@article{HeinzeDipankarHenkenetal.2017, author = {Heinze, Rieke and Dipankar, Anurag and Henken, Cintia Carbajal and Moseley, Christopher and Sourdeval, Odran and Tr{\"o}mel, Silke and Xie, Xinxin and Adamidis, Panos and Ament, Felix and Baars, Holger and Barthlott, Christian and Behrendt, Andreas and Blahak, Ulrich and Bley, Sebastian and Brdar, Slavko and Brueck, Matthias and Crewell, Susanne and Deneke, Hartwig and Di Girolamo, Paolo and Evaristo, Raquel and Fischer, J{\"u}rgen and Frank, Christopher and Friederichs, Petra and G{\"o}cke, Tobias and Gorges, Ksenia and Hande, Luke and Hanke, Moritz and Hansen, Akio and Hege, Hans-Christian and Hose, Corinna and Jahns, Thomas and Kalthoff, Norbert and Klocke, Daniel and Kneifel, Stefan and Knippertz, Peter and Kuhn, Alexander and van Laar, Thriza and Macke, Andreas and Maurer, Vera and Mayer, Bernhard and Meyer, Catrin I. and Muppa, Shravan K. and Neggers, Roeland A. J. and Orlandi, Emiliano and Pantillon, Florian and Pospichal, Bernhard and R{\"o}ber, Niklas and Scheck, Leonhard and Seifert, Axel and Seifert, Patric and Senf, Fabian and Siligam, Pavan and Simmer, Clemens and Steinke, Sandra and Stevens, Bjorn and Wapler, Kathrin and Weniger, Michael and Wulfmeyer, Volker and Z{\"a}ngl, G{\"u}nther and Zhang, Dan and Quaas, Johannes}, title = {Large-eddy simulations over Germany using ICON: a comprehensive evaluation}, volume = {143}, journal = {Quarterly Journal of the Royal Meteorological Society}, number = {702}, doi = {10.1002/qj.2947}, pages = {69 -- 100}, year = {2017}, abstract = {Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary-layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.}, language = {en} } @misc{FischerGoetschelWeiser2017, author = {Fischer, Lisa and G{\"o}tschel, Sebastian and Weiser, Martin}, title = {Lossy data compression reduces communication time in hybrid time-parallel integrators}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-63961}, year = {2017}, abstract = {Parallel in time methods for solving initial value problems are a means to increase the parallelism of numerical simulations. Hybrid parareal schemes interleaving the parallel in time iteration with an iterative solution of the individual time steps are among the most efficient methods for general nonlinear problems. Despite the hiding of communication time behind computation, communication has in certain situations a significant impact on the total runtime. Here we present strict, yet no sharp, error bounds for hybrid parareal methods with inexact communication due to lossy data compression, and derive theoretical estimates of the impact of compression on parallel efficiency of the algorithms. These and some computational experiments suggest that compression is a viable method to make hybrid parareal schemes robust with respect to low bandwidth setups.}, language = {en} } @article{FischerGoetschelWeiser2018, author = {Fischer, Lisa and G{\"o}tschel, Sebastian and Weiser, Martin}, title = {Lossy data compression reduces communication time in hybrid time-parallel integrators}, volume = {19}, journal = {Comput. Vis. Sci.}, number = {1}, doi = {10.1007/s00791-018-0293-2}, pages = {19 -- 30}, year = {2018}, abstract = {Parallel in time methods for solving initial value problems are a means to increase the parallelism of numerical simulations. Hybrid parareal schemes interleaving the parallel in time iteration with an iterative solution of the individual time steps are among the most efficient methods for general nonlinear problems. Despite the hiding of communication time behind computation, communication has in certain situations a significant impact on the total runtime. Here we present strict, yet no sharp, error bounds for hybrid parareal methods with inexact communication due to lossy data compression, and derive theoretical estimates of the impact of compression on parallel efficiency of the algorithms. These and some computational experiments suggest that compression is a viable method to make hybrid parareal schemes robust with respect to low bandwidth setups.}, language = {en} } @misc{Fischer2017, type = {Master Thesis}, author = {Fischer, Lisa}, title = {On the convergence of inexact time parallel time integration}, pages = {61}, year = {2017}, language = {en} } @masterthesis{Fischer2014, type = {Bachelor Thesis}, author = {Fischer, Jens V.}, title = {A Gossiping Framework for Scalaris}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-50685}, year = {2014}, language = {en} } @misc{FischerSchuetteDeuflhardetal.2001, author = {Fischer, Alexander and Sch{\"u}tte, Christof and Deuflhard, Peter and Cordes, Frank}, title = {Hierarchical Uncoupling-Coupling of Metastable Conformations}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-6296}, number = {01-03}, year = {2001}, abstract = {Uncoupling-coupling Monte Carlo (UCMC) combines uncoupling techniques for finite Markov chains with Markov chain Monte Carlo methodology. UCMC aims at avoiding the typical metastable or trapping behavior of Monte Carlo techniques. From the viewpoint of Monte Carlo, a slowly converging long-time Markov chain is replaced by a limited number of rapidly mixing short-time ones. Therefore, the state space of the chain has to be hierarchically decomposed into its metastable conformations. This is done by means of combining the technique of conformation analysis as recently introduced by the authors, and appropriate annealing strategies. We present a detailed examination of the uncoupling-coupling procedure which uncovers its theoretical background, and illustrates the hierarchical algorithmic approach. Furthermore, application of the UCMC algorithm to the \$n\$-pentane molecule allows us to discuss the effect of its crucial steps in a typical molecular scenario.}, language = {en} } @article{GarciaSantiagoHammerschmidtSachsetal.2022, author = {Garcia Santiago, Xavier and Hammerschmidt, Martin and Sachs, Johannes and Burger, Sven and Kwon, Hyunah and Kn{\"o}ller, Marvin and Arens, Tilo and Fischer, Peer and Fernandez-Corbaton, Ivan and Rockstuhl, Carsten}, title = {Toward maximally electromagnetically chiral scatterers at optical frequencies}, volume = {9}, journal = {ACS Photonics}, arxiv = {http://arxiv.org/abs/2112.04422}, doi = {10.1021/acsphotonics.1c01887}, pages = {1954}, year = {2022}, language = {en} } @article{GorgullaCınaroğluFischeretal.2021, author = {Gorgulla, Christoph and {\c{C}}{\i}naroğlu, S{\"u}leyman and Fischer, Patrick D. and Fackeldey, Konstantin and Wagner, Gerhard and Arthanari, Haribabu}, title = {VirtualFlow Ants—Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization}, volume = {22}, journal = {Special Issue Artificial Intelligence \& Deep Learning Approaches for Structural Bioinformatics}, number = {11}, doi = {https://doi.org/10.3390/ijms22115807}, pages = {5807}, year = {2021}, abstract = {The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.}, language = {en} } @article{SchimunekSeidlElezetal.2024, author = {Schimunek, Johannes and Seidl, Philipp and Elez, Katarina and Hempel, Tim and Le, Tuan and No{\´e}, Frank and Olsson, Simon and Raich, Llu{\´i}s and Winter, Robin and Gokcan, Hatice and Gusev, Filipp and Gutkin, Evgeny M. and Isayev, Olexandr and Kurnikova, Maria G. and Narangoda, Chamali H. and Zubatyuk, Roman and Bosko, Ivan P. and Furs, Konstantin V. and Karpenko, Anna D. and Kornoushenko, Yury V. and Shuldau, Mikita and Yushkevich, Artsemi and Benabderrahmane, Mohammed B. and Bousquet-Melou, Patrick and Bureau, Ronan and Charton, Beatrice and Cirou, Bertrand C. and Gil, G{\´e}rard and Allen, William J. and Sirimulla, Suman and Watowich, Stanley and Antonopoulos, Nick and Epitropakis, Nikolaos and Krasoulis, Agamemnon and Itsikalis, Vassilis and Theodorakis, Stavros and Kozlovskii, Igor and Maliutin, Anton and Medvedev, Alexander and Popov, Petr and Zaretckii, Mark and Eghbal-Zadeh, Hamid and Halmich, Christina and Hochreiter, Sepp and Mayr, Andreas and Ruch, Peter and Widrich, Michael and Berenger, Francois and Kumar, Ashutosh and Yamanishi, Yoshihiro and Zhang, Kam Y. J. and Bengio, Emmanuel and Bengio, Yoshua and Jain, Moksh J. and Korablyov, Maksym and Liu, Cheng-Hao and Marcou, Gilles and Glaab, Enrico and Barnsley, Kelly and Iyengar, Suhasini M. and Ondrechen, Mary Jo and Haupt, V. Joachim and Kaiser, Florian and Schroeder, Michael and Pugliese, Luisa and Albani, Simone and Athanasiou, Christina and Beccari, Andrea and Carloni, Paolo and D'Arrigo, Giulia and Gianquinto, Eleonora and Goßen, Jonas and Hanke, Anton and Joseph, Benjamin P. and Kokh, Daria B. and Kovachka, Sandra and Manelfi, Candida and Mukherjee, Goutam and Mu{\~n}iz-Chicharro, Abraham and Musiani, Francesco and Nunes-Alves, Ariane and Paiardi, Giulia and Rossetti, Giulia and Sadiq, S. Kashif and Spyrakis, Francesca and Talarico, Carmine and Tsengenes, Alexandros and Wade, Rebecca C. and Copeland, Conner and Gaiser, Jeremiah and Olson, Daniel R. and Roy, Amitava and Venkatraman, Vishwesh and Wheeler, Travis J. and Arthanari, Haribabu and Blaschitz, Klara and Cespugli, Marco and Durmaz, Vedat and Fackeldey, Konstantin and Fischer, Patrick D. and Gorgulla, Christoph and Gruber, Christian and Gruber, Karl and Hetmann, Michael and Kinney, Jamie E. and Padmanabha Das, Krishna M. and Pandita, Shreya and Singh, Amit and Steinkellner, Georg and Tesseyre, Guilhem and Wagner, Gerhard and Wang, Zi-Fu and Yust, Ryan J. and Druzhilovskiy, Dmitry S. and Filimonov, Dmitry A. and Pogodin, Pavel V. and Poroikov, Vladimir and Rudik, Anastassia V. and Stolbov, Leonid A. and Veselovsky, Alexander V. and De Rosa, Maria and De Simone, Giada and Gulotta, Maria R. and Lombino, Jessica and Mekni, Nedra and Perricone, Ugo and Casini, Arturo and Embree, Amanda and Gordon, D. Benjamin and Lei, David and Pratt, Katelin and Voigt, Christopher A. and Chen, Kuang-Yu and Jacob, Yves and Krischuns, Tim and Lafaye, Pierre and Zettor, Agn{\`e}s and Rodr{\´i}guez, M. Luis and White, Kris M. and Fearon, Daren and Von Delft, Frank and Walsh, Martin A. and Horvath, Dragos and Brooks III, Charles L. and Falsafi, Babak and Ford, Bryan and Garc{\´i}a-Sastre, Adolfo and Yup Lee, Sang and Naffakh, Nadia and Varnek, Alexandre and Klambauer, G{\"u}nter and Hermans, Thomas M.}, title = {A community effort in SARS-CoV-2 drug discovery}, volume = {43}, journal = {Molecular Informatics}, number = {1}, doi = {https://doi.org/10.1002/minf.202300262}, pages = {e202300262}, year = {2024}, 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} } @inproceedings{GossingBeckertFischeretal.2024, author = {Gossing, Anne and Beckert, Andreas and Fischer, Christoph and Klenert, Nicolas and Natarajan, Vijay and Pacey, George and Vogt, Thorwin and Rautenhaus, Marc and Baum, Daniel}, title = {A Ridge-based Approach for Extraction and Visualization of 3D Atmospheric Fronts}, booktitle = {2024 IEEE Visualization and Visual Analytics (VIS)}, doi = {10.1109/VIS55277.2024.00043}, pages = {176 -- 180}, year = {2024}, abstract = {An atmospheric front is an imaginary surface that separates two distinct air masses and is commonly defined as the warm-air side of a frontal zone with high gradients of atmospheric temperature and humidity. These fronts are a widely used conceptual model in meteorology, which are often encountered in the literature as two-dimensional (2D) front lines on surface analysis charts. This paper presents a method for computing three-dimensional (3D) atmospheric fronts as surfaces that is capable of extracting continuous and well-confined features suitable for 3D visual analysis, spatio-temporal tracking, and statistical analyses. Recently developed contour-based methods for 3D front extraction rely on computing the third derivative of a moist potential temperature field. Additionally, they require the field to be smoothed to obtain continuous large-scale structures. This paper demonstrates the feasibility of an alternative method to front extraction using ridge surface computation. The proposed method requires only the sec- ond derivative of the input field and produces accurate structures even from unsmoothed data. An application of the ridge-based method to a data set corresponding to Cyclone Friederike demonstrates its benefits and utility towards visual analysis of the full 3D structure of fronts.}, language = {en} }