Zobrazeno 1 - 10
of 86 037
pro vyhledávání: '"Scholz, A."'
Autor:
Ibik, Adaeze L., Drout, Maria R., Gaensler, Bryan M., Scholz, Paul, Sridhar, Navin, Margalit, Ben, Law, Casey J., Clarke, Tracy E., Tendulkar, Shriharsh P., Michilli, Daniele, Eftekhari, Tarraneh, Bhardwaj, Mohit, Burke-Spolaor, Sarah, Chatterjee, Shami, Cook, Amanda M., Hessels, Jason W. T., Kirsten, Franz, Joseph, Ronniy C., Kaspi, Victoria M., Lazda, Mattias, Masui, Kiyoshi W., Nimmo, Kenzie, Pandhi, Ayush, Pearlman, Aaron B., Pleunis, Ziggy, Rafiei-Ravandi, Masoud, Shin, Kaitlyn, Smith, Kendrick M.
The identification of persistent radio sources (PRSs) coincident with two repeating fast radio bursts (FRBs) supports FRB theories requiring a compact central engine. However, deep non-detections in other cases highlight the diversity of repeating FR
Externí odkaz:
http://arxiv.org/abs/2409.11533
Autor:
Bauza, Maria, Chen, Jose Enrique, Dalibard, Valentin, Gileadi, Nimrod, Hafner, Roland, Martins, Murilo F., Moore, Joss, Pevceviciute, Rugile, Laurens, Antoine, Rao, Dushyant, Zambelli, Martina, Riedmiller, Martin, Scholz, Jon, Bousmalis, Konstantinos, Nori, Francesco, Heess, Nicolas
We present DemoStart, a novel auto-curriculum reinforcement learning method capable of learning complex manipulation behaviors on an arm equipped with a three-fingered robotic hand, from only a sparse reward and a handful of demonstrations in simulat
Externí odkaz:
http://arxiv.org/abs/2409.06613
Autor:
Langeveld, Adam B., Scholz, Aleks, Mužić, Koraljka, Jayawardhana, Ray, Capela, Daniel, Albert, Loïc, Doyon, René, Flagg, Laura, de Furio, Matthew, Johnstone, Doug, Lafrèniere, David, Meyer, Michael
The discovery and characterization of free-floating planetary-mass objects (FFPMOs) is fundamental to our understanding of star and planet formation. Here we report results from an extremely deep spectroscopic survey of the young star cluster NGC1333
Externí odkaz:
http://arxiv.org/abs/2408.12639
Autor:
Cook, Amanda M., Scholz, Paul, Pearlman, Aaron B., Abbott, Thomas C., Cruces, Marilyn, Gaensler, B. M., Fengqiu, Dong, Michilli, Daniele, Eadie, Gwendolyn, Kaspi, Victoria M., Stairs, Ingrid, Tan, Chia Min, Bhardwaj, Mohit, Cassanelli, Tomas, Curtin, Alice P., Ibik, Adaeze L., Lazda, Mattias, Masui, Kiyoshi W., Pandhi, Ayush, Rafiei-Ravandi, Masoud, Sammons, Mawson W., Shin, Kaitlyn, Smith, Kendrick, Stenning, David C.
We present an extensive contemporaneous X-ray and radio campaign performed on the repeating fast radio burst (FRB) source FRB 20220912A for eight weeks immediately following the source's detection by CHIME/FRB. This includes X-ray data from XMM-Newto
Externí odkaz:
http://arxiv.org/abs/2408.11895
Generative models are a cornerstone of Bayesian data analysis, enabling predictive simulations and model validation. However, in practice, manually specified priors often lead to unreasonable simulation outcomes, a common obstacle for full Bayesian s
Externí odkaz:
http://arxiv.org/abs/2408.06504
Autor:
Funke, Lars, Ilchen, Markus, Dingel, Kristina, Mazza, Tommaso, Mullins, Terence, Otto, Thorsten, Rivas, Daniel, Savio, Sara, Serkez, Svitozar, Walter, Peter, Wieland, Niclas, Wülfing, Lasse, Bari, Sadia, Boll, Rebecca, Braune, Markus, Calegari, Francesca, De Fanis, Alberto, Decking, Winfried, Duensing, Andreas, Düsterer, Stefan, Ehresmann, Arno, Erk, Benjamin, de Lima, Danilo Enoque Ferreira, Galler, Andreas, Geloni, Gianluca, Grünert, Jan, Guetg, Marc, Grychtol, Patrik, Hans, Andreas, Held, Arne, Hindriksson, Ruda, Inhester, Ludger, Jahnke, Till, Laksman, Joakim, Larsson, Mats, Liu, Jia, Marangos, Jon P., Marder, Lutz, Meier, David, Meyer, Michael, Mirian, Najmeh, Ott, Christian, Passow, Christopher, Pfeifer, Thomas, Rupprecht, Patrick, Schletter, Albert, Schmidt, Philipp, Scholz, Frank, Schott, Simon, Schneidmiller, Evgeny, Sick, Bernhard, Son, Sang-Kil, Tiedtke, Kai, Usenko, Sergey, Wanie, Vincent, Wurzer, Markus, Yurkov, Mikhail, Zhaunerchyk, Vitali, Helml, Wolfram
Attosecond X-ray pulses are the key to studying electron dynamics at their natural time scale involving specific electronic states. They are promising to build the conceptual bridge between physical and chemical photo-reaction processes. Free-electro
Externí odkaz:
http://arxiv.org/abs/2408.03858
Autor:
Elmers, H. J., Tkach, O., Lytvynenko, Y., Yogi, P., Schmitt, M., Biswas, D., Liu, J., Chernov, S. V., Hoesch, M., Kutnyakhov, D., Wind, N., Wenthaus, L., Scholz, M., Rossnagel, K., Gloskovskii, A., Schlueter, C., Winkelmann, A., Haghighirad, A. -A., Lee, T. -L., Sing, M., Claessen, R., Tacon, M. Le, Demsar, J., Schonhense, G., Fedchenko, O.
Using x-ray photoelectron diffraction (XPD) and angle-resolved photoemission spectroscopy, we study photoemission intensity changes related to changes in the geometric and electronic structure in the kagome metal CsV$_3$Sb$_5$ upon transition to an u
Externí odkaz:
http://arxiv.org/abs/2408.03750
In this paper, we introduce a novel, data-driven approach for solving high-dimensional Bayesian inverse problems based on partial differential equations (PDEs), called Weak Neural Variational Inference (WNVI). The method complements real measurements
Externí odkaz:
http://arxiv.org/abs/2407.20697
Autor:
Dong, Fengqiu Adam, Clarke, Tracy, Curtin, Alice P., Kumar, Ajay, Stairs, Ingrid, Chatterjee, Shami, Cook, Amanda M., Fonseca, Emmanuel, Gaensler, B. M., Hessels, Jason W. T., Kaspi, Victoria M., Lazda, Mattias, Masui, Kiyoshi W., McKee, James W., Meyers, Bradley W., Pearlman, Aaron B., Ransom, Scott M., Scholz, Paul, Shin, Kaitlyn, Smith, Kendrick M., Tan, Chia Min
Neutron stars and white dwarfs are both dense remnants of post-main-sequence stars. Pulsars, magnetars and strongly magnetised white dwarfs have all been seen to been observed to exhibit coherent, pulsed radio emission in relation to their rotational
Externí odkaz:
http://arxiv.org/abs/2407.07480
Autor:
Hassouna, Mohamed, Holzhüter, Clara, Lytaev, Pawel, Thomas, Josephine, Sick, Bernhard, Scholz, Christoph
The rise of renewable energy and distributed generation requires new approaches to overcome the limitations of traditional methods. In this context, Graph Neural Networks are promising due to their ability to learn from graph-structured data. Combine
Externí odkaz:
http://arxiv.org/abs/2407.04522