@unpublished{67292,
  abstract     = {{Classical shadows are an influential framework for compressing copies of a given quantum state $ρ$ into classical data $S$, enabling many properties of $ρ$ to be predicted from relatively few copies. In this work, we study two natural questions involving shadows: (1) Given $S$, when can one efficiently verify that $S$ came from a genuine $n$-qubit state? This is called the Classical Shadow Validity (CSV) problem, introduced by Karaiskos, Rudolph, Meyer, Eisert, and Gharibian [ICALP 2026]. (2) Given $S$ that allows one to capture 2-local properties of $ρ$, can one fake or spoof a shadow $S'$ which predicts 3-local properties of some state? For (1), we show CSV is efficiently solvable for permutation-invariant shadows, QMA-hard for real, fermionic, and bosonic shadows, and both coNP-hard and QMA-hard when the observable family consists of all $n$-qubit Pauli strings. A result of independent interest along the way is a new upper bound qc-$Σ_2$ $\subseteq$ $\mathrm{P}^{\mathrm{PP}}$, where qc-$Σ_2$ is a quantum analogue of the second level of the polynomial hierarchy in which the first proof is quantum. For (2), we show intractability: Given the 2-local marginals $S$ of a quantum state $ρ$, estimating the 3-local marginals of $ρ$ is intractable unless QCMA $\subseteq$ BPP, even if the state $ρ$ is the unique state consistent with $S$.}},
  author       = {{Karaiskos, Georgios and Raza, Asad and Rudolph, Dorian and Koh, Dax Enshan and Gharibian, Sevag}},
  booktitle    = {{arXiv:2609.40107}},
  title        = {{{Verification Complexity and Extension of Classical Shadows}}},
  year         = {{2026}},
}

@unpublished{67293,
  abstract     = {{Low-energy estimation and state preparation for general $k$-local Hamiltonians are fundamental challenges in quantum complexity theory. Buhrman et al.~ [BGLGST, PRL 2025] recently broke the natural Grover bound $O^\ast(2^{n/2})$ for both problems, with the improvement depending on the relative accuracy $\varepsilon$ and the locality $k$. In this work, we present faster exponential quantum algorithms for these problems, where the binary entropy function governs the runtime exponent. For sufficiently small $\varepsilon/k$, our algorithms improve the exponent by a factor of $\log(k/\varepsilon)$ over [BGLGST, PRL 2025]. Our main technical result is an entropy-governed lower bound on the dimension of the Hamiltonian's low-energy subspace, obtained by depolarizing its ground state. For fixed $k$, this bound is optimal up to constant factors in the exponent. The same framework yields tighter bounds for Heisenberg, $XY$, and Ising models on arbitrary interaction graphs.}},
  author       = {{Gharibian, Sevag and Le Gall, Francois and Mataraarachchi, Ranitha and Tamaki, Suguru}},
  title        = {{{Near-Optimal Bounds on the Density of Low-Energy States of $k$-Local Hamiltonians and Faster Quantum Algorithms}}},
  year         = {{2026}},
}

@unpublished{67291,
  author       = {{Rudolph, Dorian and Motamedi, Arsalan and Sambrani, Dhruva and Reza Naeij, Hamid and Chabaud, Ulysse and Gharibian, Sevag and Mehraban, Saeed}},
  title        = {{{A physical and universal model of bosonic computations with Solovay-Kitaev theorem}}},
  year         = {{2026}},
}

@article{51160,
  abstract     = {{We rigorously derive novel and sharp finite-data error bounds for highly
sample-efficient Extended Dynamic Mode Decomposition (EDMD) for both i.i.d. and
ergodic sampling. In particular, we show all results in a very general setting
removing most of the typically imposed assumptions such that, among others,
discrete- and continuous-time stochastic processes as well as nonlinear partial
differential equations are contained in the considered system class. Besides
showing an exponential rate for i.i.d. sampling, we prove, to the best of our
knowledge, the first superlinear convergence rates for ergodic sampling of
deterministic systems. We verify sharpness of the derived error bounds by
conducting numerical simulations for highly-complex applications from molecular
dynamics and chaotic flame propagation.}},
  author       = {{Philipp, Friedrich M. and Schaller, Manuel and Boshoff, Septimus and Peitz, Sebastian and Nüske, Feliks and Worthmann, Karl}},
  journal      = {{Physica D: Nonlinear Phenomena}},
  title        = {{{Variance representations and convergence rates for data-driven approximations of Koopman operators}}},
  doi          = {{10.1016/j.physd.2026.135223}},
  volume       = {{492}},
  year         = {{2026}},
}

@article{53858,
  author       = {{Akhter, Junaid and Fährmann, Paul David and Sonntag, Konstantin and Peitz, Sebastian}},
  journal      = {{SIAM Review}},
  number       = {{3}},
  pages        = {{656--683}},
  publisher    = {{SIAM}},
  title        = {{{Common pitfalls to avoid while using multiobjective optimization in machine learning}}},
  doi          = {{10.1137/24M1658875}},
  volume       = {{68}},
  year         = {{2026}},
}

@inproceedings{67308,
  abstract     = {{Optimizing large-scale multibody systems is a challenging task, particularly in the presence of multiple conflicting criteria. To prevent high simulation costs, surrogate models constructed from a small number of expensive model evaluations are very popular. However, it is difficult to ensure the optimality of the obtained solutions using a single pre-computed model. We present a back-and-forth approach between surrogate modeling and multi-objective optimization, and we compare different strategies for optimization, sampling, and surrogate modeling, to identify the most promising approach in terms of computational efficiency and solution quality.}},
  author       = {{Amakor, Augustina Chidinma and Berkemeier, Manuel B. and Wohlleben, Meike Claudia and Sextro, Walter and Peitz, Sebastian}},
  booktitle    = {{Artificial Neural Networks and Machine Learning – ICANN 2025}},
  editor       = {{Senn, Walter and Sanguineti, Marcello and Saudargiene, Ausra and Tetko, Igor V. and Villa, Alessandro E. P. and Jirsa, Viktor and Bengio, Yoshua}},
  isbn         = {{978-3-032-04555-3}},
  keywords     = {{own, own-conference}},
  pages        = {{251–262}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Surrogate-Assisted Multi-objective Design of Complex Multibody Systems}}},
  doi          = {{10.1007/978-3-032-04555-3_21}},
  year         = {{2026}},
}

@inproceedings{67307,
  author       = {{Hotegni, Sedjro Salomon and Peitz, Sebastian}},
  booktitle    = {{14th International Conference on Learning Representations (ICLR)}},
  keywords     = {{own, own-conference}},
  title        = {{{SPREAD: Sampling-based Pareto front Refinement via Efficient Adaptive Diffusion}}},
  doi          = {{10.48550/arXiv.2509.21058}},
  year         = {{2026}},
}

@unpublished{67306,
  author       = {{Stenner, Jan and Harder, Hans and Peitz, Sebastian}},
  booktitle    = {{arXiv:2606.30238}},
  keywords     = {{own, own-preprint, erc}},
  title        = {{{Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection}}},
  year         = {{2026}},
}

@unpublished{67309,
  author       = {{Stenner, Jan and Kilian, Alexander and Peitz, Sebastian and de Meer, Hermann}},
  booktitle    = {{arXiv:2606.30316}},
  keywords     = {{own, own-preprint}},
  title        = {{{Toward an Energy-Optimized Operation of Data Centers Located in Wind Farms Using Reinforcement Learning}}},
  year         = {{2026}},
}

@inproceedings{67285,
  abstract     = {{This research provides a method for designing competenceoriented, modular workflows that support strategic decisionmaking in strategic product planning (SPP) under conditions of uncertainty and time pressure. Increasing digitalization and data availability require decision support systems that integrate analytical models while being tailored to the competencies of decision-makers. Based on a systematic literature review and stakeholder workshops, eight success factors for competency-oriented workflow integration are identified, including modularity, traceability, interoperability, adaptability, handling uncertainty, and user acceptance. Based on these factors, a five-step method is developed that links business processes, data sources, evaluation criteria, visualization formats, and graphical workflow implementation. Strategic and technical decision logic are integrated into a unified, modular framework using graphical modeling environments. The method is validated in workshops and demonstrates its applicability in time-critical, multi-criteria decision contexts. The results show improved transparency, adaptability, and practical usability of datadriven decision processes that support robust and traceable business decisions. }},
  author       = {{Gräßler, Iris and Özcan, Deniz}},
  booktitle    = {{24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE }},
  editor       = {{Gonzalez, Jose David Nunez and Romay, Manuel Grana}},
  isbn         = {{978-9-492859-40-2}},
  keywords     = {{Workflow, Decision Support, Strategic Product Planning, Decision-making}},
  location     = {{San Sebastian, Spain}},
  pages        = {{73--80}},
  title        = {{{Competence-Oriented Modular Workflow Design for Strategic Decisions}}},
  volume       = {{24}},
  year         = {{2026}},
}

@inproceedings{67284,
  abstract     = {{<jats:p>For foresightful strategic decisions in engineering and production, it is important to identify and classify operational engineering data inmanufacturing companies in terms of relevance and impact. Established methods like Scenario-Technique or roadmapping consider expertise of strategic decision-makers and central decision-making bodies by, for instance, workshops and interviews. There is no overarching approach for evaluating the variety of operational data sources and feed them into specific data processing pipelines targeting strategic decision support. Based on a systematic literature analysis and comprehensive industrial experience, requirements are derived. These requirements are used to develop a method to identify, classify and evaluate data for strategic decision-making. The method is validated in an industrial project. The aim is to exploit informal and fragmented data from operational levels into structured, transparent decision support for strategic players.</jats:p>}},
  author       = {{Gräßler, Iris and Özcan, Deniz}},
  booktitle    = {{AHFE International}},
  issn         = {{2771-0718}},
  location     = {{Paris}},
  publisher    = {{AHFE International}},
  title        = {{{Extended Exploitation of Data in Manufacturing Companies for Strategic Decision-Making}}},
  doi          = {{10.54941/ahfe1008175}},
  volume       = {{237}},
  year         = {{2026}},
}

@inproceedings{67286,
  abstract     = {{The effects of decisions in strategic product planning are usually far-reaching, but at the same time difficult to assess. Simulations help to make these effects more tangible. Until now, the use of simulation in strategic product planning has been limited to behavioral and innovation diffusion studies. This paper presents a process model for widening business models or planning upcoming product generations. It supports integrating the simulation of technical systems into decisionmaking processes to select the most suitable product for adaptation to new application scenarios. To this end, the characteristics of such new application scenarios are applied to existing product models in simulation, and the system behavior is evaluated based on key figures. This supports the comparison of different products and the selection of the product alternative requiring the least amount of modification. The process model enables decision-makers to systematically integrate simulation into the decision-making process and thus make more data-based decisions. }},
  author       = {{Gräßler, Iris and Özcan, Deniz and Döhner, Niklas}},
  booktitle    = {{24th INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE }},
  editor       = {{Gonzalez, Jose David Nunez and Romay, Manuel Grana}},
  isbn         = {{978-9-492859-40-2}},
  keywords     = {{Decision-making, Decision support systems, Mechanical engineering, System analysis, System engineering}},
  location     = {{San Sebastian, Spain}},
  pages        = {{65--72}},
  title        = {{{Leveraging System Simulation for Decision  Support in Strategic Product Planning}}},
  volume       = {{24}},
  year         = {{2026}},
}

@article{67325,
  abstract     = {{The influence of the hydrophilicity of mesoporous silica on wetting with water was investigated by comparing a standard hydrophilic MCM-41 and a partially hydrophobicized material obtained by trimethylsilylation of MCM-41. The materials were characterized using X-ray diffraction, N2 physisorption, thermogravimetric analysis, infrared spectroscopy, as well as 29Si and 13C solid-state nuclear magnetic resonance spectroscopy. Trimethylsilylation leads to a reduction of the pore diameter (determined using density functional theory) from 3.8 to 3.6 nm. Using proton solid-state nuclear magnetic resonance (NMR) under magic-angle spinning, it was found that the filling of these narrow pores with increasing amounts of water follows an axial mode, independent of surface hydrophilicity. The axial model of pore-filling is supported by the coexistence of two characteristic 1H NMR water signals, one from physisorbed water molecules, which can exchange protons with silanol groups, and one from bulk-like water in completely filled pores, where water molecules are in exchange between sites at the pore wall and sites closer to the center of the pore.}},
  author       = {{Zhao, Yanjing and Weinberger, Christian and Tiemann, Michael and Schmidt, Claudia}},
  issn         = {{2629-2742}},
  journal      = {{Analysis & Sensing}},
  number       = {{5}},
  publisher    = {{Wiley}},
  title        = {{{NMR Investigation of Water in Mesoporous Silica Materials With Different Surfaces}}},
  doi          = {{10.1002/anse.70109}},
  volume       = {{6}},
  year         = {{2026}},
}

@inbook{36895,
  author       = {{Webersen, Yvonne and Riese, Josef}},
  booktitle    = {{ Demokratiebildung in der Lehrkräftebildung. Positionen – Potenziale – Perspektiven.}},
  editor       = {{Becher, Andrea and Bloh, Bea and Herzig, Bardo and Pollmeier, Pascal}},
  publisher    = {{Waxmann}},
  title        = {{{Wie funktionieren (Pseudo)wissenschaften? Ein Seminarkonzept für angehende Lehrkräfte naturwissenschaftlicher Fächer}}},
  doi          = {{https://doi.org/10.31244/9783818852290 }},
  volume       = {{3}},
  year         = {{2026}},
}

@inproceedings{67333,
  author       = {{Zarkalam, Darya and Rotthaler, Anna Lena and Simko, Lucy and Acar, Yasemin}},
  booktitle    = {{Twenty-Second Symposium on Usable Privacy and Security (SOUPS 2026)}},
  pages        = {{141–160}},
  title        = {{{From Thrift Stores to Digital Storefronts: Users’ Perspectives on Privacy and Security of Online Second-Hand Shopping in Germany}}},
  year         = {{2026}},
}

@misc{67352,
  author       = {{Freier, Eric Samson }},
  title        = {{{Agentic VirtuTutor: Implementation of an agentic embodied AI learning assistant and comparison with a non-agentic implementation in the serious VR game VirtuChemLab}}},
  year         = {{2026}},
}

@misc{67351,
  author       = {{Jones, Merlin Frederic }},
  title        = {{{Dijkstra - Shortest Path Search mit ganzen Zahlen}}},
  year         = {{2026}},
}

@article{67355,
  abstract     = {{<jats:title>ABSTRACT:</jats:title>
                  <jats:p>OEMs are shifting from product-centric offerings toward smart services, but adoption is still hindered by technical development barriers. We conduct a systematic literature review of peer-reviewed studies with original industrial evidence and identify eight barrier categories across data, semantics, integration, governance and modularity. We map them onto a smart-service architecture and key analytics roles, and relate them to GenAI building blocks such as LLMs and knowledge graphs, outlining a research agenda for overcoming technical barriers towards scalable OEM smart service development.</jats:p>}},
  author       = {{Heuwinkel, Tim and Weller, Julian and Gabriel, Stefan and Kürpick, Christian and Dumitrescu, Roman}},
  issn         = {{2732-527X}},
  journal      = {{Proceedings of the Design Society}},
  pages        = {{2343--2352}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Still no smart service? A review of technical barriers to smart service adoption in the GenAI era}}},
  doi          = {{10.1017/pds.2026.10592}},
  volume       = {{6}},
  year         = {{2026}},
}

@article{67354,
  author       = {{Twardzik, Jan Luca and Schreiner, Nick and Cichon, Gerrit and Kürpick, Christian and Dumitrescu, Roman}},
  issn         = {{0921-3449}},
  journal      = {{Resources, Conservation and Recycling}},
  publisher    = {{Elsevier BV}},
  title        = {{{Embedding environmental and circularity metrics in product development decisions: A structured decision-support approach for early-stage industrial concept evaluation}}},
  doi          = {{10.1016/j.resconrec.2026.109112}},
  volume       = {{235}},
  year         = {{2026}},
}

@article{67274,
  author       = {{Münzmay, Andreas and Müller, Kai-Hinrich}},
  issn         = {{0177-4182}},
  journal      = {{Musiktheorie. Zeitschrift für Musikwissenschaft (Themenheft: Musikedition und ihre Sichtbarkeiten. Wissenschaft – Musikpraxis – Öffentlichkeit)}},
  number       = {{2}},
  pages        = {{138--152}},
  title        = {{{Digitale Musikeditionen zwischen Open Science und Aufführungspraxis. Ein Gespräch}}},
  volume       = {{41}},
  year         = {{2026}},
}