of directed cycles has cardinality equal to the cycle rank; in this case, the basis is unique and computable in polynomial time, and nonexistence can likewise be certified efficiently. Lastly, we show that while minimum-weight forward fundamental cycle bases can be found in polynomial time whenever they exist, the minimum-weight forward weakly fundamental cycle basis problem is NP-hard via a polynomial-time reduction from the minimum-weight weakly fundamental cycle basis problem on digraphs with metric weights.}, language = {en} } @misc{BaumannDudaSchielaetal.2026, author = {Baumann, Felix and Duda, Georg and Schiela, Anton and Weiser, Martin}, title = {Identification of Stress in Heterogeneous Contact Models}, volume = {173}, journal = {Non-Smooth and Complementarity-Based Distributed Parameter Systems}, editor = {Hinterm{\"u}ller, Michael and Herzog, Roland and Kanzow, Christian and Ulbrich, Michael and Ulbrich, Stefan}, publisher = {Springer Nature}, year = {2026}, abstract = {We develop a heterogeneous model of the lower limb system to simulate muscle forces and stresses acting on the knee joint. The modelling of the bone dynamics leads to an index-3 DAE, which we discretize by higher order collocation methods. Furthermore, we present an elastomechanical contact knee joint model of the articular cartilage. For the solution of the contact problem we develop an efficient multigrid solver, based on an Augmented-Lagrangian relaxation of the contact constraints. We formulate the identification of joint forces and resulting stresses with respect to different knee joint models as an inverse problem based on medical gait data.}, language = {en} } @article{FischbachBetzRebholzetal.2026, author = {Fischbach, Jan David and Betz, Fridtjof and Rebholz, Lukas and Garg, Puneet and Frizyuk, Kristina and Binkowski, Felix and Burger, Sven and Hammerschmidt, Martin and Rockstuhl, Carsten}, title = {Pole-Expansion of the T-Matrix Based on a Matrix-Valued AAA-Algorithm}, journal = {ArXiV}, arxiv = {http://arxiv.org/abs/2602.18414}, doi = {10.48550/arXiv.2602.18414}, pages = {arXiv:2602.18414}, year = {2026}, language = {en} } @article{WuttkeStockmannWinkler2026, author = {Wuttke, Ulrike and Stockmann, Ralf and Winkler, Alexander}, title = {Podcasts als bibliothekarisches Handlungsfeld}, volume = {29}, journal = {B.I.T. online (BIT online) : Bibliothek, Information, Technologie}, number = {1}, issn = {1616-2617}, pages = {48 -- 53}, year = {2026}, language = {de} } @inproceedings{SunkaraRostamivonTycowiczetal.2026, author = {Sunkara, Vikram and Rostami, Atefe and von Tycowicz, Christoph and Sch{\"u}tte, Christof}, title = {Stop throwing away your Decoder; extract the learnt local coordinate system using Latent-XAI}, booktitle = {The 4th World Conference on Explainable Artificial Intelligence (XAI-2026)}, year = {2026}, language = {en} } @article{Navayazdani2026, author = {Navayazdani, Esfandiar}, title = {Ridge Regression on Riemannian Manifolds for Time-Series Prediction}, journal = {Information Geometry}, arxiv = {http://arxiv.org/abs/2411.18339}, year = {2026}, language = {en} } @article{LueckeWinkelmannKoltai2026, author = {L{\"u}cke, Marvin and Winkelmann, Stefanie and Koltai, Peter}, title = {Accurate mean-field equation for voter model dynamics on scale-free networks}, volume = {113}, journal = {Physical Review E}, arxiv = {http://arxiv.org/abs/2509.13485}, doi = {10.1103/vkpx-5cvt}, pages = {034311}, year = {2026}, abstract = {Understanding the emergent macroscopic behavior of dynamical systems on networks is a crucial but challenging task. One of the simplest and most effective methods to construct a reduced macroscopic model is given by mean-field theory. The resulting approximations perform well on dense and homogeneous networks but poorly on scale-free networks, which, however, are more realistic in many applications. In this paper, we introduce a modified version of the mean-field approximation for voter model dynamics on scale-free networks. The two main deviations from classical theory are that we use degree-weighted shares as coarse variables and that we introduce a correlation factor that can be interpreted as slowing down dynamics induced by interactions. We observe that the correlation factor is only a property of the network and not of the state or of parameters of the process. This approach achieves a significantly smaller approximation error than standard methods without increasing dimensionality.}, language = {en} } @article{WehlitzPavliotisSchuetteetal.2026, author = {Wehlitz, Nathalie and Pavliotis, Grigorios and Sch{\"u}tte, Christof and Winkelmann, Stefanie}, title = {Data-driven Reduction of Transfer Operators for Particle Clustering Dynamics}, arxiv = {http://arxiv.org/abs/2601.02932}, year = {2026}, abstract = {We develop an operator-based framework to coarse-grain interacting particle systems that exhibit clustering dynamics. Starting from the particle-based transfer operator, we first construct a sequence of reduced representations: the operator is projected onto concentrations and then further reduced by representing the concentration dynamics on a geometric low-dimensional manifold and an adapted finite-state discretization. The resulting coarse-grained transfer operator is finally estimated from dynamical simulation data by inferring the transition probabilities between the Markov states. Applied to systems with multichromatic and Morse interaction potentials, the reduced model reproduces key features of the clustering process, including transitions between cluster configurations and the emergence of metastable states. Spectral analysis and transition-path analysis of the estimated operator reveal implied time scales and dominant transition pathways, providing an interpretable and efficient description of particle-clustering dynamics.}, language = {en} } @article{SchuetteSikorskiKresseetal.2026, author = {Sch{\"u}tte, Christof and Sikorski, Alexander and Kresse, Jakob and Weber, Marcus}, title = {On-the-Fly Lifting of Coarse Reaction-Coordinate Paths to Full-Dimensional Transition Path Ensembles}, arxiv = {http://arxiv.org/abs/2603.23266}, doi = {10.48550/arXiv.2603.23266}, year = {2026}, abstract = {Effective dynamics on a low-dimensional collective-variable (CV) or latent space can be simulated far more cheaply than the underlying high-dimensional stochastic system, but exploiting such coarse predictions requires lifting: turning a coarse CV trajectory into dynamically consistent full-dimensional states and path ensembles, without relying on global sampling of invariant or conditional fiber measures. We present a local, on-the-fly lifting strategy based on guided full-system trajectories. First an effective model in CV space is used to obtain a coarse reference trajectory. Then, an ensemble of full-dimensional trajectories is generated from a guided version of the original dynamics, where the guidance steers the trajectory to track the CV reference path. Because guidance biases the path distribution, we correct it via pathwise Girsanov reweighting, yielding a correct-by-construction importance-sampling approximation of the conditional law of the uncontrolled dynamics. We further connect the approach to stochastic optimal control, clarifying how coarse models can inform variance-reducing guidance for rare-event quantities. Numerical experiments demonstrate that inexpensive coarse transition paths can be converted into realistic full-system transition pathways (including barrier crossings and detours) and can accelerate estimation of transition pathways and statistics while providing minimal bias through weighted ensembles.}, language = {en} } @inproceedings{RiedmuellerZittelKoch2026, author = {Riedm{\"u}ller, Stephanie and Zittel, Janina and Koch, Thorsten}, title = {Warm-starting Strategies in Scalarization Methods for Multi-Objective Optimization}, booktitle = {Operations Research Proceedings 2025}, arxiv = {http://arxiv.org/abs/2507.21933}, year = {2026}, abstract = {We explore how warm-starting strategies can be integrated into scalarization-based approaches for multi-objective optimization in (mixed) integer linear programming. Scalarization methods remain widely used classical techniques to compute Pareto-optimal solutions in applied settings. They are favored due to their algorithmic simplicity and broad applicability across continuous and integer programs with an arbitrary number of objectives. While warm-starting has been applied in this context before, a systematic methodology and analysis remain lacking. We address this gap by providing a theoretical characterization of warm-starting within scalarization methods, focusing on the sequencing of subproblems. However, optimizing the order of subproblems to maximize warm-start efficiency may conflict with alternative criteria, such as early identification of infeasible regions. We quantify these trade-offs through an extensive computational study.}, language = {en} } @misc{KharmaWiesSchintke2026, author = {Kharma, Sami and Wies, Tobias and Schintke, Florian}, title = {Comprehensive Plugin-Based Monitoring of Nexflow Workflow Executions}, journal = {SCA/HPC Asia 2026}, arxiv = {http://arxiv.org/abs/2603.28783}, year = {2026}, language = {en} } @article{TrepczynskiKneifelHeylandetal.2025, author = {Trepczynski, Adam and Kneifel, Paul and Heyland, Mark and Leskovar, Marko and Moewis, Philippe and Damm, Philipp and Taylor, William R. and Zachow, Stefan and Duda, Georg N.}, title = {Impact of the external knee flexion moment on patello-femoral loading derived from in vivo loads and kinematics}, volume = {12/2024}, journal = {Frontiers in Bioengineering and Biotechnology}, publisher = {Frontiers Media SA}, organization = {Charit{\´e} - Universit{\"a}tsmedizin Berlin}, issn = {2296-4185}, doi = {10.3389/fbioe.2024.1473951}, year = {2025}, abstract = {Introduction: Anterior knee pain and other patello-femoral (PF) complications frequently limit the success of total knee arthroplasty as the final treatment of end stage osteoarthritis. However, knowledge about the in-vivo loading conditions at the PF joint remains limited, as no direct measurements are available. We hypothesised that the external knee flexion moment (EFM) is highly predictive of the PF contact forces during activities with substantial flexion of the loaded knee. Materials and methods: Six patients (65-80 years, 67-101 kg) with total knee arthroplasty (TKA) performed two activities of daily living: sit-stand-sit and squat. Tibio-femoral (TF) contact forces were measured in vivo using instrumented tibial components, while synchronously internal TF and PF kinematics were captured with mobile fluoroscopy. The measurements were used to compute PF contact forces using patient specific musculoskeletal models. The relationship between the EFM and the PF contact force was quantified using linear regression. Results: Mean peak TF contact forces of 1.97-3.24 times body weight (BW) were found while peak PF forces reached 1.75 to 3.29 times body weight (BW). The peak EFM ranged from 3.2 to 5.9 \%BW times body height, and was a good predictor of the PF contact force (R2 = 0.95 and 0.88 for sit-stand-sit and squat, respectively). Discussion: The novel combination of in vivo TF contact forces and internal patellar kinematics enabled a reliable assessment of PF contact forces. The results of the regression analysis suggest that PF forces can be estimated based solely on the EFM from quantitative gait analysis. Our study also demonstrates the relevance of PF contact forces, which reach magnitudes similar to TF forces during activities of daily living.}, language = {en} } @misc{RiedmuellerBuchholzZittel2025, author = {Riedm{\"u}ller, Stephanie and Buchholz, Annika and Zittel, Janina}, title = {Enhancing Multi-Energy Modeling: The Role of Mixed-Integer Optimization Decisions}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-100329}, year = {2025}, abstract = {The goal to decarbonize the energy sector has led to increased research in modeling and optimizing multi-energy systems. One of the most promising and popular techniques for modeling and solving (multi-)energy optimization problems is (multi-objective) mixed-integer programming, valued for its ability to represent the complexities of integrated energy systems. While the literature often focuses on deriving mathematical formulations and parameter settings, less attention is given to critical post-formulation decisions. Modeling multi-energy systems as mixed-integer linear optimization programs demands decisions across multiple degrees of freedom. Key steps include reducing a real-world multi energy network into an abstract topology, defining variables, formulating the relevant (in-)equalities to represent technical requirements, setting (multiple) objectives, and integrating these elements into a mixed-integer program (MIP). However, with these elements fixed, the specific transformation of the abstract topology into a graph structure and the construction of the MIP remain non-uniquely. These choices can significantly impact user-friendliness, problem size, and computational efficiency, thus affecting the feasibility and efficiency of modeling efforts. In this work, we identify and analyze the additional degrees of freedom and describe two distinct approaches to address them. The approaches are compared regarding mathematical equivalence, suitability for solution algorithms, and clarity of the underlying topology. A case study on a realistic subarea of Berlin's district heating network involving tri-objective optimization for a unit commitment problem demonstrates the practical significance of these decisions. By highlighting these critical yet often overlooked aspects, our work equips energy system modelers with insights to improve computational efficiency, scalability, and interpretability in their optimization efforts, ultimately enhancing the practicality and effectiveness of multi-energy system models.}, language = {en} } @misc{PedersenLindnerRehfeldtetal.2025, author = {Pedersen, Jaap and Lindner, Niels and Rehfeldt, Daniel and Koch, Thorsten}, title = {Comparing Branching Rules for the Quota Steiner Tree Problem with Interference}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101250}, year = {2025}, abstract = {Branching decisions play a crucial role in branch-and-bound algorithms for solving combinatorial optimization problems. In this paper, we investigate several branching rules applied to the Quota Steiner Tree Problem with Interference (QSTPI). The Quota Steiner Tree Problem (QSTP) generalizes the classical Steiner Tree Problem (STP) in graphs by seeking a minimum-cost tree that connects a subset of profit-associated vertices to meet a given quota. The extended version, QSTPI, introduces interference among vertices: Selecting certain vertices simultaneously reduces their individual contributions to the overall profit. This problem arises, for example, in positioning and connecting wind turbines, where turbines possibly shadow other turbines, reducing their energy yield. While exact solvers for standard STP-related problems often rely heavily on reduction techniques and cutting-plane methods - rarely generating large branch-and-bound trees - experiments reveal that large instances of QSTPI require significantly more branching to compute provably optimal solutions. In contrast to branching on variables, we utilize the combinatorial structure of the QSTPI by branching on the graph's vertices. We adapt classical and problem-specific branching rules and present a comprehensive computational study comparing the effectiveness of these branching strategies.}, language = {en} } @misc{KempkeKoch2025, author = {Kempke, Nils-Christian and Koch, Thorsten}, title = {A GPU accelerated variant of Schroeppel-Shamir's algorithm for solving the market split problem}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-100554}, year = {2025}, abstract = {The market split problem (MSP), introduced by Cornu{\´e}jols and Dawande (1998), is a challenging binary optimization problem that performs poorly on state-of-the-art linear programming-based branch-and-cut solvers. We present a novel algorithm for solving the feasibility version of this problem, derived from Schroeppel-Shamir's algorithm for the one-dimensional subset sum problem. Our approach is based on exhaustively enumerating one-dimensional solutions of MSP and utilizing GPUs to evaluate candidate solutions across the entire problem. The resulting hybrid CPU-GPU implementation efficiently solves instances with up to 10 constraints and 90 variables. We demonstrate the algorithm's performance on benchmark problems, solving instances of size (9, 80) in less than fifteen minutes and (10, 90) in up to one day.}, language = {en} } @article{KochBernalNeiraChenetal.2025, author = {Koch, Thorsten and Bernal Neira, David E. and Chen, Ying and Cortiana, Giorgio and Egger, Daniel J. and Heese, Raoul and Hegade, Narendra N. and Gomez Cadavid, Alejandro and Huang, Rhea and Itoko, Toshinari and Kleinert, Thomas and Maciel Xavier, Pedro and Mohseni, Naeimeh and Montanez-Barrera, Jhon A. and Nakano, Koji and Nannicini, Giacomo and O'Meara, Corey and Pauckert, Justin and Proissl, Manuel and Ramesh, Anurag and Schicker, Maximilian and Shimada, Noriaki and Takeori, Mitsuharu and Valls, Victor and Van Bulck, David and Woerner, Stefan and Zoufal, Christa}, title = {Quantum Optimization Benchmark Library -- The Intractable Decathlon}, arxiv = {http://arxiv.org/abs/2504.03832}, year = {2025}, abstract = {Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particularly in combinatorial optimization -- where most algorithms are heuristics -- it is key to empirically analyze their performance on hardware and track progress towards quantum advantage. To this extent, we present ten optimization problem classes that are difficult for existing classical algorithms and can (mostly) be linked to practically-relevant applications, with the goal to enable systematic, fair, and comparable benchmarks for quantum optimization methods. Further, we introduce the Quantum Optimization Benchmark Library (QOBLIB) where the problem instances and solution track records can be found. The individual properties of the problem classes vary in terms of objective and variable type, coefficient ranges, and density. Crucially, they all become challenging for established classical methods already at system sizes ranging from less than 100 to, at most, an order of 100,000 decision variables, allowing to approach them with today's quantum computers. We reference the results from state-of-the-art solvers for instances from all problem classes and demonstrate exemplary baseline results obtained with quantum solvers for selected problems. The baseline results illustrate a standardized form to present benchmarking solutions, which has been designed to ensure comparability of the used methods, reproducibility of the respective results, and trackability of algorithmic and hardware improvements over time. We encourage the optimization community to explore the performance of available classical or quantum algorithms and hardware platforms with the benchmarking problem instances presented in this work toward demonstrating quantum advantage in optimization.}, language = {en} } @inproceedings{RiedmuellerBuchholzZittel2025, author = {Riedm{\"u}ller, Stephanie and Buchholz, Annika and Zittel, Janina}, title = {Enhancing Multi-Energy Modeling: The Role of Mixed-Integer Optimization Decisions}, booktitle = {The 38th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems - ECOS 2025}, arxiv = {http://arxiv.org/abs/2505.14492}, year = {2025}, abstract = {The goal to decarbonize the energy sector has led to increased research in modeling and optimizing multi-energy systems. One of the most promising and popular techniques for modeling and solving (multi-)energy optimization problems is (multi-objective) mixed-integer programming, valued for its ability to represent the complexities of integrated energy systems. While the literature often focuses on deriving mathematical formulations and parameter settings, less attention is given to critical post-formulation decisions. Modeling multi-energy systems as mixed-integer linear optimization programs demands decisions across multiple degrees of freedom. Key steps include reducing a real-world multi energy network into an abstract topology, defining variables, formulating the relevant (in-)equalities to represent technical requirements, setting (multiple) objectives, and integrating these elements into a mixed-integer program (MIP). However, with these elements fixed, the specific transformation of the abstract topology into a graph structure and the construction of the MIP remain non-uniquely. These choices can significantly impact user-friendliness, problem size, and computational efficiency, thus affecting the feasibility and efficiency of modeling efforts. In this work, we identify and analyze the additional degrees of freedom and describe two distinct approaches to address them. The approaches are compared regarding mathematical equivalence, suitability for solution algorithms, and clarity of the underlying topology. A case study on a realistic subarea of Berlin's district heating network involving tri-objective optimization for a unit commitment problem demonstrates the practical significance of these decisions. By highlighting these critical yet often overlooked aspects, our work equips energy system modelers with insights to improve computational efficiency, scalability, and interpretability in their optimization efforts, ultimately enhancing the practicality and effectiveness of multi-energy system models.}, language = {en} } @article{ZimperDjurdjevacHartmannetal.2025, author = {Zimper, Sebastian and Djurdjevac, Ana and Hartmann, Carsten and Sch{\"u}tte, Christof and Conrad, Natasa Djurdjevac}, title = {Mean-field optimal control with stochastic leaders}, arxiv = {http://arxiv.org/abs/2512.19201}, year = {2025}, abstract = {We consider interacting agent systems with a large number of stochastic agents (or particles) influenced by a fixed number of external stochastic lead agents. Such examples arise, for example in models of opinion dynamics, where a small number of leaders (influencers) can steer the behaviour of a large population of followers. In this context, we study a partial mean-field limit where the number of followers tends to infinity, while the number of leaders stays constant. The partial mean-field limit dynamics is then given by a McKean-Vlasov stochastic differential equation (SDE) for the followers, coupled to a controlled It{\^o}-SDE governing the dynamics of the lead agents. For a given cost functional that the lead agents seek to minimise, we show that the unique optimal control of the finite agent system convergences to the optimal control of the limiting system. This establishes that the low-dimensional control of the partial (mean-field) system provides an effective approximation for controlling the high-dimensional finite agent system. In addition, we propose a stochastic gradient descent algorithm that can efficiently approximate the mean-field control. Our theoretical results are illustrated on opinion dynamics model with lead agents, where the control objective is to drive the followers to reach consensus in finite time.}, language = {en} } @misc{MehlLindnerBartoszuketal.2025, author = {Mehl, Lukas and Lindner, Niels and Bartoszuk, Karolina and Zittel, Janina}, title = {Prototypical warm-starts for demand-robust LP-based energy system optimization}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101242}, year = {2025}, abstract = {The expressiveness of energy system optimization models (ESOMs) depends on a multitude of exogenous parameters. For example, sound estimates of the future energy demand are essential to enable qualified decisions on long-term investments. However, the enormous demand fluctuations even on a fine-grained scale diminish the computational performance of large-scale ESOMs. We therefore propose a clustering-and-decomposition method for linear programming based ESOMs that first identifies and solves prototypical demand scenarios with the dual simplex algorithm, and then composes dual optimal prototype bases to a warm-start basis for the full model. We evaluate the feasibility and computational efficiency our approach on a real-world case study, using a sector-coupled ESOM with hourly resolution for the Berlin-Brandenburg area in Germany, based on the oemof framework.}, language = {en} } @misc{RiedmuellerZittelKoch2025, author = {Riedm{\"u}ller, Stephanie and Zittel, Janina and Koch, Thorsten}, title = {Warm-starting Strategies in Scalarization Methods for Multi-Objective Optimization}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101073}, year = {2025}, abstract = {We explore how warm-starting strategies can be integrated into scalarization-based approaches for multi-objective optimization in (mixed) integer linear programming. Scalarization methods remain widely used classical techniques to compute Pareto-optimal solutions in applied settings. They are favored due to their algorithmic simplicity and broad applicability across continuous and integer programs with an arbitrary number of objectives. While warm-starting has been applied in this context before, a systematic methodology and analysis remain lacking. We address this gap by providing a theoretical characterization of warm-starting within scalarization methods, focusing on the sequencing of subproblems. However, optimizing the order of subproblems to maximize warm-start efficiency may conflict with alternative criteria, such as early identification of infeasible regions. We quantify these trade-offs through an extensive computational study.}, language = {en} } @incollection{GotzesBuchholzKallrathetal.2025, author = {Gotzes, Uwe and Buchholz, Annika and Kallrath, Josef and Lindner, Niels and Koch, Thorsten}, title = {Flexible Pooling Pattern Design with Integer Programming}, volume = {226}, booktitle = {Theory, Algorithms and Experiments in Applied Optimization. In Honor of the 70th Birthday of Panos Pardalos}, publisher = {Springer}, year = {2025}, abstract = {Sample pooling has the potential to significantly enhance large-scale screening procedures, especially in scenarios like the COVID-19 pandemic, where rapid and widespread PCR testing has been crucial. Efficient strategies are essential to increase the testing capacity, i.e., the number of tests that can be processed within a given timeframe. Non-adaptive pooling strategies can further streamline the testing process by reducing the required testing rounds. In contrast to adaptive strategies, where subsequent tests depend on prior results, non-adaptive pooling processes all samples in a single round, eliminating the need for sequential retesting and reducing delays. This paper presents a highly flexible method based on integer programming to design optimized pooling patterns suitable for various applications, including medical diagnostics and quality control in industrial production. Using coronavirus testing as a case study, we formulate and solve optimization and satisfiability models that compute efficient pool designs. Our optimized pooling does not only increase testing capacity, but also accelerates the testing process and reduces overall costs. The proposed method is adaptable and can be seamlessly integrated into automated testing systems.}, language = {en} } @article{ZhouChenPengetal.2025, author = {Zhou, Lei and Chen, Ying and Peng, Hanqiu and Koch, Thorsten}, title = {Is innovation slowing down? Insights from the AIMS framework of patent values}, volume = {280}, journal = {Expert Systems with Applications}, doi = {10.1016/j.eswa.2025.127355}, pages = {127355}, year = {2025}, abstract = {Amidst the unprecedented expansion of scientific and technological knowledge over the past century, concerns persist regarding a slowdown in innovation. To address this, we introduce the AIMS framework, which categorizes patents into four types—Aurora, Invisible, Mirage, and Success—based on their respective inherent scientific values and market-recognized economic values. Utilizing USPTO patent and citation data from 1976 to 2022, our analysis reveals an increasing volume of patent issuances but a concerning dilution in scientific quality starting in the 2000s. This trend is primarily attributed to the rise of low scientific value patents—categorized as Mirage and Invisible—and a modest decline in high-impact scientific patents—categorized as Success and Aurora. Meanwhile, the economic value of patents has risen, especially noted with the growth in Mirage patents since the 2010s, indicating a shift towards strategies that prioritize market-driven patenting. This study highlights the evolving nature of patents from mere indicators of scientific innovation to strategic tools for market dominance, providing an alternative understanding of patent value and its implications for firms' strategic decisions over patent issuance across different sectors.}, language = {en} } @article{RiedmuellerKoch2025, author = {Riedm{\"u}ller, Stephanie and Koch, Thorsten}, title = {Exact Objective Space Contraction for the Preprocessing of Multi-objective Integer Programs}, arxiv = {http://arxiv.org/abs/2512.01535}, year = {2025}, abstract = {Solving integer optimization problems with large or widely ranged objective coefficients can lead to numerical instability and increased runtimes. When the problem also involves multiple objectives, the impact of the objective coefficients on runtimes and numerical issues multiplies. We address this issue by transforming the coefficients of linear objective functions into smaller integer coefficients. To the best of our knowledge, this problem has not been defined before. Next to a straightforward scaling heuristic, we introduce a novel exact transformation approach for the preprocessing of multi-objective binary problems. In this exact approach, the large or widely ranged integer objective coefficients are transformed into the minimal integer objective coefficients that preserve the dominance relation of the points in the objective space. The transformation problem is solved with an integer programming formulation with an exponential number of constraints. We present a cutting-plane algorithm that can efficiently handle the problem size. In a first computational study, we analyze how often and in which settings the transformation actually leads to smaller coefficients. In a second study, we evaluate how the exact transformation and a typical scaling heuristic, when used as preprocessing, affect the runtime and numerical stability of the Defining Point Algorithm.}, language = {en} } @article{ChenKochPengetal.2025, author = {Chen, Ying and Koch, Thorsten and Peng, Hanqui and Zhang, Hongrui}, title = {Benchmarking of Quantum and Classical Computing in Large-Scale Dynamic Portfolio Optimization Under Market Frictions}, arxiv = {http://arxiv.org/abs/2502.05226}, year = {2025}, abstract = {Quantum computing is poised to transform the financial industry, yet its advantages over traditional methods have not been evidenced. As this technology rapidly evolves, benchmarking is essential to fairly evaluate and compare different computational strategies. This study presents a challenging yet solvable problem of large-scale dynamic portfolio optimization under realistic market conditions with frictions. We frame this issue as a Quadratic Unconstrained Binary Optimization (QUBO) problem, compatible with digital computing and ready for quantum computing, to establish a reliable benchmark. By applying the latest solvers to real data, we release benchmarks that help verify true advancements in dynamic trading strategies, either quantum or digital computing, ensuring that reported improvements in portfolio optimization are based on robust, transparent, and comparable metrics.}, language = {en} } @article{PetkovicZittel2025, author = {Petkovic, Milena and Zittel, Janina}, title = {Leveraging Transfer Learning to Overcome Data Limitations in Czochralski Crystal Growth}, volume = {8}, journal = {Advanced Theory and Simulations}, number = {11}, doi = {10.1002/adts.202500677}, year = {2025}, language = {en} } @inproceedings{RiedmuellerRivettaZittel2025, author = {Riedm{\"u}ller, Stephanie and Rivetta, Fabian and Zittel, Janina}, title = {Long-Term Multi-Objective Optimization for Integrated Unit Commitment and Investment Planning for District Heating Networks}, booktitle = {Operations Research Proceedings 2024}, publisher = {Springer Cham}, arxiv = {http://arxiv.org/abs/2410.06673}, doi = {10.1007/978-3-031-92575-7_33}, pages = {235 -- 241}, year = {2025}, abstract = {The need to decarbonize the energy system has intensified the focus on district heating networks in urban and suburban areas. Therefore, exploring transformation pathways with reasonable trade-offs between economic viability and environmental goals became necessary. We introduce a network-flow-based model class integrating unit commitment and long-term investment planning for multi-energy systems. While the integration of unit commitment and investment planning has been applied to multi-energy systems, a formal introduction and suitability for the application of long-term portfolio planning of an energy provider on an urban scale has yet to be met. Based on mixed integer linear programming, the model bridges the gap between overly detailed industrial modeling tools not designed for computational efficiency at scale and rather abstract academic models. The formulation is tested on Berlin's district heating network. Hence, the challenge lies in a large number of variables and constraints and the coupling of time steps, for example, through investment decisions. A case study explores different solutions on the Pareto front defined by optimal trade-offs between minimizing costs and CO2 emissions through a lexicographic optimization approach. The resulting solution catalog can provide decision-makers valuable insights into feasible transformation pathways, highlighting distinctions between robust and target-dependent investments.}, language = {en} } @inproceedings{PetkovicZittel2025, author = {Petkovic, Milena and Zittel, Janina}, title = {Resilient Forecasting of High-Dimensional Network Time Series in the Energy Domain: A Hybrid Approach}, booktitle = {Operations Research Proceedings 2023. OR 2023}, publisher = {Springer}, doi = {10.1007/978-3-031-58405-3_48}, pages = {375 -- 381}, year = {2025}, abstract = {Energy systems are complex networks consisting of various interconnected components. Accurate energy demand and supply forecasts are crucial for efficient system operation and decision-making. However, high-dimensional data, complex network structures, and dynamic changes and disruptions in energy networks pose significant challenges for forecasting models. To address this, we propose a hybrid approach for resilient forecasting of network time series (HRF-NTS) in the energy domain. Our approach combines mathematical optimization methods with state-of-the-art machine learning techniques to achieve accurate and robust forecasts for high-dimensional energy network time series. We incorporate an optimization framework to account for uncertainties and disruptive changes in the energy system. The effectiveness of the proposed approach is demonstrated through a case study of forecasting energy demand and supply in a complex, large-scale natural gas transmission network. The results show that the hybrid approach outperforms alternative prediction models in terms of accuracy and resilience to structural changes and disruptions, providing stable, multi-step ahead forecasts for different short to mid-term forecasting horizons.}, language = {en} } @inproceedings{YuekselErguenKochZittel2025, author = {Yueksel-Erguen, Inci and Koch, Thorsten and Zittel, Janina}, title = {Consistent flow scenario generation based on open data for operational analysis of European gas transport networks}, booktitle = {Operations Research Proceedings 2023. OR 2023}, publisher = {Springer}, doi = {10.1007/978-3-031-58405-3_63}, pages = {493 -- 499}, year = {2025}, abstract = {In recent years, European gas transport has been affected by major disruptive events like political issues such as, most recently, the Russian war on Ukraine. To incorporate the impacts of such events into decision-making during the energy transition, more complex models for gas network analysis are required. However, the limited availability of consistent data presents a significant obstacle in this endeavor. We use a mathematical-modeling-based scenario generator to deal with this obstacle. The scenario generator consists of capacitated network flow models representing the gas network at different aggregation levels. In this study, we present the coarse-to-fine approach utilized in this scenario generator.}, language = {en} } @inproceedings{KochRehfeldtShinano2025, author = {Koch, Thorsten and Rehfeldt, Daniel and Shinano, Yuji}, title = {On the state of QUBO solving}, booktitle = {Operations Research Proceedings 2023. OR 2023}, publisher = {Springer}, doi = {10.1007/978-3-031-58405-3_46}, pages = {357 -- 365}, year = {2025}, abstract = {It is regularly claimed that quantum computers will bring breakthrough progress in solving challenging combinatorial optimization problems relevant in practice. In particular, Quadratic Unconstrained Binary Optimization (QUBO) problems are said to be the model of choice for use in (adiabatic) quantum systems during the noisy intermediate- scale quantum (NISQ) era. Even the first commercial quantum-based systems are advertised to solve such problems. Theoretically, any Integer Program can be converted into a QUBO. In practice, however, there are some caveats, as even for problems that can be nicely modeled as a QUBO, this might not be the most effective way to solve them. We review the state of QUBO solving on digital and quantum computers and provide insights regarding current benchmark instances and modeling.}, language = {en} } @inproceedings{YuekselErguenLitzelPeng2025, author = {Yueksel Erguen, Inci and Litzel, Ida and Peng, Hanqiu}, title = {Integrating Large Citation Datasets}, booktitle = {Operations Research Proceedings 2024. OR 2024}, doi = {10.1007/978-3-031-92575-7_7}, pages = {46 -- 52}, year = {2025}, abstract = {This paper explores methods for building a comprehensive citation graph using big data techniques to evaluate scientific impact more accurately. Traditional citation metrics have limitations, and this work investigates merging large citation datasets to create a more accurate picture. Challenges of big data, like inconsistent data formats and lack of unique identifiers, are addressed through deduplication efforts, resulting in a streamlined and reliable merged dataset with over 119 million records and 1.4 billion citations. We demonstrate that merging large citation datasets builds a more accurate citation graph facilitating a more robust evaluation of scientific impact.}, language = {en} } @article{ZakiyevaPetkovic2025, author = {Zakiyeva, Nazgul and Petkovic, Milena}, title = {High-dimensional high-frequency time series prediction with a mixed integer optimisation method}, journal = {Operations Research Proceedings 2023. OR 2023}, issn = {1438-0064}, doi = {10.1007/978-3-031-58405-3_54}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-93068}, pages = {423 -- 429}, year = {2025}, abstract = {We study a functional autoregressive model for high-frequency time series. We approach the estimation of the proposed model using a Mixed Integer Optimisation method. The proposed model captures serial dependence in the functional time series by including high-dimensional curves. We illustrate our methodology on large-scale natural gas network data. Our model provides more accurate day-ahead hourly out-of-sample forecast of the gas in and out-flows compared to alternative prediction models.}, language = {en} } @misc{VuLitzelKoch2025, author = {Vu, Thi Huong and Litzel, Ida and Koch, Thorsten}, title = {Similarity-based fuzzy clustering scientific articles: potentials and challenges from mathematical and computational perspectives}, arxiv = {http://arxiv.org/abs/2506.04045}, year = {2025}, abstract = {Fuzzy clustering, which allows an article to belong to multiple clusters with soft membership degrees, plays a vital role in analyzing publication data. This problem can be formulated as a constrained optimization model, where the goal is to minimize the discrepancy between the similarity observed from data and the similarity derived from a predicted distribution. While this approach benefits from leveraging state-of-the-art optimization algorithms, tailoring them to work with real, massive databases like OpenAlex or Web of Science -- containing about 70 million articles and a billion citations -- poses significant challenges. We analyze potentials and challenges of the approach from both mathematical and computational perspectives. Among other things, second-order optimality conditions are established, providing new theoretical insights, and practical solution methods are proposed by exploiting the problem's structure. Specifically, we accelerate the gradient projection method using GPU-based parallel computing to efficiently handle large-scale data.}, language = {en} } @misc{ZakiyevaPetkovic2025, author = {Zakiyeva, Nazgul and Petkovic, Milena}, title = {Large-scale functional network time series model solved with mathematical programming approach}, journal = {Econometrics and Statistics}, doi = {10.1016/j.ecosta.2025.10.001}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101936}, year = {2025}, abstract = {A functional network autoregressive model is proposed for studying large-scale network time series observed at high temporal resolution. The model incorporates high-dimensional curves to capture both serial and cross-sectional dependence in large-scale network functional time series. Estimation of the model is approached using a Mixed Integer Optimization method. Simulation studies confirm the consistency of parameter and adjacency matrix estimation. The method is applied to data from a real-life natural gas supply network. Compared to alternative prediction models, the proposed model delivers more accurate day-ahead hourly out-of-sample forecasts of the gas inflows and outflows at most gas nodes.}, language = {en} } @article{ZakiyevaPetkovic2025, author = {Zakiyeva, Nazgul and Petkovic, Milena}, title = {Large-scale functional network time series model solved with mathematical programming approach}, journal = {Econometrics and Statistics}, publisher = {Elsevier BV}, issn = {2452-3062}, doi = {10.1016/j.ecosta.2025.10.001}, year = {2025}, language = {en} } @misc{ShinanoVigerske2025, author = {Shinano, Yuji and Vigerske, Stefan}, title = {Smoothie: Mixing the strongest MIP solvers to solve hard MIP instances on supercomputers - Phase I development}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-101906}, year = {2025}, abstract = {Mixed-Integer Linear Programming (MIP) is applicable to such a wide range of real-world decision problems that the competition for the best code to solve such problems has lead to tremendous progress over the last decades. While current solvers can solve some of the problems that seemed completely out-of-reach just 10 years ago, there are always relevant MIP problems that currently cannot be solved. With the Smoothie solver we intend to solve extremely hard MIP problems by building on the many years that went into the development of several state-of-the-art MIP solvers and by utilizing some of the largest computing resources available. The high-level task parallelization framework UG (Ubiquity Generator) is used and extended by Smoothie to build a solver that uses large-scale parallelization to distribute the solution of a single MIP on a shared- or distributed-memory computing infrastructure, thereby employing several established MIP solvers simultaneously. For the first development phase, which is the topic of this report, both FICO Xpress and Gurobi are used in concurrent mode on a single machine, while information on incumbent solutions and explored branch-and-bound subtrees is exchanged. A dynamic restarting mechanism ensures that solver configurations are selected that promise most suitable for the MIP to be solved. We report on initial findings using this early version of Smoothie on unsolved problems from MIPLIB 2017.}, language = {en} } @misc{VuKoch2025, author = {Vu, Thi Huong and Koch, Thorsten}, title = {Clustering scientific publications: lessons learned through experiments with a real citation network}, arxiv = {http://arxiv.org/abs/2505.18180}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-100418}, year = {2025}, abstract = {Clustering scientific publications helps uncover research structures within bibliographic databases. Graph-based methods such as spectral, Louvain, and Leiden clustering are commonly used due to their ability to model citation networks. However, their effectiveness can diminish when applied to real-world data. This study evaluates these clustering algorithms on a citation graph of about 700,000 articles and 4.6 million citations from the Web of Science. The results show that while scalable methods like Louvain and Leiden perform efficiently, their default settings often yield poor partitioning. Meaningful outcomes require careful parameter tuning, especially for large networks with uneven structures, including a dense core and loosely connected papers. These findings highlight practical lessons about the challenges of large-scale data, method selection and tuning based on specific structures of bibliometric clustering tasks.}, language = {en} } @article{KiesslingLeyfferVanaret2025, author = {Kießling, David and Leyffer, Sven and Vanaret, Charlie}, title = {A Unified Funnel Restoration SQP Algorithm}, journal = {Mathematical Programming B}, doi = {10.1007/s10107-025-02284-3}, year = {2025}, abstract = {We consider nonlinearly constrained optimization problems and discuss a generic double-loop framework consisting of basic algorithmic ingredients that unifies a broad range of nonlinear optimization solvers. This framework has been implemented in the open-source solver Uno, a Swiss Army knife-like C++ optimization framework that unifies many nonlinearly constrained nonconvex optimization solvers. We illustrate the framework with a sequential quadratic programming (SQP) algorithm that maintains an acceptable upper bound on the constraint violation, called a funnel, that is monotonically decreased to control the feasibility of the iterates. Infeasible quadratic subproblems are handled by a feasibility restoration strategy. Globalization is controlled by a line search or a trust-region method. We prove global convergence of the trust-region funnel SQP method, building on known results from filter methods. We implement the algorithm in Uno, and we provide extensive test results for the trust-region line-search funnel SQP on small CUTEst instances.}, language = {en} } @article{KempkeRehfeldtKoch2025, author = {Kempke, Nils-Christian and Rehfeldt, Daniel and Koch, Thorsten}, title = {A Massively Parallel Interior-Point-Method for Arrowhead Linear Programs}, journal = {SIAM Journal on Scientific Computing}, arxiv = {http://arxiv.org/abs/2412.07731}, year = {2025}, language = {en} } @article{RongChenMaetal.2025, author = {Rong, Guoyang and Chen, Ying and Ma, Feicheng and Koch, Thorsten}, title = {Exploring Interdisciplinary Research Trends through Critical Years for Interdisciplinary Citation}, volume = {19}, journal = {Journal of Informetrics}, number = {4}, doi = {10.1016/j.joi.2025.101726}, year = {2025}, language = {en} } @misc{PedersenLindnerRehfeldtetal.2025, author = {Pedersen, Jaap and Lindner, Niels and Rehfeldt, Daniel and Koch, Thorsten}, title = {Integrated Wind Farm Design: Optimizing Turbine Placement and Cable Routing with Wake Effects}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-99218}, year = {2025}, abstract = {An accelerated deployment of renewable energy sources is crucial for a successful transformation of the current energy system, with wind energy playing a key role in this transition. This study addresses the integrated wind farm layout and cable routing problem, a challenging nonlinear optimization problem. We model this problem as an extended version of the Quota Steiner Tree Problem (QSTP), optimizing turbine placement and network connectivity simultaneously to meet specified expansion targets. Our proposed approach accounts for the wake effect - a region of reduced wind speed induced by each installed turbine - and enforces minimum spacing between turbines. We introduce an exact solution framework in terms of the novel Quota Steiner Tree Problem with interference (QSTPI). By leveraging an interference-based splitting strategy, we develop an advanced solver capable of tackling large-scale problem instances. The presented approach outperforms generic state-of-the-art mixed integer programming solvers on our dataset by up to two orders of magnitude. Moreover, we demonstrate that our integrated method significantly reduces the costs in contrast to a sequential approach. Thus, we provide a planning tool that enhances existing planning methodologies for supporting a faster and cost-efficient expansion of wind energy.}, language = {en} } @misc{KempkeKuntKatamishetal.2025, author = {Kempke, Nils-Christian and Kunt, Tim and Katamish, Bassel and Vanaret, Charlie and Sasanpour, Shima and Clarner, Jan-Patrick and Koch, Thorsten}, title = {Developing heuristic solution techniques for large-scale unit commitment models}, issn = {1438-0064}, arxiv = {http://arxiv.org/abs/2502.19012}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-99555}, year = {2025}, abstract = {Shifting towards renewable energy sources and reducing carbon emissions necessitate sophisticated energy system planning, optimization, and extension. Energy systems optimization models (ESOMs) often form the basis for political and operational decision-making. ESOMs are frequently formulated as linear (LPs) and mixed-integer linear (MIP) problems. MIPs allow continuous and discrete decision variables. Consequently, they are substantially more expressive than LPs but also more challenging to solve. The ever-growing size and complexity of ESOMs take a toll on the computational time of state-of-the-art commercial solvers. Indeed, for large-scale ESOMs, solving the LP relaxation -- the basis of modern MIP solution algorithms -- can be very costly. These time requirements can render ESOM MIPs impractical for real-world applications. This article considers a set of large-scale decarbonization-focused unit commitment models with expansion decisions based on the REMix framework (up to 83 million variables and 900,000 discrete decision variables). For these particular instances, the solution to the LP relaxation and the MIP optimum lie close. Based on this observation, we investigate the application of relaxation-enforced neighborhood search (RENS), machine learning guided rounding, and a fix-and-propagate (FP) heuristic as a standalone solution method. Our approach generated feasible solutions 20 to 100 times faster than GUROBI, achieving comparable solution quality with primal-dual gaps as low as 1\% and up to 35\%. This enabled us to solve numerous scenarios without lowering the quality of our models. For some instances that Gurobi could not solve within two days, our FP method provided feasible solutions in under one hour.}, language = {en} } @article{LePetkovic2025, author = {Le, Thi Thai and Petkovic, Milena}, title = {Predicting Fluid Interface Instability in Energy Systems for Sustainable Energy Transition}, journal = {Operations Research Proceedings 2023. OR 2023.}, publisher = {Springer}, doi = {10.1007/978-3-031-58405-3_45}, pages = {349 -- 356}, year = {2025}, abstract = {Due to the coexistence of different gases in underground storage, this work explores the interface stability's impact on energy storage, specifically during the injection and withdrawal of gases such as hydrogen and natural gas. A new approach of combing simulation and time series analysis is used to accurately predict instability modes in energy systems. Our simulation is based on the 2D Euler equations, solved using a second-order finite volume method with a staggered grid. The solution is validated by comparing them to experimental data and analytical solutions, accurately predicting the instability's behavior. We use time series analysis and state-of-the-art regime-switching methods to identify critical features of the interface dynamics, providing crucial insights into system optimization and design.}, language = {en} } @inproceedings{LindnerBartoszukDebguptaetal.2025, author = {Lindner, Niels and Bartoszuk, Karolina and Debgupta, Srinwanti and Gering, Marie-Claire and Muschner, Christoph and Zittel, Janina}, title = {Warm-starting modeling to generate alternatives for energy transition paths in the Berlin-Brandenburg area}, booktitle = {Operations Research Proceedings 2024. OR 2024}, doi = {10.1007/978-3-031-92575-7_35}, pages = {248 -- 253}, year = {2025}, abstract = {Energy system optimization models are key to investigate energy transition paths towards a decarbonized future. Since this approach comes with intrinsic uncertainties, it is insufficient to compute a single optimal solution assuming perfect foresight to provide a profound basis for decision makers. The paradigm of modeling to generate alternatives enables to explore the near-optimal solution space to a certain extent. However, large-scale energy models require a non-negligible computation time to be solved. We propose to use warm start methods to accelerate the process of finding close-to-optimal alternatives. In an extensive case study for the energy transition of the Berlin-Brandenburg area, we make use of the sector-coupled linear programming oemof-B3 model to analyze a scenario for the year 2050 with a resolution of one hour and 100\% reduction of greenhouse gas emissions. We demonstrate that we can actually achieve a significant computational speedup.}, language = {en} } @inproceedings{StomporZittelKochetal.2025, author = {Stompor, Tomasz and Zittel, Janina and Koch, Thorsten and Rusch, Beate}, title = {Fully Algorithmic Librarian: Large-Scale Citation Experiments}, booktitle = {20th International Society of Scientometrics and Informetrics Conference 2025, June 23-27, 2025 | Yerevan, Armenia}, doi = {10.51408/issi2025_204}, year = {2025}, abstract = {The Fully Algorithmic Librarian (FAN) project explores application scenarios for algorithmic-intelligence(AI)-supported methods in academic libraries as central institutions for research support. To this end, the study builds on two algorithmic approaches for analyzing large-scale citation networks. A comparison of Web of Science (WoS) and OpenAlex structures using the PageRank algorithm reveals key differences. Additionally, a multi-label clustering technique designed for large-scale citation networks accounts for disciplinary variations in publication practices.}, language = {en} } @article{ChenKochPengetal.2025, author = {Chen, Ying and Koch, Thorsten and Peng, Hanqui and Zhang, Hongrui}, title = {Benchmarking of Quantum and Classical Computing in Large-Scale Dynamic Portfolio Optimization Under Market Frictions}, arxiv = {http://arxiv.org/abs/2502.05226}, year = {2025}, language = {en} } @inproceedings{TurnerBertholdBesancon2025, author = {Turner, Mark and Berthold, Timo and Besan{\c{c}}on, Mathieu}, title = {A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming}, booktitle = {Operations Research Proceedings 2023. OR 2023.}, doi = {10.1007/978-3-031-58405-3_28}, pages = {217 -- 244}, year = {2025}, abstract = {The current cut selection algorithm used in mixed-integer programming solvers has remained largely unchanged since its creation. In this paper, we propose a set of new cut scoring measures, cut filtering techniques, and stopping criteria, extending the current state-of-the-art algorithm and obtaining a 5\\% performance improvement for SCIP over the MIPLIB 2017 benchmark set.}, language = {en} } @article{ShinanoFujii2025, author = {Shinano, Yuji and Fujii, Koichi}, title = {Introduction to Quadratic Programming Solvers}, volume = {64}, journal = {Journal of The Society of Instrument and Control Engineers}, number = {8}, doi = {10.11499/sicejl.64.532}, pages = {532 -- 540}, year = {2025}, language = {en} } @article{NagelHeitzigSchoell2025, author = {Nagel, Soeren and Heitzig, Jobst and Schoell, Eckehard}, title = {Macroscopic Stochastic Model for Economic Cycle Dynamics}, volume = {134}, journal = {Physical Review Letters}, number = {4}, publisher = {American Physical Society}, arxiv = {http://arxiv.org/abs/2312.16708}, doi = {https://doi.org/10.1103/PhysRevLett.134.047402}, pages = {1 -- 6}, year = {2025}, abstract = {We present a stochastic dynamic model which can explain economic cycles. We show that the macroscopic description yields a complex dynamical landscape consisting of multiple stable fixed points, each corresponding to a split of the population into a large low and a small high income group. The stochastic fluctuations induce switching between the resulting metastable states and excitation oscillations just below a deterministic bifurcation. The shocks are caused by the decisions of a few agents who have a disproportionate influence over the macroscopic state of the economy due to the unequal distribution of wealth among the population. The fluctuations have a long-term effect on the growth of economic output and lead to business cycle oscillations exhibiting coherence resonance, where the correlation time is controlled by the population size which is inversely proportional to the noise intensity.}, language = {en} } @article{CharronMusilGuljasetal.2025, author = {Charron, Nicholas and Musil, F{\´e}lix and Guljas, Andrea and Chen, Yaoyi and Bonneau, Klara and Pasos-Trejo, Aldo and Jacopo, Venturin and Daria, Gusew and Zaporozhets, Iryna and Kr{\"a}mer, Andreas and Templeton, Clark and Atharva, Kelkar and Durumeric, Aleksander and Olsson, Simon and P{\´e}rez, Adri{\`a} and Majewski, Maciej and Husic, Brooke and Patel, Ankit and De Fabritiis, Gianni and No{\´e}, Frank and Clementi, Cecilia}, title = {Navigating protein landscapes with a machine-learned transferable coarse-grained model}, volume = {17}, journal = {Nature Chemistry}, arxiv = {http://arxiv.org/abs/2310.18278}, doi = {10.1038/s41557-025-01874-0}, pages = {1284 -- 1292}, year = {2025}, abstract = {The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a universal, computationally efficient coarse-grained (CG) model with similar prediction performance has been a long-standing challenge. By combining recent deep learning methods with a large and diverse training set of all-atom protein simulations, we here develop a bottom-up CG force field with chemical transferability, which can be used for extrapolative molecular dynamics on new sequences not used during model parametrization. We demonstrate that the model successfully predicts folded structures, intermediates, metastable folded and unfolded basins, and the fluctuations of intrinsically disordered proteins while it is several orders of magnitude faster than an all-atom model. This showcases the feasibility of a universal and computationally efficient machine-learned CG model for proteins.}, language = {en} } @article{KrishnadasCharronFournier2025, author = {Krishnadas, Anirudh and Charron, Nicolas and Fournier, Rene}, title = {Melting Transitions in Small Aluminum Clusters Simulated with Energies Approaching DFT Accuracy.}, journal = {ACS Publications- Journal of Chemical Theory and Computation}, year = {2025}, abstract = {We describe a computational framework for modelling melting-like transitions in atomic clusters that combines first-principles energy calculations, global optimization, and machine-learned interatomic potentials. A diverse set of configurations is generated by global optimization, and energies are calculated by Density Functional Theory. The energies are fitted to an accuracy of 10 meV/atom or better with an Allegro E(3)-equivariant neural network potential. The model allows efficient parallel tempering Monte Carlo simulations with near DFT-level accuracy. This methodology was validated by simulating Na_20 and comparing it to earlier experimental and computational results. We used it to study melting-like transitions in Al_n+ clusters (n=9 to 16), and Al_n and Al_n^- (n=12, 13,14). The simulated heat capacity of these clusters, in particular Al_16+, are in qualitative agreement with experiments. The melting point of Al_n+ clusters with n=11-16 are well above the bulk melting point (934 K). The closed-shell Al_13- species has an exceptionally high melting point, close to 2100 K.}, language = {en} } @article{KrishnadasMoshiQuintanaetal.2025, author = {Krishnadas, Anirudh and Moshi, Maryam and Quintana, Ramon Alain Miranda and Fournier, Rene}, title = {Geometric Features and a Neural Network Classifier for Detecting Melting-Like Transitions in Clusters.}, journal = {AIP Publications - The Journal of Chemical Physics}, year = {2025}, abstract = {Melting-like transitions in clusters are normally identified by a peak in the heat capacity curve C(T ) at T = Tc. Computing C(T ) requires costly simulations with millions of steps. We discuss four easily calculated functions of temperature that help detect and characterize melting-like transitions. The first, f1 (or WU ), is the width of the potential energy distribution which shows an abrupt increase near Tc. The other three are statistics of the ordered set of N(N - 1)/2 interatomic distances rij: (i) f2 is a measure of dissimilarity to the lowest energy configuration, or global minimum; (ii) f3 is the effective number of rij's found in a small interval centered around (r1 + r2)/2 where r1, r2 are the positions of the first two peaks in the pair distribution function; and (iii) f4 is a measure of non-uniformity in the distribution of the ri j's. Numerical tests with empirical potentials that model three types of bonding (van der Waals, covalent, and metallic) show that f1, f2, f3, and f4 produce estimates for the middle of the melting region in general agreement with Tc. An Artificial Neural Network (ANN) classifier that takes, as inputs, f2, f3, and many variants of f4, is used to calculate the solid fraction FS(T) and find the solid-liquid coexistence region between freezing and melting temperatures, [Tf , Tm]. Inflection points in f3(T ) and FS(T ) are very sensitive indicators of phase transitions. Estimates of Tc obtained from them converge one to three orders of magnitude faster, in simulation time, than those obtained with C(T ).}, language = {en} } @article{MarcoMarcus2025, author = {Marco, Reidelbach and Marcus, Weber}, title = {From Documentation to Discovery - MaRDMO and the MaRDI Ecosystem}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16735889}, year = {2025}, language = {en} } @article{FischerGerberKopruckietal.2025, author = {Fischer, Kristina and Gerber, Anja and Koprucki, Thomas and Noback, Andres and Reidelbach, Marco and Schrade, Torsten and Thiery, Florian}, title = {Windows on Data: Federating Research Data with FAIR Digital Objects and Linked Open Data}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16736222}, year = {2025}, language = {en} } @article{BiernackaCastroFritzschetal.2025, author = {Biernacka, Katarzyna and Castro, Leyla Jael and Fritzsch, Bernadette and Grossmann, Yves Vincent and Reidelbach, Marco and Struck, Alexander and Lanza, Giacomo and Walter, David and Ulusoy, Inga}, title = {From Vision to Implementation: Current Practices and Challenges of Software Management Plans in Research}, journal = {2nd Conference on Research Data Infrastructure (CoRDI)}, doi = {10.5281/zenodo.16735302}, year = {2025}, language = {en} } @article{ClauseckerLemireSchintke2025, author = {Clausecker, Robert and Lemire, Daniel and Schintke, Florian}, title = {Faster Positional-Population Counts for AVX2, AVX-512, and ASIMD}, volume = {37}, journal = {Concurrency and Computation: Practice and Experience}, number = {27-28}, publisher = {Wiley}, issn = {1532-0626}, doi = {10.1002/cpe.70435}, year = {2025}, language = {en} } @article{SenguptaBartoli2025, author = {Sengupta, Agniva and Bartoli, Adrien}, title = {Convex Solutions to SfT and NRSfM under Algebraic Deformation Models}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, doi = {10.1109/TPAMI.2025.3635039}, year = {2025}, abstract = {We present nonlinear formulations to Shape-from-Template (SfT) and Non-Rigid Structure-from-Motion (NRSfM) faithfully exploiting the isometric, conformal and equiareal deformation models. Existing work uses relaxations such as inextensibility or requires knowing the optic flow field around the correspondences, an impractical assumption. In contrast, the proposed formulations only require point correspondences and resolve all ambiguities using the notions of maximal depth and maximal isometry heuristics. We propose solution methods using Semi-Definite Programming (SDP) for all formulations. We show that straightforward SDP models conflict with the usual maximal depth heuristic and propose an adapted opposite-depth parameterisation demonstrating a lesser relaxation gap. Experimental results on many real-world benchmark datasets demonstrate superior accuracy over existing methods.}, language = {en} } @misc{WeiserHubigShanmugamSubramaniam2025, author = {Weiser, Martin and Hubig, Michael and Shanmugam Subramaniam, Jayant}, title = {Reconstructing Ambient Temperature Changes in Death Time Estimation with a Bayesian Double-Exponential Approach}, journal = {Zenodo}, doi = {10.5281/zenodo.17702240}, year = {2025}, abstract = {Code and data for the reconstruction of ambient temperature drop in time of death estimation We provide Octave code and temperature measurement data for - empirircally estimating thermal sensor likelihood - estimating time and amplitude of a single sudden ambient temperature drop from temperature measurement data in two thermally different compartments.}, language = {en} } @inproceedings{GłuchTuranNagarajanetal.2025, author = {Głuch, Grzegorz and Turan, Berkant and Nagarajan, Sai Ganesh and Pokutta, Sebastian}, title = {The Good, the Bad and the Ugly: Meta-Analysis of Watermarks, Transferable Attacks and Adversarial Defenses}, booktitle = {Proceedings of the Conference on Neural Information Processing Systems}, year = {2025}, language = {en} } @inproceedings{KeraPelleritiIshiharaetal.2025, author = {Kera, Hiroshi and Pelleriti, Nico and Ishihara, Yuki and Zimmer, Max and Pokutta, Sebastian}, title = {Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms}, booktitle = {Proceedings of the Conference on Neural Information Processing Systems}, year = {2025}, language = {en} } @article{SekulicSchaibleMuelleretal.2025, author = {Sekulic, Ivan and Schaible, Jonas and M{\"u}ller, Gabriel and Plock, Matthias and Burger, Sven and Mart{\´i}nez-Lahuerta, V{\´i}ctor Jos{\´e} and Gaaloul, Naceur and Schneider, Philipp-Immanuel}, title = {Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions}, volume = {6}, journal = {Mach. Learn. Sci. Technol.}, publisher = {IOP Publishing}, doi = {10.1088/2632-2153/ae1f5f}, pages = {040503}, year = {2025}, abstract = {Abstract Bayesian optimization with Gaussian process surrogates is a popular approach for optimizing expensive-to-evaluate functions in terms of time, energy, or computational resources. Typically, a Gaussian process models a scalar objective derived from observed data. However, in many real-world applications, the objective is a combination of multiple outputs from physical experiments or simulations. Converting these multidimensional observations into a single scalar can lead to information loss, slowing convergence and yielding suboptimal results. To address this, we propose to use multi-output Gaussian processes to learn the full vector of observations directly, before mapping them to the scalar objective via an inexpensive analytical function. This physics-informed approach retains more information from the underlying physical processes, improving surrogate model accuracy. As a result, the approach accelerates optimization and produces better final designs compared to standard implementations.}, language = {en} } @inproceedings{SchemberaWuebbelingKleikampetal.2025, author = {Schembera, Bj{\"o}rn and W{\"u}bbeling, Frank and Kleikamp, Hendrik and Schmidt, Burkhard and Shehu, Aurela and Reidelbach, Marco and Biedinger, Christine and Fiedler, Jochen and Koprucki, Thomas and Iglezakis, Dorothea and G{\"o}ddeke, Dominik}, title = {Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics}, volume = {2331}, booktitle = {Metadata and Semantic Research. MTSR 2024}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {9783031819735}, issn = {1865-0929}, doi = {10.1007/978-3-031-81974-2_8}, pages = {95 -- 109}, year = {2025}, abstract = {Mathematical models and algorithms are an essential part of mathematical research data, as they are epistemically grounding numerical data. To make this research data FAIR, we present how two previously distinct ontologies, MathAlgoDB for algorithms and MathModDB for models, were merged and extended into a living knowledge graph as the key outcome. This was achieved by connecting the ontologies through computational tasks that correspond to algorithmic tasks. Moreover, we show how models and algorithms can be enriched with subject-specific metadata, such as matrix symmetry or model linearity, essential for defining workflows and determining suitable algorithms. Additionally, we propose controlled vocabularies to be added, along with a new class that differentiates base quantities from specific use case quantities. We illustrate the capabilities of the developed knowledge graph using two detailed examples from different application areas of applied mathematics, having already integrated over 250 research assets into the knowledge graph.}, language = {en} } @inproceedings{ZschiedrichBetzBinkowskietal.2025, author = {Zschiedrich, Lin and Betz, Fridtjof and Binkowski, Felix and Kuen, Lilli and Hammerschmidt, Martin and Burger, Sven}, title = {Efficient Photonic Component Analysis via AAA Rational Approximation}, booktitle = {2025 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD)}, doi = {10.1109/NUSOD64393.2025.11199710}, pages = {115 -- 116}, year = {2025}, language = {en} } @phdthesis{Plock2025, author = {Plock, Matthias}, title = {On Methods for Bayesian Optimization of Least Squares Problems and Optimization of Nanophotonic Devices}, doi = {10.17169/refubium-48179}, year = {2025}, language = {en} } @inproceedings{ManogueSchangKuşetal.2025, author = {Manogue, Kevin and Schang, Tomasz and Ku{\c{s}}, Dilara and M{\"u}ller, Jonas and Zachow, Stefan and Sengupta, Agniva}, title = {Generalizing Shape-from-Template to Topological Changes}, booktitle = {Smart Tools and Applications in Graphics - Eurographics Italian Chapter Conference}, publisher = {The Eurographics Association}, isbn = {978-3-03868-296-7}, arxiv = {http://arxiv.org/abs/2511.03459}, doi = {10.2312/stag.20251322}, year = {2025}, abstract = {Reconstructing the surfaces of deformable objects from correspondences between a 3D template and a 2D image is well studied under Shape-from-Template (SfT) methods; however, existing approaches break down when topological changes accompany the deformation. We propose a principled extension of SfT that enables reconstruction in the presence of such changes. Our approach is initialized with a classical SfT solution and iteratively adapts the template by partitioning its spatial domain so as to minimize an energy functional that jointly encodes physical plausibility and reprojection consistency. We demonstrate that the method robustly captures a wide range of practically relevant topological events including tears and cuts on bounded 2D surfaces, thereby establishing the first general framework for topological-change-aware SfT. Experiments on both synthetic and real data confirm that our approach consistently outperforms baseline methods.}, language = {en} } @misc{SekulicSchaibleMuelleretal.2025, author = {Sekulic, Ivan and Schaible, Jonas and M{\"u}ller, Gabriel and Plock, Matthias and Burger, Sven and Martinez-Lahuerta, Victor J. and Gaaloul, Naceur and Schneider, Philipp-Immanuel}, title = {Data publication for Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions}, journal = {Zenodo}, doi = {10.5281/zenodo.16751507}, year = {2025}, language = {en} } @misc{BetzBinkowskiFischbachetal.2025, author = {Betz, Fridtjof and Binkowski, Felix and Fischbach, Jan David and Feldman, Nick and Zschiedrich, Lin and Rockstuhl, Carsten and Koenderink, A. Femius and Burger, Sven}, title = {Uncovering Hidden Resonances in Non-Hermitian Systems with Scattering Thresholds (Laser Photonics Rev. 19(21)/2025)}, volume = {19}, journal = {Laser Photonics Rev.}, number = {21}, doi = {10.1002/lpor.70534}, pages = {e70534}, year = {2025}, language = {en} }