@article{28942, author = {{Wecker, Christian and Schulz, Andreas Markus and Heine, Jens and Bart, Hans Jörg and Kenig, Eugeny Y.}}, journal = {{International Journal of Heat and Mass Transfer}}, publisher = {{ELSEVIER}}, title = {{{Droplet formation –a numerical investigation of liquid-liquid systems with consideration of Marangoni convection}}}, doi = {{10.1016/j.ijheatmasstransfer.2021.122465}}, volume = {{188}}, year = {{2022}}, } @article{44235, author = {{Inguva, Venkatesh and Kenig, Eugeny Y. and Perot, J. Blair}}, journal = {{Journal of Computational Physics}}, publisher = {{Elsevier}}, title = {{{A front-tracking method for two-phase flow simulation with no spurious currents}}}, volume = {{456}}, year = {{2022}}, } @article{30591, author = {{Bertling, René and Hack, M. and Ausner, I. and Horschitz, B. and Bernemann, Sören Antonius and Kenig, Eugeny}}, issn = {{0009-2509}}, journal = {{Chemical Engineering Science}}, keywords = {{Applied Mathematics, Industrial and Manufacturing Engineering, General Chemical Engineering, General Chemistry}}, publisher = {{Elsevier BV}}, title = {{{Modelling film and rivulet flows on microstructured surfaces using CFD methods}}}, doi = {{10.1016/j.ces.2021.117414}}, volume = {{251}}, year = {{2022}}, } @inproceedings{33739, abstract = {{At least 5% of questions submitted to search engines ask about cause-effect relationships in some way. To support the development of tailored approaches that can answer such questions, we construct Webis-CausalQA-22, a benchmark corpus of 1.1 million causal questions with answers. We distinguish different types of causal questions using a novel typology derived from a data-driven, manual analysis of questions from ten large question answering (QA) datasets. Using high-precision lexical rules, we extract causal questions of each type from these datasets to create our corpus. As an initial baseline, the state-of-the-art QA model UnifiedQA achieves a ROUGE-L F1 score of 0.48 on our new benchmark.}}, author = {{Bondarenko, Alexander and Wolska, Magdalena and Heindorf, Stefan and Blübaum, Lukas and Ngonga Ngomo, Axel-Cyrille and Stein, Benno and Braslavski, Pavel and Hagen, Matthias and Potthast, Martin}}, booktitle = {{Proceedings of the 29th International Conference on Computational Linguistics}}, pages = {{3296–3308}}, publisher = {{International Committee on Computational Linguistics}}, title = {{{CausalQA: A Benchmark for Causal Question Answering}}}, year = {{2022}}, } @unpublished{33493, abstract = {{Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing.}}, author = {{Gavini, Vikram and Baroni, Stefano and Blum, Volker and Bowler, David R. and Buccheri, Alexander and Chelikowsky, James R. and Das, Sambit and Dawson, William and Delugas, Pietro and Dogan, Mehmet and Draxl, Claudia and Galli, Giulia and Genovese, Luigi and Giannozzi, Paolo and Giantomassi, Matteo and Gonze, Xavier and Govoni, Marco and Gulans, Andris and Gygi, François and Herbert, John M. and Kokott, Sebastian and Kühne, Thomas and Liou, Kai-Hsin and Miyazaki, Tsuyoshi and Motamarri, Phani and Nakata, Ayako and Pask, John E. and Plessl, Christian and Ratcliff, Laura E. and Richard, Ryan M. and Rossi, Mariana and Schade, Robert and Scheffler, Matthias and Schütt, Ole and Suryanarayana, Phanish and Torrent, Marc and Truflandier, Lionel and Windus, Theresa L. and Xu, Qimen and Yu, Victor W. -Z. and Perez, Danny}}, booktitle = {{arXiv:2209.12747}}, title = {{{Roadmap on Electronic Structure Codes in the Exascale Era}}}, year = {{2022}}, } @inproceedings{46193, author = {{Karp, Martin and Podobas, Artur and Kenter, Tobias and Jansson, Niclas and Plessl, Christian and Schlatter, Philipp and Markidis, Stefano}}, booktitle = {{International Conference on High Performance Computing in Asia-Pacific Region}}, publisher = {{ACM}}, title = {{{A High-Fidelity Flow Solver for Unstructured Meshes on Field-Programmable Gate Arrays: Design, Evaluation, and Future Challenges}}}, doi = {{10.1145/3492805.3492808}}, year = {{2022}}, } @unpublished{32404, abstract = {{The CP2K program package, which can be considered as the swiss army knife of atomistic simulations, is presented with a special emphasis on ab-initio molecular dynamics using the second-generation Car-Parrinello method. After outlining current and near-term development efforts with regards to massively parallel low-scaling post-Hartree-Fock and eigenvalue solvers, novel approaches on how we plan to take full advantage of future low-precision hardware architectures are introduced. Our focus here is on combining our submatrix method with the approximate computing paradigm to address the immanent exascale era.}}, author = {{Kühne, Thomas and Plessl, Christian and Schade, Robert and Schütt, Ole}}, booktitle = {{arXiv:2205.14741}}, title = {{{CP2K on the road to exascale}}}, year = {{2022}}, } @article{33226, abstract = {{A parallel hybrid quantum-classical algorithm for the solution of the quantum-chemical ground-state energy problem on gate-based quantum computers is presented. This approach is based on the reduced density-matrix functional theory (RDMFT) formulation of the electronic structure problem. For that purpose, the density-matrix functional of the full system is decomposed into an indirectly coupled sum of density-matrix functionals for all its subsystems using the adaptive cluster approximation to RDMFT. The approximations involved in the decomposition and the adaptive cluster approximation itself can be systematically converged to the exact result. The solutions for the density-matrix functionals of the effective subsystems involves a constrained minimization over many-particle states that are approximated by parametrized trial states on the quantum computer similarly to the variational quantum eigensolver. The independence of the density-matrix functionals of the effective subsystems introduces a new level of parallelization and allows for the computational treatment of much larger molecules on a quantum computer with a given qubit count. In addition, for the proposed algorithm techniques are presented to reduce the qubit count, the number of quantum programs, as well as its depth. The evaluation of a density-matrix functional as the essential part of our approach is demonstrated for Hubbard-like systems on IBM quantum computers based on superconducting transmon qubits.}}, author = {{Schade, Robert and Bauer, Carsten and Tamoev, Konstantin and Mazur, Lukas and Plessl, Christian and Kühne, Thomas}}, journal = {{Phys. Rev. Research}}, pages = {{033160}}, publisher = {{American Physical Society}}, title = {{{Parallel quantum chemistry on noisy intermediate-scale quantum computers}}}, doi = {{10.1103/PhysRevResearch.4.033160}}, volume = {{4}}, year = {{2022}}, } @unpublished{46275, abstract = {{Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing.}}, author = {{Gavini, Vikram and Baroni, Stefano and Blum, Volker and Bowler, David R. and Buccheri, Alexander and Chelikowsky, James R. and Das, Sambit and Dawson, William and Delugas, Pietro and Dogan, Mehmet and Draxl, Claudia and Galli, Giulia and Genovese, Luigi and Giannozzi, Paolo and Giantomassi, Matteo and Gonze, Xavier and Govoni, Marco and Gulans, Andris and Gygi, François and Herbert, John M. and Kokott, Sebastian and Kühne, Thomas and Liou, Kai-Hsin and Miyazaki, Tsuyoshi and Motamarri, Phani and Nakata, Ayako and Pask, John E. and Plessl, Christian and Ratcliff, Laura E. and Richard, Ryan M. and Rossi, Mariana and Schade, Robert and Scheffler, Matthias and Schütt, Ole and Suryanarayana, Phanish and Torrent, Marc and Truflandier, Lionel and Windus, Theresa L. and Xu, Qimen and Yu, Victor W. -Z. and Perez, Danny}}, booktitle = {{arXiv:2209.12747}}, title = {{{Roadmap on Electronic Structure Codes in the Exascale Era}}}, year = {{2022}}, } @article{33684, author = {{Schade, Robert and Kenter, Tobias and Elgabarty, Hossam and Lass, Michael and Schütt, Ole and Lazzaro, Alfio and Pabst, Hans and Mohr, Stephan and Hutter, Jürg and Kühne, Thomas and Plessl, Christian}}, issn = {{0167-8191}}, journal = {{Parallel Computing}}, keywords = {{Artificial Intelligence, Computer Graphics and Computer-Aided Design, Computer Networks and Communications, Hardware and Architecture, Theoretical Computer Science, Software}}, publisher = {{Elsevier BV}}, title = {{{Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms}}}, doi = {{10.1016/j.parco.2022.102920}}, volume = {{111}}, year = {{2022}}, } @article{27364, author = {{Meyer, Marius and Kenter, Tobias and Plessl, Christian}}, issn = {{0743-7315}}, journal = {{Journal of Parallel and Distributed Computing}}, title = {{{In-depth FPGA Accelerator Performance Evaluation with Single Node Benchmarks from the HPC Challenge Benchmark Suite for Intel and Xilinx FPGAs using OpenCL}}}, doi = {{10.1016/j.jpdc.2021.10.007}}, year = {{2022}}, } @inproceedings{34136, author = {{Grynko, Yevgen and Shkuratov, Yuriy and Alhaddad, Samer and Förstner, Jens}}, keywords = {{tet_topic_scattering}}, location = {{Granada, Spain}}, publisher = {{Copernicus GmbH}}, title = {{{Light backscattering from numerical analog of planetary regoliths}}}, doi = {{10.5194/epsc2022-151}}, year = {{2022}}, } @techreport{49113, abstract = {{In this report we present our system for the Detection and Classification of Acoustic Scenes and Events (DCASE) 2022 Challenge Task 4: Sound Event Detection in Domestic Environments 1 . As in previous editions of the Challenge, we use forward-backward convolutional recurrent neural networks (FBCRNNs) [1, 2] for weakly labeled and semi-supervised sound event detection (SED) and eventually generate strong pseudo labels for weakly labeled and unlabeled data. Then, (tag-conditioned) bidirectional CRNNs (Bi-CRNNs) [1, 2] are trained in a strongly supervised manner as our final SED models. In each of the training stages we use multiple iterations of self-training. Compared to previous editions, we improved our system performance by 1) some tweaks regarding data augmentation, pseudo labeling and inference 2) using weakly labeled AudioSet data [3] for pretraining larger networks and 3) augmenting the DESED data [4] with strongly labeled AudioSet data [5] for finetuning of the networks. Source code is publicly available at https://github.com/fgnt/pb_sed.}}, author = {{Ebbers, Janek and Haeb-Umbach, Reinhold}}, title = {{{Pre-Training And Self-Training For Sound Event Detection In Domestic Environments}}}, year = {{2022}}, } @inproceedings{33509, abstract = {{In this publication a novel method for far-field prediction from magnetic Huygens box data based on the boundary element method (BEM) is presented. Two examples are considered for the validation of this method. The first example represents an electric dipole so that the obtained calculations can be compared to an analytical solution. As a second example, a printed circuit board is considered and the calculated far-field is compared to a fullwave simulation. In both cases, the calculations for different field integral equations are under comparison, and the results indicate that the presented method performs very well with a combined field integral equation, for the specified problem, when only magnetic Huygens box data is given.}}, author = {{Marschalt, Christoph and Schroder, Dominik and Lange, Sven and Hilleringmann, Ulrich and Hedayat, Christian and Kuhn, Harald and Sievers, Denis and Förstner, Jens}}, booktitle = {{2022 Smart Systems Integration (SSI)}}, keywords = {{Near-Field Scanning, Huygens Box, Boundary Element Method, Method of Moments, tet_topic_hf, tet_enas}}, location = {{Grenoble, France}}, publisher = {{IEEE}}, title = {{{Far-field Calculation from magnetic Huygens Box Data using the Boundary Element Method}}}, doi = {{10.1109/ssi56489.2022.9901431}}, year = {{2022}}, } @inproceedings{33848, abstract = {{Impressive progress in neural network-based single-channel speech source separation has been made in recent years. But those improvements have been mostly reported on anechoic data, a situation that is hardly met in practice. Taking the SepFormer as a starting point, which achieves state-of-the-art performance on anechoic mixtures, we gradually modify it to optimize its performance on reverberant mixtures. Although this leads to a word error rate improvement by 7 percentage points compared to the standard SepFormer implementation, the system ends up with only marginally better performance than a PIT-BLSTM separation system, that is optimized with rather straightforward means. This is surprising and at the same time sobering, challenging the practical usefulness of many improvements reported in recent years for monaural source separation on nonreverberant data.}}, author = {{Cord-Landwehr, Tobias and Boeddeker, Christoph and von Neumann, Thilo and Zorila, Catalin and Doddipatla, Rama and Haeb-Umbach, Reinhold}}, booktitle = {{2022 International Workshop on Acoustic Signal Enhancement (IWAENC)}}, publisher = {{IEEE}}, title = {{{Monaural source separation: From anechoic to reverberant environments}}}, year = {{2022}}, } @inproceedings{33819, author = {{von Neumann, Thilo and Kinoshita, Keisuke and Boeddeker, Christoph and Delcroix, Marc and Haeb-Umbach, Reinhold}}, booktitle = {{ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}}, publisher = {{IEEE}}, title = {{{SA-SDR: A Novel Loss Function for Separation of Meeting Style Data}}}, doi = {{10.1109/icassp43922.2022.9746757}}, year = {{2022}}, } @misc{33816, author = {{Gburrek, Tobias and Boeddeker, Christoph and von Neumann, Thilo and Cord-Landwehr, Tobias and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}}, publisher = {{arXiv}}, title = {{{A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network}}}, doi = {{10.48550/ARXIV.2205.00944}}, year = {{2022}}, } @inproceedings{33954, author = {{Boeddeker, Christoph and Cord-Landwehr, Tobias and von Neumann, Thilo and Haeb-Umbach, Reinhold}}, booktitle = {{Interspeech 2022}}, publisher = {{ISCA}}, title = {{{An Initialization Scheme for Meeting Separation with Spatial Mixture Models}}}, doi = {{10.21437/interspeech.2022-10929}}, year = {{2022}}, } @article{44088, abstract = {{Hole polarons and defect-bound exciton polarons in lithium niobate are investigated by means of density-functional theory, where the localization of the holes is achieved by applying the +U approach to the oxygen 2p orbitals. We find three principal configurations of hole polarons: (i) self-trapped holes localized at displaced regular oxygen atoms and (ii) two other configurations bound to a lithium vacancy either at a threefold coordinated oxygen atom above or at a two-fold coordinated oxygen atom below the defect. The latter is the most stable and is in excellent quantitative agreement with measured g factors from electron paramagnetic resonance. Due to the absence of mid-gap states, none of these hole polarons can explain the broad optical absorption centered between 2.5 and 2.8 eV that is observed in transient absorption spectroscopy, but such states appear if a free electron polaron is trapped at the same lithium vacancy as the bound hole polaron, resulting in an exciton polaron. The dielectric function calculated by solving the Bethe–Salpeter equation indeed yields an optical peak at 2.6 eV in agreement with the two-photon experiments. The coexistence of hole and exciton polarons, which are simultaneously created in optical excitations, thus satisfactorily explains the reported experimental data.}}, author = {{Schmidt, Falko and Kozub, Agnieszka L. and Gerstmann, Uwe and Schmidt, Wolf Gero and Schindlmayr, Arno}}, issn = {{2073-4352}}, journal = {{Crystals}}, number = {{11}}, publisher = {{MDPI AG}}, title = {{{A density-functional theory study of hole and defect-bound exciton polarons in lithium niobate}}}, doi = {{10.3390/cryst12111586}}, volume = {{12}}, year = {{2022}}, } @article{31937, author = {{Li, Yao and Ma, Xuekai and Hatzopoulos, Zaharias and Savvidis, Pavlos G. and Schumacher, Stefan and Gao, Tingge}}, issn = {{2330-4022}}, journal = {{ACS Photonics}}, number = {{6}}, pages = {{2079--2086}}, publisher = {{American Chemical Society (ACS)}}, title = {{{Switching Off a Microcavity Polariton Condensate near the Exceptional Point}}}, doi = {{10.1021/acsphotonics.2c00288}}, volume = {{9}}, year = {{2022}}, }