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pro vyhledávání: '"Schmidt, Frank P."'
An overview is given of the methods and preliminary results from dedicated beam studies on three topics conducted over five days in July 2023. In the first study, the Fermilab Booster magnets were held constant at magnetic fields corresponding to the
Externí odkaz:
http://arxiv.org/abs/2408.08987
As deep learning models continue to advance and are increasingly utilized in real-world systems, the issue of robustness remains a major challenge. Existing certified training methods produce models that achieve high provable robustness guarantees at
Externí odkaz:
http://arxiv.org/abs/2307.13078
The Gottesman-Kitaev-Preskill (GKP) code offers the possibility to encode higher-dimensional qudits into individual bosonic modes with, for instance, photonic excitations. Since photons enable the reliable transmission of quantum information over lon
Externí odkaz:
http://arxiv.org/abs/2303.16034
Many challenges from natural world can be formulated as a graph matching problem. Previous deep learning-based methods mainly consider a full two-graph matching setting. In this work, we study the more general partial matching problem with multi-grap
Externí odkaz:
http://arxiv.org/abs/2212.00780
We present an exact rate analysis for a secret key that can be shared among two parties employing a linear quantum repeater chain. One of our main motivations is to address the question whether simply placing quantum memories along a quantum communic
Externí odkaz:
http://arxiv.org/abs/2203.10318
Autor:
Keller, Karsten, Sagoschen, Ingo, Farmakis, Ioannis T., Mohr, Katharina, Valerio, Luca, Wild, Johannes, Barco, Stefano, Schmidt, Frank P., Gori, Tommaso, Espinola-Klein, Christine, Münzel, Thomas, Lurz, Philipp, Konstantinides, Stavros, Hobohm, Lukas
Publikováno v:
In Research and Practice in Thrombosis and Haemostasis August 2024 8(6)
Autor:
Schmidt, Frank, van Loock, Peter
We propose two schemes to obtain Gottesman-Kitaev-Preskill (GKP) error syndromes by means of linear optical operations, homodyne measurements and GKP ancillae. This includes showing that for a concatenation of GKP codes with a $[n,k,d]$ stabilizer co
Externí odkaz:
http://arxiv.org/abs/2110.05315
Recent work has shown that it is possible to learn neural networks with provable guarantees on the output of the model when subject to input perturbations, however these works have focused primarily on defending against adversarial examples for image
Externí odkaz:
http://arxiv.org/abs/2007.00147
Autor:
van Loock, Peter, Alt, Wolfgang, Becher, Christoph, Benson, Oliver, Boche, Holger, Deppe, Christian, Eschner, Jürgen, Höfling, Sven, Meschede, Dieter, Michler, Peter, Schmidt, Frank, Weinfurter, Harald
We analyze elementary building blocks for quantum repeaters based on fiber channels and memory stations. Implementations are considered for three different physical platforms, for which suitable components are available: quantum dots, trapped atoms a
Externí odkaz:
http://arxiv.org/abs/1912.10123
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