Zobrazeno 1 - 10
of 22 561
pro vyhledávání: '"Enders, A"'
Autor:
Herbert, Maximilian, Eggert, Tobias, Enders, Joachim, Engart, Markus, Fritzsche, Yuliya, Meier, Maximilian, Schulze, Julian, Wende, Vincent
GaAs-based photocathodes are the only viable source capable of providing spin-polarized electrons for accelerator applications. This type of photocathode requires a thin surface layer, in order to achieve negative electron affinity (NEA) for efficien
Externí odkaz:
http://arxiv.org/abs/2409.04319
Autor:
Enders, Michael T., Sarkar, Mitradeep, Klironomou, Evgenia, Picardi, Michela Florinda, Deeva, Aleksandra, Papadakis, Georgia T.
The ability to detect and engineer chirality plays a defining role in understanding nature, presenting itself in various phenomena ranging from the formation of DNA to enzymatic activities and digital encoding. Inducing a chiral response using nanoph
Externí odkaz:
http://arxiv.org/abs/2409.02641
Autor:
Welborn, Samuel S., Harris, Chris, Ribet, Stephanie M., Varnavides, Georgios, Ophus, Colin, Enders, Bjoern, Ercius, Peter
Data management is a critical component of modern experimental workflows. As data generation rates increase, transferring data from acquisition servers to processing servers via conventional file-based methods is becoming increasingly impractical. Th
Externí odkaz:
http://arxiv.org/abs/2407.03215
We study a sequential decision-making problem for a profit-maximizing operator of an Autonomous Mobility-on-Demand system. Optimizing a central operator's vehicle-to-request dispatching policy requires efficient and effective fleet control strategies
Externí odkaz:
http://arxiv.org/abs/2404.06975
Recent advancements in detector technology have significantly increased the size and complexity of experimental data, and high-performance computing (HPC) provides a path towards more efficient and timely data processing. However, movement of large d
Externí odkaz:
http://arxiv.org/abs/2403.14352
Autor:
Enders, Dominic, Shulman, Tatiana
The (Local) Lifting Property ((L)LP) is introduced by Kirchberg and deals with lifting completely positive maps. We give a characterization of the (L)LP in terms of lifting $\ast$-homomorphisms. We use it to prove that if $A$ and $B$ have the LP and
Externí odkaz:
http://arxiv.org/abs/2403.12224
We study the robustness of deep reinforcement learning algorithms against distribution shifts within contextual multi-stage stochastic combinatorial optimization problems from the operations research domain. In this context, risk-sensitive algorithms
Externí odkaz:
http://arxiv.org/abs/2402.09992
Autor:
Reuther, Albert, Brown, Nick, Arndt, William, Blaschke, Johannes, Boehme, Christian, Chazapis, Antony, Enders, Bjoern, Henschel, Robert, Kunkel, Julian, Martinasso, Maxime
As a broader set of applications from simulations to data analysis and machine learning require more parallel computational capability, the demand for interactive and urgent high performance computing (HPC) continues to increase. This paper overviews
Externí odkaz:
http://arxiv.org/abs/2401.14550
We study vehicle dispatching in autonomous mobility on demand (AMoD) systems, where a central operator assigns vehicles to customer requests or rejects these with the aim of maximizing its total profit. Recent approaches use multi-agent deep reinforc
Externí odkaz:
http://arxiv.org/abs/2312.08884
Autor:
Kadler, M., Riechers, D. A., Agarwal, J., Baczko, A. -K., Beuther, H., Bigiel, F., Birnstiel, T., Boccardi, B., Bomans, D. J., Boogaard, L., Braun, T. T., Britzen, S., Brüggen, M., Brunthaler, A., Caselli, P., Elsässer, D., von Fellenberg, S., Flock, M., Fromm, C. M., Fuhrmann, L., Hartogh, P., Hoeft, M., Keenan, R. P., Kovalev, Y., Kreckel, K., Livingston, J., Lobanov, A. P., Müller, H., Ros, E., Schilke, P., De Simone, M., Spitler, L., Ueda, T., Vardoulaki, E., Vegetti, S., Weis, K., Wendel, C., Xu, M. H., Zhao, G. -Y., Albrecht, M., Basu, A., Tjus, J. Becker, Bernhart, S., Blum, J., Bonnassieux, E., Bredendiek, C., van Delden, M., Di Gennaro, G., Enders, A., Eppel, F., Hase, H., Hoang, D., Hugentobler, U., Kaasinen, M., Krupp, N., Kun, E., Laubach, M., Lin, Y., Mannheim, K., Menten, K. M., Perkuhn, R., Pohl, N., Powell, D. M., Rezzolla, L., Ricci, L., Schinnerer, E., Schmidt, K., Schöpfel, J., Stanko, S., Stein, M., Sulzenauer, N., Taziaux, S., Tursunov, A., Walter, F., Weiss, A., Witzel, G., Wolf, S., Zensus, J. A., Mus, A., Toth, L. V., Alberdi, A., Benisty, M., Cox, P., Guirado, J. C., Johnson, M. D., Juvela, M., Neeleman, M., Pashchenko, I. N., Torres, M. A. Pérez, Perraut, K., Zajacek, M.
The Next Generation Very Large Array (ngVLA) is a planned radio interferometer providing unprecedented sensitivity at wavelengths between 21 cm and 3 mm. Its 263 antenna element array will be spatially distributed across North America to enable both
Externí odkaz:
http://arxiv.org/abs/2311.10056