Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Thomas Fösel"'
Autor:
Kevin Reuer, Jonas Landgraf, Thomas Fösel, James O’Sullivan, Liberto Beltrán, Abdulkadir Akin, Graham J. Norris, Ants Remm, Michael Kerschbaum, Jean-Claude Besse, Florian Marquardt, Andreas Wallraff, Christopher Eichler
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-7 (2023)
Abstract Realizing the full potential of quantum technologies requires precise real-time control on time scales much shorter than the coherence time. Model-free reinforcement learning promises to discover efficient feedback strategies from scratch wi
Externí odkaz:
https://doaj.org/article/6df00c495d4a4b6fb8aae0c362b34f3d
Autor:
Juliane Doster, Tirth Shah, Thomas Fösel, Philipp Paulitschke, Florian Marquardt, Eva M. Weig
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-7 (2022)
Coupled nanomechanical resonator arrays serve as model systems to study collective dynamical phenomena. Doster et al. introduce a two-dimensional array of pillar resonators encoding a mechanical polarization degree of freedom for analyzing polarizati
Externí odkaz:
https://doaj.org/article/649d070ab01d449a8284459637e6d214
Publikováno v:
Quantum, Vol 6, p 714 (2022)
Neural networks have emerged as a powerful way to approach many practical problems in quantum physics. In this work, we illustrate the power of deep learning to predict the dynamics of a quantum many-body system, where the training is $\textit{based
Externí odkaz:
https://doaj.org/article/11dc7b9df3fa4854bd92d2fab99306ff
Publikováno v:
Physical Review X, Vol 8, Iss 3, p 031084 (2018)
Machine learning with artificial neural networks is revolutionizing science. The most advanced challenges require discovering answers autonomously. In the domain of reinforcement learning, control strategies are improved according to a reward functio
Externí odkaz:
https://doaj.org/article/a2fc5036028f463993820ffde303eede
L lines, C points and Chern numbers: understanding band structure topology using polarization fields
Publikováno v:
New Journal of Physics, Vol 19, Iss 11, p 115013 (2017)
Topology has appeared in different physical contexts. The most prominent application is topologically protected edge transport in condensed matter physics. The Chern number, the topological invariant of gapped Bloch Hamiltonians, is an important quan
Externí odkaz:
https://doaj.org/article/4acf1e7fa2054d0ba9128ca073b97ba7
Publikováno v:
Physik in unserer Zeit. 50:220-227
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7637136fffffa500ce48151816d4c0f
https://doi.org/10.1002/piuz.201901549
https://doi.org/10.1002/piuz.201901549
Publikováno v:
Physical Review X
Physical Review X, Vol 8, Iss 3, p 031084 (2018)
Physical Review X, Vol 8, Iss 3, p 031084 (2018)
Machine learning with artificial neural networks is revolutionizing science. The most advanced challenges require discovering answers autonomously. This is the domain of reinforcement learning, where control strategies are improved according to a rew
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d73b4fd865ab48836fd155377ff72d33
Autor:
Thomas Fösel, Gabriele-Birgit Kraus
Publikováno v:
Beatmung von Kindern in Anästhesie und Intensivmedizin ISBN: 9783540566731
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e95cf604482c1945237a3c59df2c4686
https://doi.org/10.1007/978-3-642-45732-6_20
https://doi.org/10.1007/978-3-642-45732-6_20