Zobrazeno 1 - 10
of 10 309
pro vyhledávání: '"A. Haefner"'
Autor:
Lippi, Eleonora, Gerken, Manuel, Häfner, Stephan, Repp, Marc, Pires, Rico, Rautenberg, Michael, Krom, Tobias, Kuhnle, Eva D., Tran, Binh, Ulmanis, Juris, Zhu, Bing, Chomaz, Lauriane, Weidemüller, Matthias
We present the experimental apparatus enabling the observation of the heteronuclear Efimov effect in an optically trapped ultracold mixture of $^6$Li-$^{133}$Cs with high-resolution control of the interactions. A compact double-species Zeeman slower
Externí odkaz:
http://arxiv.org/abs/2410.16031
This perspective piece is the result of a Generative Adversarial Collaboration (GAC) tackling the question `How does neural activity represent probability distributions?'. We have addressed three major obstacles to progress on answering this question
Externí odkaz:
http://arxiv.org/abs/2409.02709
Autor:
Stolk, Arian J., van der Enden, Kian L., Slater, Marie-Christine, Raa-Derckx, Ingmar te, Botma, Pieter, van Rantwijk, Joris, Biemond, Benjamin, Hagen, Ronald A. J., Herfst, Rodolf W., Koek, Wouter D., Meskers, Arjan J. H., Vollmer, René, van Zwet, Erwin J., Markham, Matthew, Edmonds, Andrew M., Geus, Jan Fabian, Elsen, Florian, Jungbluth, Bernd, Haefner, Constantin, Tresp, Christoph, Stuhler, Jürgen, Ritter, Stephan, Hanson, Ronald
Publikováno v:
Sci. Adv. 10, eadp6442 (2024)
A key challenge towards future quantum internet technology is connecting quantum processors at metropolitan scale. Here, we report on heralded entanglement between two independently operated quantum network nodes separated by 10km. The two nodes host
Externí odkaz:
http://arxiv.org/abs/2404.03723
Neural approaches have shown a significant progress on camera-based reconstruction. But they require either a fairly dense sampling of the viewing sphere, or pre-training on an existing dataset, thereby limiting their generalizability. In contrast, p
Externí odkaz:
http://arxiv.org/abs/2404.00098
Autor:
Häfner, Dietrich, Klein, Christiane
In a recent paper by G\'erard, H\"afner, and Wrochna, the Unruh state for massless fermions on a Kerr spacetime was constructed and the authors showed its Hadmard property in the case of very slowly rotating black holes $\vert a\vert\ll M$. In this n
Externí odkaz:
http://arxiv.org/abs/2403.09261
Autor:
Hendrickson, Aaron J., Haefner, David P., Chan, Stanley H., Shade, Nicholas R., Fossum, Eric R.
Working from a Poisson-Gaussian noise model, a multi-sample extension of the Photon Counting Histogram Expectation Maximization (PCH-EM) algorithm is derived as a general-purpose alternative to the Photon Transfer (PT) method. This algorithm is deriv
Externí odkaz:
http://arxiv.org/abs/2403.04498
Autor:
Blohm, Gunnar, Peters, Benjamin, Haefner, Ralf, Isik, Leyla, Kriegeskorte, Nikolaus, Lieberman, Jennifer S., Ponce, Carlos R., Roig, Gemma, Peters, Megan A. K.
Generative adversarial collaborations (GACs) are a form of formal teamwork between groups of scientists with diverging views. The goal of GACs is to identify and ultimately resolve the most important challenges, controversies, and exciting theoretica
Externí odkaz:
http://arxiv.org/abs/2402.12604
Autor:
Peters, Benjamin, DiCarlo, James J., Gureckis, Todd, Haefner, Ralf, Isik, Leyla, Tenenbaum, Joshua, Konkle, Talia, Naselaris, Thomas, Stachenfeld, Kimberly, Tavares, Zenna, Tsao, Doris, Yildirim, Ilker, Kriegeskorte, Nikolaus
Vision is widely understood as an inference problem. However, two contrasting conceptions of the inference process have each been influential in research on biological vision as well as the engineering of machine vision. The first emphasizes bottom-u
Externí odkaz:
http://arxiv.org/abs/2401.06005
Autor:
Häfner, Gregor, Müller, Marcus
The cellular environment, characterized by its intricate composition and spatial organization, hosts a variety of organelles, ranging from membrane-bound ones to membraneless structures that are formed through liquid-liquid phase separation. Cells sh
Externí odkaz:
http://arxiv.org/abs/2312.12018
Publikováno v:
Proceedings of the National Academy of Sciences (2023), 120(48), e2306275120
Big data and large-scale machine learning have had a profound impact on science and engineering, particularly in fields focused on forecasting and prediction. Yet, it is still not clear how we can use the superior pattern matching abilities of machin
Externí odkaz:
http://arxiv.org/abs/2311.12579