Zobrazeno 1 - 10
of 49 888
pro vyhledávání: '"Farkas AN"'
Autor:
Olejník, Kamil, Kašpar, Zdeněk, Zubáč, Jan, Telkamp, Sjoerd, Farkaš, Andrej, Kriegner, Dominik, Výborný, Karel, Železný, Jakub, Šobáň, Zbyněk, Zeng, Peng, Jungwirth, Tomáš, Novák, Vít, Krizek, Filip
We demonstrate that epitaxial thin film antiferromagnet Mn2As exhibits the quench-switching effect, which was previously reported only in crystallographically similar antiferromagnetic CuMnAs thin films. Quench switching in Mn2As shows stronger incre
Externí odkaz:
http://arxiv.org/abs/2411.01930
Autor:
Kiss, Csaba, Müller, Thomas G., Farkas-Takács, Anikó, Moór, Attila, Protopapa, Silvia, Parker, Alex H., Santos-Sanz, Pablo, Ortiz, Jose Luis, Holler, Bryan J., Wong, Ian, Stansberry, John, Fernández-Valenzuela, Estela, Glein, Christopher R., Lellouch, Emmanuel, Vilenius, Esa, Kalup, Csilla E., Regály, Zsolt, Szakáts, Róbert, Marton, Gábor, Pál, András, Szabó, Gyula M.
We report on the discovery of a very prominent mid-infrared (18-25 {\mu}m) excess associated with the trans-Neptunian dwarf planet (136472) Makemake. The excess, detected by the MIRI instrument of the James Webb Space Telescope, along with previous m
Externí odkaz:
http://arxiv.org/abs/2410.22544
Autor:
Zubáč, Jan, Surýnek, Miloslav, Olejník, Kamil, Farkaš, Andrej, Krizek, Filip, Nádvorník, Lukáš, Kubaščík, Petr, Kašpar, Zdeněk, Trojánek, František, Campion, Richard P., Novák, Vít, Němec, Petr, Jungwirth, Tomáš
Solving complex tasks in a modern information-driven society requires novel materials and concepts for energy-efficient hardware. Antiferromagnets offer a promising platform for seeking such approaches due to their exceptional features: low power con
Externí odkaz:
http://arxiv.org/abs/2410.16909
Autor:
Gyöngyössy, Natabara Máté, Török, Bernát, Farkas, Csilla, Lucaj, Laura, Menyhárd, Attila, Menyhárd-Balázs, Krisztina, Simonyi, András, van der Smagt, Patrick, Ződi, Zsolt, Lőrincz, András
Regulatory frameworks for the use of AI are emerging. However, they trail behind the fast-evolving malicious AI technologies that can quickly cause lasting societal damage. In response, we introduce a pioneering Assistive AI framework designed to enh
Externí odkaz:
http://arxiv.org/abs/2410.14353
Publikováno v:
In Artificial Neural Networks and Machine Learning -- ICANN 2024 (pp. 285--298). Springer Nature Switzerland
Causal learning allows humans to predict the effect of their actions on the known environment and use this knowledge to plan the execution of more complex actions. Such knowledge also captures the behaviour of the environment and can be used for its
Externí odkaz:
http://arxiv.org/abs/2410.07751
Autor:
Alshehri, Azzah, Bürger, Jan, Chopra, Saransh, Eich, Niclas, Eppelt, Jonas, Erdmann, Martin, Eschle, Jonas, Fackeldey, Peter, Farkas, Maté, Feickert, Matthew, Fillinger, Tristan, Fischer, Benjamin, Gerlach, Lino Oscar, Hartmann, Nikolai, Heidelbach, Alexander, Held, Alexander, Ivanov, Marian I, Molina, Josué, Nikitenko, Yaroslav, Osborne, Ianna, Padulano, Vincenzo Eduardo, Pivarski, Jim, Praz, Cyrille, Rieger, Marcel, Rodrigues, Eduardo, Shadura, Oksana, Smieško, Juraj, Stark, Giordon Holtsberg, Steinfeld, Judith, Warkentin, Angela
The second PyHEP.dev workshop, part of the "Python in HEP Developers" series organized by the HEP Software Foundation (HSF), took place in Aachen, Germany, from August 26 to 30, 2024. This gathering brought together nearly 30 Python package developer
Externí odkaz:
http://arxiv.org/abs/2410.02112
Random numbers are used in a wide range of sciences. In many applications, generating unpredictable private random numbers is indispensable. Device-independent quantum random number generation is a framework that makes use of the intrinsic randomness
Externí odkaz:
http://arxiv.org/abs/2409.18916
Autor:
Farkas, Gavril, Izadi, Elham
We describe an extension at the level of the moduli space of stable spin curves of genus g of the map associating to an ineffective spin structure its Scorza curve (equivalently, the vanishing locus of its Szeg\H{o} kernel). We compute the class of t
Externí odkaz:
http://arxiv.org/abs/2409.13303
Autor:
Kays, Roland, Snider, Matthew H., Hess, George, Cove, Michael V., Jensen, Alex, Shamon, Hila, McShea, William J., Rooney, Brigit, Allen, Maximilian L., Pekins, Charles E., Wilmers, Christopher C., Pendergast, Mary E., Green, Austin M., Suraci, Justin, Leslie, Matthew S., Nasrallah, Sophie, Farkas, Dan, Jordan, Mark, Grigione, Melissa, LaScaleia, Michael C., Davis, Miranda L., Hansen, Chris, Millspaugh, Josh, Lewis, Jesse S., Havrda, Michael, Long, Robert, Remine, Kathryn R., Jaspers, Kodi J., Lafferty, Diana J. R., Hubbard, Tru, Studds, Colin E., Barthelmess, Erika L., Andy, Katherine, Romero, Andrea, O'Neill, Brian J., Hawkins, Melissa T. R., Lombardi, Jason V., Sergeyev, Maksim, Fisher-Reid, M. Caitlin, Rentz, Michael S., Nagy, Christopher, Davenport, Jon M., Rega-Brodsky, Christine C., Appel, Cara L., Lesmeister, Damon B., Giery, Sean T., Whittier, Christopher A., Alston, Jesse M., Sutherland, Chris, Rota, Christopher, Murphy, Thomas, Lee, Thomas E., Mortelliti, Alessio, Bergman, Dylan L., Compton, Justin A., Gerber, Brian D., Burr, Jess, Rezendes, Kylie, DeGregorio, Brett A., Wehr, Nathaniel H., Benson, John F., O’Mara, M. Teague, Jachowski, David S., Gray, Morgan, Beyer, Dean E., Belant, Jerrold L., Horan, Robert V., Lonsinger, Robert C., Kuhn, Kellie M., Hasstedt, Steven C. M., Zimova, Marketa, Moore, Sophie M., Herrera, Daniel J., Fritts, Sarah, Edelman, Andrew J., Flaherty, Elizabeth A., Petroelje, Tyler R., Neiswenter, Sean A., Risch, Derek R., Iannarilli, Fabiola, van der Merwe, Marius, Maher, Sean P., Farris, Zach J., Webb, Stephen L., Mason, David S., Lashley, Marcus A., Wilson, Andrew M., Vanek, John P., Wehr, Samuel R., Conner, L. Mike, Beasley, James C., Bontrager, Helen L., Baruzzi, Carolina, Ellis-Felege, Susan N., Proctor, Mike D., Schipper, Jan, Weiss, Katherine C. B., Darracq, Andrea K., Barr, Evan G., Alexander, Peter D., Şekercioğlu, Çağan H., Bogan, Daniel A., Schalk, Christopher M., Fantle-Lepczyk, Jean E., Lepczyk, Christopher A., LaPoint, Scott, Whipple, Laura S., Rowe, Helen Ivy, Mullen, Kayleigh, Bird, Tori, Zorn, Adam, Brandt, LaRoy, Lathrop, Richard G., McCain, Craig, Crupi, Anthony P., Clark, James, Parsons, Arielle
Publikováno v:
Diversity and Distributions, 2024 Sep 01. 30(9), 1-16.
Externí odkaz:
https://www.jstor.org/stable/48784956
Random effects meta-analysis is a widely applied methodology to synthetize research findings of studies in a specific scientific question. Besides estimating the mean effect, an important aim of the meta-analysis is to summarize the heterogeneity, i.
Externí odkaz:
http://arxiv.org/abs/2408.08080