@article{nokey,

title = {Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations},

author = {M. Aehle, M. Novák, V. Vassilev, N. R. Gauger, L. Heinrich, M. Kagan, D. Lange},

doi = {10.1016/j.cpc.2024.109491},

year  = {2025},

date = {2025-04-01},

urldate = {2025-04-01},

journal = {Computer Physics Communications},

volume = {309},

pages = {109491},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{BGAG2025,

title = {Hybrid parallel discrete adjoints in SU2},

author = {J. Blühdorn, P. Gomes, M. Aehle, N. R. Gauger},

doi = {10.1016/j.compfluid.2024.106528},

year  = {2025},

date = {2025-01-02},

urldate = {2025-01-02},

journal = {Computers & Fluids},

volume = {289},

number = {106528},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Development of the trigger-controlling system for the proton computed tomography prototype},

author = {N. Ritjoho, P. Phumara, Y. Buanill, P. Boontueng, A. Songmoolnak, N. Laojamnongwong, L. Charoonratana, T. Sanghangthum, D. Röhrich, A. Schilling, M. Aehle, J. Alme, G. G. Barnaföldi, G. Bíró, T. Bodova, V. Borshchov, A. van den Brink, V. Eikeland, G. Feofilov, C. Garth, N. R. Gauger, et al.},

doi = {10.1016/j.nima.2024.170125},

isbn = {0168-9002},

year  = {2024},

date = {2024-12-10},

urldate = {2024-12-10},

journal = {Nuclear Instruments and Methods in Physics Research Section A},

pages = {170125},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{aerospace11080607,

title = {Nonlinear Surrogate Model Design for Aerodynamic Dataset Generation Based on Artificial Neural Networks},

author = {G. Suarez, E. Özkaya, N.R. Gauger, H. Steiner, M. Schäfer, D. Naumann},

doi = {10.3390/aerospace11080607},

issn = {2226-4310},

year  = {2024},

date = {2024-07-24},

urldate = {2024-07-24},

journal = {Aerospace},

volume = {11},

issue = {8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokeyr,

title = {Data-driven aerodynamic shape design with distributionally robust optimization approaches},

author = {L. Chen, J. Rottmayer, L. Kusch, N. R.Gauger, Y. Ye, },

url = {https://doi.org/10.1016/j.cma.2024.117131},

issn = {0045-7825},

year  = {2024},

date = {2024-06-15},

urldate = {2024-06-15},

journal = {Computer Methods in Applied Mechanics and Engineering},

volume = {429},

pages = {117131},

abstract = {We formulate and solve data-driven aerodynamic shape design problems with distributionally robust optimization (DRO) approaches. DRO aims to minimize the worst-case expected performance in a set of distributions that is informed by observed data with uncertainties. Building on the findings of the work Gotoh, et al. (2018), we study the connections between a class of DRO and robust design optimization, which is classically based on the mean–variance (standard deviation) optimization formulation pioneered by Taguchi. Our results provide a new perspective to the understanding and formulation of robust design optimization problems. It enables data-driven and statistically principled approaches to quantify the trade-offs between robustness and performance, in contrast to the classical robust design formulation that captures uncertainty only qualitatively. Our preliminary computational experiments on aerodynamic shape optimization in transonic turbulent flow show promising design results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Stochastic Aspects of Dynamical Low-Rank Approximation in the Context of Machine Learning},

author = {A. Hnatiuk, L. Kusch, J. Kusch, N. R. Gauger, A. Walther},

url = {https://optimization-online.org/?p=25971},

year  = {2024},

date = {2024-03-23},

urldate = {2024-03-23},

journal = {Optimization Online},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Adjoint-based design optimization of a Kenics static mixer},

author = {C.M. Ubal, N. Beishuizen, L. Kusch, J. van Oijen},

url = {https://doi.org/10.1016/j.rineng.2024.101856},

year  = {2024},

date = {2024-02-05},

urldate = {2024-02-05},

journal = {Results in Engineering},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {A gradient descent akin method for constrained optimization: algorithms and applications},

author = {L. Chen, K. U. Bletzinger, N. R.Gauger, Y. Ye, },

url = {https://doi.org/10.1080/10556788.2023.2285450},

year  = {2024},

date = {2024-01-16},

urldate = {2024-01-16},

journal = {Optimization Methods and Software},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Gradient Enhanced Surrogate Modeling Framework for Aerodynamic Design Optimization},

author = {E. Özkaya , J. Rottmayer, N.R. Gauger},

doi = {10.2514/6.2024-2670},

year  = {2024},

date = {2024-01-04},

urldate = {2024-01-04},

journal = {AIAA 2024-2670},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KKG2023,

title = {Towards Neural Charged Particle Tracking in Digital Tracking Calorimeters With Reinforcement Learning},

author = {T. Kortus, R. Keidel, N.R. Gauger, Bergen pCT Collaboration},

url = {https://doi.org/10.1109/TPAMI.2023.3305027},

doi = {10.1109/TPAMI.2023.3305027},

year  = {2023},

date = {2023-12-01},

urldate = {2023-12-01},

journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},

volume = {45},

number = {12},

pages = {15820-15833},

howpublished = {TechRxiv 21717323.v1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{aehle_exploration_2023,

title = {Exploration of Differentiability in a Proton Computed Tomography Simulation Framework},

author = {M. Aehle, J. Alme, G. Barnaföldi, J. Blühdorn, T. Bodova, V. Borshchov, A. van den Brink, V. Eikeland, G. Feofilov, C. Garth, N. R. Gauger, et al.},

url = {https://iopscience.iop.org/article/10.1088/1361-6560/ad0bdd},

doi = {10.1088/1361-6560/ad0bdd},

year  = {2023},

date = {2023-11-10},

urldate = {2023-11-10},

journal = {Physics in Medicine and Biology},

volume = {68},

number = {24},

pages = {244002},

howpublished = {arXiv:2202.05551},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SchillingEtAl2023,

title = {Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter},

author = {A. Schilling, M. Aehle, J. Alme, G. Barnaföldi, T. Bodova, V. Borshchov, A. van den Brink, V. Eikeland, G. Feofilov, C. Garth, N.R. Gauger, et al.},

url = {https://iopscience.iop.org/article/10.1088/1361-6560/acf5c2/pdf},

year  = {2023},

date = {2023-09-20},

urldate = {2023-09-20},

journal = {Phys. Med. Biol.},

volume = {68},

number = {194001},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{MODE2023a,

title = {Toward the end-to-end optimization of particle physics instruments with differentiable programming},

author = {T. Dorigo, A. Giammanco, P. Vischia, M. Aehle, M. Bawaj, A. Boldyrev, P. de Castro Manzano, D. Derkach, J. Donini, A. Edelen, F. Fanzago, N.R. Gauger, et al.},

url = {https://doi.org/10.1016/j.revip.2023.100085},

year  = {2023},

date = {2023-05-25},

urldate = {2023-05-25},

journal = {Reviews in Physics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SBGetal2023,

title = {On recent developments for efficient turbomachinery design using algorithmic differentiation},

author = {M. Sagebaum, J. Blühdorn, N.R. Gauger, J. Backhaus, C. Frey, G. Geiser, F. Bayer, E. Kügeler, C. Battistoni, M. Nagel},

doi = {10.29008/ETC2023-346 },

year  = {2023},

date = {2023-04-26},

urldate = {2023-04-26},

journal = {Proceedings of 15th European Conference on Turbomachinery Fluid Dynamics & Thermodynamics (ETC15)},

number = {ETC2023-346},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SaGau2023,

title = {Aggregated type handling in CoDiPack},

author = {M. Sagebaum, N.R. Gauger},

doi = {10.1002/pamm.202200208},

year  = {2023},

date = {2023-03-27},

urldate = {2023-03-01},

journal = {Proc. Appl. Math. Mech.},

volume = {22},

number = {e202200208},

issue = {1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Event-Based Automatic Differentiation of OpenMP with OpDiLib},

author = {J. Blühdorn, M. Sagebaum, N. R. Gauger},

doi = {10.1145/3570159},

year  = {2023},

date = {2023-03-21},

urldate = {2023-03-21},

journal = {ACM Transactions on Mathematical Software},

volume = {49},

number = {3},

issue = {1},

pages = {1--31},

abstract = {We present the new software OpDiLib, a universal add-on for classical operator overloading AD tools that enables the automatic differentiation (AD) of OpenMP parallelized code. With it, we establish support for OpenMP features in a reverse mode operator overloading AD tool to an extent that was previously only reported on in source transformation tools. We achieve this with an event-based implementation ansatz that is unprecedented in AD. Combined with modern OpenMP features around OMPT, we demonstrate how it can be used to achieve differentiation without any additional modifications of the source code; neither do we impose a priori restrictions on the data access patterns, which makes OpDiLib highly applicable. For further performance optimizations, restrictions like atomic updates on adjoint variables can be lifted in a fine-grained manner. OpDiLib can also be applied in a semi-automatic fashion via a macro interface, which supports compilers that do not implement OMPT. We demonstrate the applicability of OpDiLib for a pure operator overloading approach in a hybrid parallel environment. We quantify the cost of atomic updates on adjoint variables and showcase the speedup and scaling that can be achieved with the different configurations of OpDiLib in both the forward and the reverse pass.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The Bergen proton CT system},

author = {M. Aehle, J. Alme, G.G. Barnaföldi, T. Bodova, V. Borshchov, A. van den Brink, M. Chaar, V. Eikeland, G. Feofilov, C. Garth, N. R. Gauger, G. Genov, O. Grøttvik, H. Helstrup, S. Igolkin, R. Keidel, et al.},

url = {https://iopscience.iop.org/article/10.1088/1748-0221/18/02/C02051},

year  = {2023},

date = {2023-02-01},

urldate = {2023-02-01},

journal = {Journal of Instrumentation},

volume = {18},

number = {2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DiGauSchmi2022,

title = {Combining Sobolev smoothing with parameterized shape optimization},

author = {T. Dick, N.R. Gauger, S. Schmidt},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0045793022001839},

doi = {https://doi.org/10.1016/j.compfluid.2022.105568},

year  = {2022},

date = {2022-08-15},

urldate = {2022-08-15},

journal = {Computers & Fluids},

volume = {Vol. 244},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{BuDeGa2022,

title = {Stabilization and Acceleration of Coupled Discrete Adjoint Solvers in Multi-Disciplinary Optimization},

author = {O. Burghardt, P. Dehpanah, N.R. Gauger},

doi = {https://doi.org/10.2514/6.2022-3787},

year  = {2022},

date = {2022-06-29},

urldate = {2022-06-29},

journal = {AIAA 2022-3787},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RaGrueGau2022ab,

title = {Scalable Hybrid Parallel ILU Preconditioner to Solve Sparse Linear Systems},

author = {R. Ram, D. Grünewald, N.R. Gauger},

url = {https://doi.org/10.1007/978-3-031-06156-1_46},

year  = {2022},

date = {2022-06-09},

urldate = {2022-06-09},

journal = {Parallel Processing Workshops. Euro-Par 2021. Lecture Notes in Computer Science, Vol. 13098. Springer, Cham},

pages = {540-544},

keywords = {},

pubstate = {published},

tppubtype = {article}

}