[{"main_file_link":[{"url":"https://arxiv.org/abs/2606.30238","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"67306","user_id":"47427","title":"Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection","year":"2026","status":"public","author":[{"full_name":"Stenner, Jan","last_name":"Stenner","first_name":"Jan"},{"id":"98879","first_name":"Hans","last_name":"Harder","full_name":"Harder, Hans"},{"full_name":"Peitz, Sebastian","orcid":"0000-0002-3389-793X","last_name":"Peitz","first_name":"Sebastian","id":"47427"}],"date_updated":"2026-10-01T12:01:23Z","date_created":"2026-10-01T12:00:58Z","type":"preprint","keyword":["own","own-preprint","erc"],"oa":"1","department":[{"_id":"655"}],"publication":"arXiv:2606.30238","citation":{"short":"J. Stenner, H. Harder, S. Peitz, ArXiv:2606.30238 (2026).","chicago":"Stenner, Jan, Hans Harder, and Sebastian Peitz. “Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection.” <i>ArXiv:2606.30238</i>, 2026.","apa":"Stenner, J., Harder, H., &#38; Peitz, S. (2026). Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection. In <i>arXiv:2606.30238</i>.","ieee":"J. Stenner, H. Harder, and S. Peitz, “Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection,” <i>arXiv:2606.30238</i>. 2026.","ama":"Stenner J, Harder H, Peitz S. Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection. <i>arXiv:260630238</i>. Published online 2026.","bibtex":"@article{Stenner_Harder_Peitz_2026, title={Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection}, journal={arXiv:2606.30238}, author={Stenner, Jan and Harder, Hans and Peitz, Sebastian}, year={2026} }","mla":"Stenner, Jan, et al. “Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection.” <i>ArXiv:2606.30238</i>, 2026."}},{"department":[{"_id":"655"}],"type":"journal_article","keyword":["own","own-journal","erc"],"date_created":"2026-10-01T11:55:20Z","abstract":[{"lang":"eng","text":"Data-driven surrogate models provide fast and fully differentiable approximations of complex dynamical systems. In this work, we develop such surrogates for the Rayleigh–Bénard convection (RBC), which governs thermally driven flows in natural and industrial environments. Specifically, the proposed models approximate the discrete-time flow map of the RBC system, advancing the full system state by a fixed time step. We train Fourier Neural Operator (FNO)–based models to learn the dynamics of RBC in two and three dimensions and compare them to a convolutional U-Net baseline and a Koopman-based Linear Recurrent Autoencoder Network (LRAN). The two-dimensional system serves as a baseline for the more challenging three-dimensional case, which exhibits increased spatial complexity and turbulent dynamics. Across all settings, FNO-based models consistently outperform the LRAN, while achieving performance comparable to the U-Net in several regimes. Incorporating spatio-temporal inputs via FNOs leads to improved long-term prediction accuracy, particularly for turbulent flows. The physical fidelity of the predictions is assessed using convective heat flux statistics, profiles, and fluctuations, showing that FNOs most closely reproduce the ground-truth flow statistics. In addition, we demonstrate that FNOs enable zero-shot super-resolution across unseen spatial discretizations, a capability not shared by the convolutional baselines. These results highlight the potential of neural operator–based models as accurate, physically consistent, and resolution-independent surrogates for downstream tasks such as flow control."}],"citation":{"mla":"Markmann, Thorben, et al. “Fourier Neural Operators as Data-Driven Surrogates for Two- and Three-Dimensional Rayleigh–Bénard Convection.” <i>Neurocomputing</i>, vol. 679, 2026, p. 133201, doi:<a href=\"https://doi.org/10.1016/j.neucom.2026.133201\">10.1016/j.neucom.2026.133201</a>.","bibtex":"@article{Markmann_Straat_Peitz_Hammer_2026, title={Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–Bénard convection}, volume={679}, DOI={<a href=\"https://doi.org/10.1016/j.neucom.2026.133201\">10.1016/j.neucom.2026.133201</a>}, journal={Neurocomputing}, author={Markmann, Thorben and Straat, Michiel and Peitz, Sebastian and Hammer, Barbara}, year={2026}, pages={133201} }","ama":"Markmann T, Straat M, Peitz S, Hammer B. Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–Bénard convection. <i>Neurocomputing</i>. 2026;679:133201. doi:<a href=\"https://doi.org/10.1016/j.neucom.2026.133201\">10.1016/j.neucom.2026.133201</a>","ieee":"T. Markmann, M. Straat, S. Peitz, and B. Hammer, “Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–Bénard convection,” <i>Neurocomputing</i>, vol. 679, p. 133201, 2026, doi: <a href=\"https://doi.org/10.1016/j.neucom.2026.133201\">10.1016/j.neucom.2026.133201</a>.","apa":"Markmann, T., Straat, M., Peitz, S., &#38; Hammer, B. (2026). Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–Bénard convection. <i>Neurocomputing</i>, <i>679</i>, 133201. <a href=\"https://doi.org/10.1016/j.neucom.2026.133201\">https://doi.org/10.1016/j.neucom.2026.133201</a>","short":"T. Markmann, M. Straat, S. Peitz, B. Hammer, Neurocomputing 679 (2026) 133201.","chicago":"Markmann, Thorben, Michiel Straat, Sebastian Peitz, and Barbara Hammer. “Fourier Neural Operators as Data-Driven Surrogates for Two- and Three-Dimensional Rayleigh–Bénard Convection.” <i>Neurocomputing</i> 679 (2026): 133201. <a href=\"https://doi.org/10.1016/j.neucom.2026.133201\">https://doi.org/10.1016/j.neucom.2026.133201</a>."},"publication":"Neurocomputing","volume":679,"doi":"10.1016/j.neucom.2026.133201","user_id":"47427","language":[{"iso":"eng"}],"_id":"67302","page":"133201","intvolume":"       679","date_updated":"2026-10-01T11:56:04Z","author":[{"full_name":"Markmann, Thorben","first_name":"Thorben","last_name":"Markmann"},{"last_name":"Straat","first_name":"Michiel","full_name":"Straat, Michiel"},{"last_name":"Peitz","orcid":"0000-0002-3389-793X","first_name":"Sebastian","full_name":"Peitz, Sebastian","id":"47427"},{"first_name":"Barbara","last_name":"Hammer","full_name":"Hammer, Barbara"}],"publication_identifier":{"issn":["0925-2312"]},"year":"2026","title":"Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–Bénard convection","status":"public"},{"status":"public","user_id":"47427","volume":331,"editor":[{"last_name":"Sukhatme","first_name":"Gaurav","full_name":"Sukhatme, Gaurav"},{"last_name":"Lindemann","first_name":"Lars","full_name":"Lindemann, Lars"},{"full_name":"Tu, Stephen","last_name":"Tu","first_name":"Stephen"},{"full_name":"Wierman, Adam","first_name":"Adam","last_name":"Wierman"},{"full_name":"Atanasov, Nikolay","first_name":"Nikolay","last_name":"Atanasov"}],"page":"1601–1619","_id":"67299","publisher":"PMLR","citation":{"apa":"Harder, H., Vishwasrao, A., Guastoni, L., Vinuesa, R., &#38; Peitz, S. (2026). Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems. In G. Sukhatme, L. Lindemann, S. Tu, A. Wierman, &#38; N. Atanasov (Eds.), <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i> (Vol. 331, pp. 1601–1619). PMLR. <a href=\"https://doi.org/10.48550/arXiv.2511.04641\">https://doi.org/10.48550/arXiv.2511.04641</a>","ieee":"H. Harder, A. Vishwasrao, L. Guastoni, R. Vinuesa, and S. Peitz, “Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems,” in <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>, 2026, vol. 331, pp. 1601–1619, doi: <a href=\"https://doi.org/10.48550/arXiv.2511.04641\">10.48550/arXiv.2511.04641</a>.","chicago":"Harder, Hans, Abhijeet Vishwasrao, Luca Guastoni, Ricardo Vinuesa, and Sebastian Peitz. “Efficient Probabilistic Surrogate Modeling Techniques for Partially-Observed Large-Scale Dynamical Systems.” In <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>, edited by Gaurav Sukhatme, Lars Lindemann, Stephen Tu, Adam Wierman, and Nikolay Atanasov, 331:1601–1619. Proceedings of Machine Learning Research. PMLR, 2026. <a href=\"https://doi.org/10.48550/arXiv.2511.04641\">https://doi.org/10.48550/arXiv.2511.04641</a>.","short":"H. Harder, A. Vishwasrao, L. Guastoni, R. Vinuesa, S. Peitz, in: G. Sukhatme, L. Lindemann, S. Tu, A. Wierman, N. Atanasov (Eds.), Proceedings of The 8th Annual Learning for Dynamics and Control Conference, PMLR, 2026, pp. 1601–1619.","mla":"Harder, Hans, et al. “Efficient Probabilistic Surrogate Modeling Techniques for Partially-Observed Large-Scale Dynamical Systems.” <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>, edited by Gaurav Sukhatme et al., vol. 331, PMLR, 2026, pp. 1601–1619, doi:<a href=\"https://doi.org/10.48550/arXiv.2511.04641\">10.48550/arXiv.2511.04641</a>.","ama":"Harder H, Vishwasrao A, Guastoni L, Vinuesa R, Peitz S. Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems. In: Sukhatme G, Lindemann L, Tu S, Wierman A, Atanasov N, eds. <i>Proceedings of The 8th Annual Learning for Dynamics and Control Conference</i>. Vol 331. Proceedings of Machine Learning Research. PMLR; 2026:1601–1619. doi:<a href=\"https://doi.org/10.48550/arXiv.2511.04641\">10.48550/arXiv.2511.04641</a>","bibtex":"@inproceedings{Harder_Vishwasrao_Guastoni_Vinuesa_Peitz_2026, series={Proceedings of Machine Learning Research}, title={Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems}, volume={331}, DOI={<a href=\"https://doi.org/10.48550/arXiv.2511.04641\">10.48550/arXiv.2511.04641</a>}, booktitle={Proceedings of The 8th Annual Learning for Dynamics and Control Conference}, publisher={PMLR}, author={Harder, Hans and Vishwasrao, Abhijeet and Guastoni, Luca and Vinuesa, Ricardo and Peitz, Sebastian}, editor={Sukhatme, Gaurav and Lindemann, Lars and Tu, Stephen and Wierman, Adam and Atanasov, Nikolay}, year={2026}, pages={1601–1619}, collection={Proceedings of Machine Learning Research} }"},"oa":"1","date_updated":"2026-10-01T11:52:48Z","intvolume":"       331","year":"2026","title":"Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems","author":[{"id":"98879","full_name":"Harder, Hans","last_name":"Harder","first_name":"Hans"},{"full_name":"Vishwasrao, Abhijeet","first_name":"Abhijeet","last_name":"Vishwasrao"},{"last_name":"Guastoni","first_name":"Luca","full_name":"Guastoni, Luca"},{"full_name":"Vinuesa, Ricardo","last_name":"Vinuesa","first_name":"Ricardo"},{"id":"47427","full_name":"Peitz, Sebastian","first_name":"Sebastian","last_name":"Peitz","orcid":"0000-0002-3389-793X"}],"doi":"10.48550/arXiv.2511.04641","main_file_link":[{"url":"https://openreview.net/pdf?id=Z9srtyqVLE","open_access":"1"}],"language":[{"iso":"eng"}],"series_title":"Proceedings of Machine Learning Research","publication":"Proceedings of The 8th Annual Learning for Dynamics and Control Conference","type":"conference","keyword":["own","own-conference","erc"],"department":[{"_id":"655"}],"date_created":"2026-10-01T11:51:57Z"},{"date_created":"2026-10-01T11:59:35Z","keyword":["own","own-conference","erc"],"type":"conference","department":[{"_id":"655"}],"oa":"1","publication":"International Conference on Machine Learning (ICML)","citation":{"ieee":"J. Becktepe, A. Franz, N. Thuerey, and S. Peitz, “Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control,” 2026, doi: <a href=\"https://doi.org/10.48550/arXiv.2601.15015\">10.48550/arXiv.2601.15015</a>.","apa":"Becktepe, J., Franz, A., Thuerey, N., &#38; Peitz, S. (2026). Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control. <i>International Conference on Machine Learning (ICML)</i>. <a href=\"https://doi.org/10.48550/arXiv.2601.15015\">https://doi.org/10.48550/arXiv.2601.15015</a>","short":"J. Becktepe, A. Franz, N. Thuerey, S. Peitz, in: International Conference on Machine Learning (ICML), 2026.","chicago":"Becktepe, Jannis, Aleksandra Franz, Nils Thuerey, and Sebastian Peitz. “Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control.” In <i>International Conference on Machine Learning (ICML)</i>, 2026. <a href=\"https://doi.org/10.48550/arXiv.2601.15015\">https://doi.org/10.48550/arXiv.2601.15015</a>.","mla":"Becktepe, Jannis, et al. “Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control.” <i>International Conference on Machine Learning (ICML)</i>, 2026, doi:<a href=\"https://doi.org/10.48550/arXiv.2601.15015\">10.48550/arXiv.2601.15015</a>.","bibtex":"@inproceedings{Becktepe_Franz_Thuerey_Peitz_2026, title={Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control}, DOI={<a href=\"https://doi.org/10.48550/arXiv.2601.15015\">10.48550/arXiv.2601.15015</a>}, booktitle={International Conference on Machine Learning (ICML)}, author={Becktepe, Jannis and Franz, Aleksandra and Thuerey, Nils and Peitz, Sebastian}, year={2026} }","ama":"Becktepe J, Franz A, Thuerey N, Peitz S. Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control. In: <i>International Conference on Machine Learning (ICML)</i>. ; 2026. doi:<a href=\"https://doi.org/10.48550/arXiv.2601.15015\">10.48550/arXiv.2601.15015</a>"},"main_file_link":[{"url":"https://safe-autonomous-systems.github.io/fluidgym/","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"67305","user_id":"47427","doi":"10.48550/arXiv.2601.15015","year":"2026","status":"public","title":"Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control","author":[{"first_name":"Jannis","last_name":"Becktepe","full_name":"Becktepe, Jannis"},{"first_name":"Aleksandra","last_name":"Franz","full_name":"Franz, Aleksandra"},{"full_name":"Thuerey, Nils","first_name":"Nils","last_name":"Thuerey"},{"full_name":"Peitz, Sebastian","last_name":"Peitz","orcid":"0000-0002-3389-793X","first_name":"Sebastian","id":"47427"}],"date_updated":"2026-10-01T12:00:51Z"},{"main_file_link":[{"url":"https://arxiv.org/abs/2603.26464","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"67298","user_id":"47427","year":"2026","status":"public","title":"Automatic feature identification in least-squares policy iteration using the Koopman operator framework","author":[{"last_name":"Mugisho Zagabe","first_name":"Christian","full_name":"Mugisho Zagabe, Christian"},{"id":"47427","first_name":"Sebastian","last_name":"Peitz","orcid":"0000-0002-3389-793X","full_name":"Peitz, Sebastian"}],"date_updated":"2026-10-01T11:51:41Z","date_created":"2026-10-01T11:50:28Z","keyword":["own","own-preprint","erc"],"type":"preprint","department":[{"_id":"655"}],"oa":"1","publication":"arXiv:2603.26464","citation":{"mla":"Mugisho Zagabe, Christian, and Sebastian Peitz. “Automatic Feature Identification in Least-Squares Policy Iteration Using the Koopman Operator Framework.” <i>ArXiv:2603.26464</i>, 2026.","ama":"Mugisho Zagabe C, Peitz S. Automatic feature identification in least-squares policy iteration using the Koopman operator framework. <i>arXiv:260326464</i>. Published online 2026.","bibtex":"@article{Mugisho Zagabe_Peitz_2026, title={Automatic feature identification in least-squares policy iteration using the Koopman operator framework}, journal={arXiv:2603.26464}, author={Mugisho Zagabe, Christian and Peitz, Sebastian}, year={2026} }","apa":"Mugisho Zagabe, C., &#38; Peitz, S. (2026). Automatic feature identification in least-squares policy iteration using the Koopman operator framework. In <i>arXiv:2603.26464</i>.","ieee":"C. Mugisho Zagabe and S. Peitz, “Automatic feature identification in least-squares policy iteration using the Koopman operator framework,” <i>arXiv:2603.26464</i>. 2026.","short":"C. Mugisho Zagabe, S. Peitz, ArXiv:2603.26464 (2026).","chicago":"Mugisho Zagabe, Christian, and Sebastian Peitz. “Automatic Feature Identification in Least-Squares Policy Iteration Using the Koopman Operator Framework.” <i>ArXiv:2603.26464</i>, 2026."}},{"date_updated":"2026-10-01T11:59:27Z","title":"Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection","year":"2026","status":"public","author":[{"first_name":"Tim","last_name":"Plotzki","full_name":"Plotzki, Tim"},{"first_name":"Sebastian","orcid":"0000-0002-3389-793X","last_name":"Peitz","full_name":"Peitz, Sebastian","id":"47427"}],"user_id":"47427","main_file_link":[{"url":"https://arxiv.org/abs/2603.28074","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"67304","publication":"arXiv:2603.28074","citation":{"mla":"Plotzki, Tim, and Sebastian Peitz. “Koopman-Based Surrogate Modeling for Reinforcement-Learning-Control of Rayleigh-Benard Convection.” <i>ArXiv:2603.28074</i>, 2026.","ama":"Plotzki T, Peitz S. Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection. <i>arXiv:260328074</i>. Published online 2026.","bibtex":"@article{Plotzki_Peitz_2026, title={Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection}, journal={arXiv:2603.28074}, author={Plotzki, Tim and Peitz, Sebastian}, year={2026} }","apa":"Plotzki, T., &#38; Peitz, S. (2026). Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection. In <i>arXiv:2603.28074</i>.","ieee":"T. Plotzki and S. Peitz, “Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection,” <i>arXiv:2603.28074</i>. 2026.","chicago":"Plotzki, Tim, and Sebastian Peitz. “Koopman-Based Surrogate Modeling for Reinforcement-Learning-Control of Rayleigh-Benard Convection.” <i>ArXiv:2603.28074</i>, 2026.","short":"T. Plotzki, S. Peitz, ArXiv:2603.28074 (2026)."},"keyword":["own","own-preprint","erc"],"type":"preprint","oa":"1","department":[{"_id":"655"}],"date_created":"2026-10-01T11:59:03Z"},{"year":"2025","title":"Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders","status":"public","author":[{"last_name":"Fromme","first_name":"Fynn","full_name":"Fromme, Fynn"},{"last_name":"Allen-Blanchette","first_name":"Christine","full_name":"Allen-Blanchette, Christine"},{"full_name":"Harder, Hans","last_name":"Harder","first_name":"Hans","id":"98879"},{"full_name":"Peitz, Sebastian","first_name":"Sebastian","last_name":"Peitz","orcid":"0000-0002-3389-793X","id":"47427"}],"date_updated":"2026-10-01T12:06:45Z","_id":"67318","language":[{"iso":"eng"}],"user_id":"47427","publication":"arXiv:2505.13569","citation":{"chicago":"Fromme, Fynn, Christine Allen-Blanchette, Hans Harder, and Sebastian Peitz. “Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders.” <i>ArXiv:2505.13569</i>, 2025.","short":"F. Fromme, C. Allen-Blanchette, H. Harder, S. Peitz, ArXiv:2505.13569 (2025).","apa":"Fromme, F., Allen-Blanchette, C., Harder, H., &#38; Peitz, S. (2025). Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders. In <i>arXiv:2505.13569</i>.","ieee":"F. Fromme, C. Allen-Blanchette, H. Harder, and S. Peitz, “Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders,” <i>arXiv:2505.13569</i>. 2025.","ama":"Fromme F, Allen-Blanchette C, Harder H, Peitz S. Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders. <i>arXiv:250513569</i>. Published online 2025.","bibtex":"@article{Fromme_Allen-Blanchette_Harder_Peitz_2025, title={Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders}, journal={arXiv:2505.13569}, author={Fromme, Fynn and Allen-Blanchette, Christine and Harder, Hans and Peitz, Sebastian}, year={2025} }","mla":"Fromme, Fynn, et al. “Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders.” <i>ArXiv:2505.13569</i>, 2025."},"date_created":"2026-10-01T12:06:29Z","keyword":["own","own-preprint","erc"],"type":"preprint","department":[{"_id":"655"}]}]