@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} } @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} } @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{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} } @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{LiuZhangLi2025, author = {Liu, Zichen and Zhang, Wei and Li, Tiejun}, title = {Improving the Euclidean Diffusion Generation of Manifold Data by Mitigating Score Function Singularity}, journal = {NeurIPS 2025}, arxiv = {http://arxiv.org/abs/2505.09922}, year = {2025}, abstract = {Euclidean diffusion models have achieved remarkable success in generative modeling across diverse domains, and they have been extended to manifold case in recent advances. Instead of explicitly utilizing the structure of special manifolds as studied in previous works, we investigate direct sampling of the Euclidean diffusion models for general manifold-constrained data in this paper. We reveal the multiscale singularity of the score function in the embedded space of manifold, which hinders the accuracy of diffusion-generated samples. We then present an elaborate theoretical analysis of the singularity structure of the score function by separating it along the tangential and normal directions of the manifold. To mitigate the singularity and improve the sampling accuracy, we propose two novel methods: (1) Niso-DM, which introduces non-isotropic noise along the normal direction to reduce scale discrepancies, and (2) Tango-DM, which trains only the tangential component of the score function using a tangential-only loss function. Numerical experiments demonstrate that our methods achieve superior performance on distributions over various manifolds with complex geometries.}, 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} } @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} } @inproceedings{BortolettoLindner2025, author = {Bortoletto, Enrico and Lindner, Niels}, title = {Scaling and Rounding Periodic Event Scheduling Instances to Different Period Times}, booktitle = {Operations Research Proceedings 2023}, editor = {Voigt, Guido and Fliedner, Malte and Haase, Knut and Br{\"u}ggemann, Wolfgang and Hoberg, Kai and Meissner, J{\"o}rn}, doi = {10.1007/978-3-031-58405-3_51}, pages = {397 -- 402}, year = {2025}, abstract = {The Periodic Event Scheduling Problem (PESP) is a notoriously hard combinatorial optimization problem, essential for the design of periodic timetables in public transportation. The coefficients of the integer variables in the standard mixed integer linear programming formulations of PESP are the period time, e.g., 60 for a horizon of one hour with a resolution of one minute. In many application scenarios, lines with different frequencies have to be scheduled, leading to period times with many divisors. It then seems natural to consider derived instances, where the period time is a divisor of the original one, thereby smaller, and bounds are scaled and rounded accordingly. To this end, we identify two rounding schemes: wide and tight. We then discuss the approximation performance of both strategies, in theory and practice.}, language = {en} } @inproceedings{LindnerLiebchen2025, author = {Lindner, Niels and Liebchen, Christian}, title = {Incremental Heuristics for Periodic Timetabling}, booktitle = {Operations Research Proceedings 2023}, editor = {Voigt, Guido and Fliedner, Malte and Haase, Knut and Br{\"u}ggemann, Wolfgang and Hoberg, Kai and Meissner, J{\"o}rn}, publisher = {Springer Nature Switzerland}, address = {Cham}, doi = {10.1007/978-3-031-58405-3_59}, pages = {461 -- 467}, year = {2025}, abstract = {We present incremental heuristics for the Periodic Event Scheduling Problem (PESP), the standard mathematical tool to optimize periodic timetables in public transport. The core of our method is to solve successively larger subinstances making use of previously found solutions. Introducing the technical notion of free stratifications, we formulate a general scheme for incremental heuristics for PESP. More practically, we use line and station information to create heuristics that add lines or stations one by one, and we evaluate these heuristics on instances of the benchmarking library PESPlib. This approach is indeed viable, and leads to new incumbent solutions for six PESPlib instances.}, 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{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{KrishnadasSinhaKirchneretal.2024, author = {Krishnadas, Anirudh and Sinha, Nidhi and Kirchner, Tom and Antony, Bobby}, title = {Calculation of electron-impact ionization of various benzene derivatives}, volume = {99}, journal = {IOP Publications- Physica Scripta}, number = {9}, doi = {10.1088/1402-4896/ad640a}, pages = {095403}, year = {2024}, abstract = {Calculations of the electron-impact ionization cross-section of pyrene, anthracene, benzoyl chloride, benzophenone, and phthalonitrile are reported over a wide energy range. A comparison of theoretical models, viz. spherical complex optical potential (SCOP), pixel counting method (PCM), and the binary encounter Bethe (BEB) model is carried out. SCOP calculations provide the inelastic cross-section, and the ionization cross-section is extracted from it. This result is modified with PCM, a model previously applied to ion collisions which takes geometric screening corrections into account. The BEB model is used as an independent approach to calculate the ionization cross-section. It is demonstrated that all model results are in reasonable agreement with each other. Comparison is also made with other theoretical data where available.}, language = {en} } @inproceedings{LoebelLindner2025, author = {L{\"o}bel, Fabian and Lindner, Niels}, title = {A Geometric Approach to Integrated Periodic Timetabling and Passenger Routing}, volume = {137}, booktitle = {25th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2025)}, editor = {Sauer, Jonas and Schmidt, Marie}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, isbn = {978-3-95977-404-8}, issn = {2190-6807}, doi = {10.4230/OASIcs.ATMOS.2025.2}, url = {http://nbn-resolving.de/urn:nbn:de:0030-drops-247580}, pages = {2:1 -- 2:19}, year = {2025}, abstract = {We offer a geometric perspective on the problem of integrated periodic timetabling and passenger routing in public transport. Inside the space of periodic tensions, we single out those regions, where the same set of paths provides shortest passenger routes. This results in a polyhedral subdivision, which we combine with the known decomposition by polytropes. On each maximal region of the common refinement, the integrated problem is solvable in polynomial time. We transform these insights into a new geometry-driven primal heuristic, integrated tropical neighborhood search (ITNS). Computationally, we compare implementations of ITNS and the integrated (restricted) modulo network simplex algorithm on the TimPassLib benchmark set, and contribute better solutions in terms of total travel time for all but one of the twenty-five instances for which a proven optimal solution is not yet known.}, language = {en} } @inproceedings{GhannamGleixner2025, author = {Ghannam, Mohammed and Gleixner, Ambros}, title = {Hybrid Genetic Search for Dynamic Vehicle Routing with Time Windows}, booktitle = {Operations Research Proceedings 2023. OR 2023}, doi = {10.1007/978-3-031-58405-3_35}, year = {2025}, language = {en} } @article{OkaforntaFarhadifarFabigetal.2025, author = {Okafornta, Chukwuebuka William and Farhadifar, Reza and Fabig, Gunar and Wu, Hai-Yin and K{\"o}ckert, Maria and Vogel, Martin and Baum, Daniel and Haase, Robert and Shelley, Michael J. and Needleman, Daniel J. and M{\"u}ller-Reichert, Thomas}, title = {Cell size reduction scales spindle elongation but not chromosome segregation in C. elegans}, journal = {bioRxiv}, doi = {10.1101/2025.10.13.681585}, year = {2025}, abstract = {How embryos adapt their internal cellular machinery to reductions in cell size during development remains a fundamental question in cell biology. Here, we use high-resolution lattice light-sheet fluorescence microscopy and automated image analysis to quantify lineage-resolved mitotic spindle and chromosome segregation dynamics from the 2- to 64-cell stages in Caenorhabditis elegans embryos. While spindle length scales with cell size across both wild-type and size-perturbed embryos, chromosome segregation dynamics remain largely invariant, suggesting that distinct mechanisms govern these mitotic processes. Combining femtosecond laser ablation with large-scale electron tomography, we find that central spindle microtubules mediate chromosome segregation dynamics and remain uncoupled from cell size across all stages of early development. In contrast, spindle elongation is driven by cortically anchored motor proteins and astral microtubules, rendering it sensitive to cell size. Incorporating these experimental results into an extended stoichiometric model for both the spindle and chromosomes, we find that allowing only cell size and microtubule catastrophe rates to vary reproduces elongation dynamics across development. The same model also accounts for centrosome separation and pronuclear positioning in the one-cell C. elegans embryo, spindle-length scaling across nematode species spanning ~100 million years of divergence, and spindle rotation in human cells. Thus, a unified stoichiometric framework provides a predictive, mechanistic account of spindle and nuclear dynamics across scales and species.}, language = {en} } @article{RiedmuellerLindner2025, author = {Riedm{\"u}ller, Stephanie and Lindner, Niels}, title = {Column Generation for Periodic Timetabling}, arxiv = {http://arxiv.org/abs/2510.12466}, year = {2025}, abstract = {Periodic timetabling for public transportation networks is typically modelled as a Periodic Event Scheduling Problem (PESP). Solving instances of the benchmark library PESPlib to optimality continues to pose a challenge. As a further approach towards this goal, we remodel the problem by a time discretization of the underlying graph and consider arc-based as well as path-based integer programming formulations. For the path-based case, we use cycles on the graph expansion of the operational lines as variables and, therefore, include more of the problem inherent structure into the model. A consequence is the validity of several known inequalities and a lower bound on the LP-relaxation, that is the best known to date. As an extension we integrate passenger routing into the new model. The proposed models have an advantage in the linear programming relaxation, on the one hand, but have an increased problem size, on the other hand. We define the corresponding pricing problems for the use of column generation to handle the size. Both models are practically tested on different problem instances.}, language = {en} } @article{GonnermannMuellerHaaseFackeldeyetal.2025, author = {Gonnermann-M{\"u}ller, Jana and Haase, Jennifer and Fackeldey, Konstantin and Pokutta, Sebastian}, title = {FACET: Teacher-Centred LLM-Based Multi-Agent Systems-Towards Personalized Educational Worksheets}, arxiv = {http://arxiv.org/abs/2508.11401}, year = {2025}, abstract = {The increasing heterogeneity of student populations poses significant challenges for teachers, particularly in mathematics education, where cognitive, motivational, and emotional differences strongly influence learning outcomes. While AI-driven personalization tools have emerged, most remain performance-focused, offering limited support for teachers and neglecting broader pedagogical needs. This paper presents the FACET framework, a teacher-facing, large language model (LLM)-based multi-agent system designed to generate individualized classroom materials that integrate both cognitive and motivational dimensions of learner profiles. The framework comprises three specialized agents: (1) learner agents that simulate diverse profiles incorporating topic proficiency and intrinsic motivation, (2) a teacher agent that adapts instructional content according to didactical principles, and (3) an evaluator agent that provides automated quality assurance. We tested the system using authentic grade 8 mathematics curriculum content and evaluated its feasibility through a) automated agent-based assessment of output quality and b) exploratory feedback from K-12 in-service teachers. Results from ten internal evaluations highlighted high stability and alignment between generated materials and learner profiles, and teacher feedback particularly highlighted structure and suitability of tasks. The findings demonstrate the potential of multi-agent LLM architectures to provide scalable, context-aware personalization in heterogeneous classroom settings, and outline directions for extending the framework to richer learner profiles and real-world classroom trials.}, language = {en} } @misc{OPUS4-10176, title = {Mathematical Optimization for Machine Learning}, editor = {Fackeldey, Konstantin and Kannan, Aswin and Pokutta, Sebastian and Sharma, Kartikey and Walter, Daniel and Walter, Andrea and Weiser, Martin}, publisher = {De Gruyter}, isbn = {9783111376776}, doi = {10.1515/9783111376776}, year = {2025}, abstract = {Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Semester 2023 of the Berlin Mathematics Research Center MATH+ collects recent progress on their interplay in topics such as discrete optimization, nonlinear programming, optimal control, first-order methods, multilevel optimization, machine learning in optimization, physics-informed learning, and fairness in machine learning.}, language = {en} }