Zobrazeno 1 - 10
of 10 353
pro vyhledávání: '"P Rupp"'
Autor:
Behner, Gerrit, Jalil, Abdur Rehman, Rupp, Alina, Lüth, Hans, Grützmacher, Detlev, Schäpers, Thomas
The combination of an ordinary s-type superconductor with three-dimensional topological insulators creates a promising platform for fault-tolerant topological quantum computing circuits based on Majorana braiding. The backbone of the braiding mechani
Externí odkaz:
http://arxiv.org/abs/2410.19311
Autor:
Mittmann, Gesa, Laiouar-Pedari, Sara, Mehrtens, Hendrik A., Haggenmüller, Sarah, Bucher, Tabea-Clara, Chanda, Tirtha, Gaisa, Nadine T., Wagner, Mathias, Klamminger, Gilbert Georg, Rau, Tilman T., Neppl, Christina, Compérat, Eva Maria, Gocht, Andreas, Hämmerle, Monika, Rupp, Niels J., Westhoff, Jula, Krücken, Irene, Seidl, Maximillian, Schürch, Christian M., Bauer, Marcus, Solass, Wiebke, Tam, Yu Chun, Weber, Florian, Grobholz, Rainer, Augustyniak, Jaroslaw, Kalinski, Thomas, Hörner, Christian, Mertz, Kirsten D., Döring, Constanze, Erbersdobler, Andreas, Deubler, Gabriele, Bremmer, Felix, Sommer, Ulrich, Brodhun, Michael, Griffin, Jon, Lenon, Maria Sarah L., Trpkov, Kiril, Cheng, Liang, Chen, Fei, Levi, Angelique, Cai, Guoping, Nguyen, Tri Q., Amin, Ali, Cimadamore, Alessia, Shabaik, Ahmed, Manucha, Varsha, Ahmad, Nazeel, Messias, Nidia, Sanguedolce, Francesca, Taheri, Diana, Baraban, Ezra, Jia, Liwei, Shah, Rajal B., Siadat, Farshid, Swarbrick, Nicole, Park, Kyung, Hassan, Oudai, Sakhaie, Siamak, Downes, Michelle R., Miyamoto, Hiroshi, Williamson, Sean R., Holland-Letz, Tim, Schneider, Carolin V., Kather, Jakob Nikolas, Tolkach, Yuri, Brinker, Titus J.
The aggressiveness of prostate cancer, the most common cancer in men worldwide, is primarily assessed based on histopathological data using the Gleason scoring system. While artificial intelligence (AI) has shown promise in accurately predicting Glea
Externí odkaz:
http://arxiv.org/abs/2410.15012
Machine-learning interatomic potentials (MLPs) are fast, data-driven surrogate models of atomistic systems' potential energy surfaces that can accelerate ab-initio molecular dynamics (MD) simulations by several orders of magnitude. The performance of
Externí odkaz:
http://arxiv.org/abs/2409.13390
Autor:
Colombo, Alessandro, Sauppe, Mario, Haddad, Andre Al, Ayyer, Kartik, Babayan, Morsal, Dagar, Ritika, Fennel, Thomas, Hecht, Linos, Knopp, Gregor, Kolatzki, Katharina, Langbehn, Bruno, Maia, Filipe, Mall, Abhishek, Mazumder, Parichita, Polat, Caner, Schäfer-Zimmermann, Julian C., Schnorr, Kirsten, Schubert, Marie Louise, Sehati, Arezu, Sellberg, Jonas A., Shen, Zhou, Sun, Zhibin, Svensson, Pamela, Tümmler, Paul, Ussling, Carl Frederic, Veteläinen, Onni, Wächter, Simon, Walsh, Noelle, Weitnauer, Alex V., You, Tong, Zuod, Maha, Bostedt, Christoph, Patanen, Minna, Rupp, Daniela
Coherent Diffraction Imaging (CDI) is an experimental technique to get images of isolated structures by recording the light scattered off the sample. Thanks to the extremely bright and short coherent light pulses provided by X-ray Free Electron Laser
Externí odkaz:
http://arxiv.org/abs/2409.07413
Learning fine-scale details of a coastal ocean simulation from a coarse representation is a challenging task. For real-world applications, high-resolution simulations are necessary to advance understanding of many coastal processes, specifically, to
Externí odkaz:
http://arxiv.org/abs/2408.16553
The energetically most efficient way how a deformed red blood cell regains equilibrium is mathematically described by the gradient flow of the Canham-Helfrich functional, including a spontaneous curvature and the conservation of surface area and encl
Externí odkaz:
http://arxiv.org/abs/2408.07493
In this study, we elaborate on the concept of scalable anomalous reflector (AR) to analyze the angular response, frequency response, and spatial scalability of a designed AR across a broad range of angles and frequencies. We utilize theoretical model
Externí odkaz:
http://arxiv.org/abs/2407.17279
Despite tremendous progress, machine learning and deep learning still suffer from incomprehensible predictions. Incomprehensibility, however, is not an option for the use of (deep) reinforcement learning in the real world, as unpredictable actions ca
Externí odkaz:
http://arxiv.org/abs/2407.14714
This paper considers the numerical solution of Timoshenko beam network models, comprised of Timoshenko beam equations on each edge of the network, which are coupled at the nodes of the network using rigid joint conditions. Through hybridization, we c
Externí odkaz:
http://arxiv.org/abs/2407.14388
Achieving optimal balance in games is essential to their success, yet reliant on extensive manual work and playtesting. To facilitate this process, the Procedural Content Generation via Reinforcement Learning (PCGRL) framework has recently been effec
Externí odkaz:
http://arxiv.org/abs/2407.11396