Zobrazeno 1 - 10
of 2 336
pro vyhledávání: '"P. Kölle"'
Autor:
Koelle, Samson, Meila, Marina
Isometry pursuit is a convex algorithm for identifying orthonormal column-submatrices of wide matrices. It consists of a novel normalization method followed by multitask basis pursuit. Applied to Jacobians of putative coordinate functions, it helps i
Externí odkaz:
http://arxiv.org/abs/2411.18502
Autor:
Wilde, Benedikt, Kaiser, Manuel, Reinschmidt, Malte, Günther, Andreas, Koelle, Dieter, Fortágh, Jószef, Kleiner, Reinhold, Bothner, Daniel
Hybrid quantum systems are highly promising platforms for addressing important challenges of quantum information science and quantum sensing. Their implementation, however, is technologically non-trivial, since each component typically has unique exp
Externí odkaz:
http://arxiv.org/abs/2410.23269
Autor:
Tahouni-Bonab, Farnaz, Hepting, Matthias, Luibrand, Theodor, Cristiani, Georg, Schmid, Christoph, Logvenov, Gennady, Keimer, Bernhard, Kleiner, Reinhold, Koelle, Dieter, Guénon, Stefan
Strongly correlated insulators, such as Mott or charge-transfer insulators, exhibit a strong temperature dependence in their resistivity. Consequently, self-heating effects can lead to electrothermal instabilities in planar thin film devices of these
Externí odkaz:
http://arxiv.org/abs/2410.20521
Autor:
García-Pons, D., Pérez-Bailón, J., Méndiz, A., Júlvez, V., Hack, M., Wurster, K., Kleiner, R., Koelle, D., Martínez-Pérez, M. J.
Magnetic nanoparticles play a crucial role in different fields such as biomedicine or information and quantum technologies. These applications require nanoparticles with a single, well-defined energy minimum, free of metastable states, and characteri
Externí odkaz:
http://arxiv.org/abs/2410.14344
Autor:
Zielinski, Sebastian, Nüßlein, Jonas, Kölle, Michael, Gabor, Thomas, Linnhoff-Popien, Claudia, Feld, Sebastian
As contemporary quantum computers do not possess error correction, any calculation performed by these devices can be considered an involuntary approximation. To solve a problem on a quantum annealer, it has to be expressed as an instance of Quadratic
Externí odkaz:
http://arxiv.org/abs/2409.15891
Autor:
Roshani, Navid, Stein, Jonas, Zorn, Maximilian, Kölle, Michael, Altmann, Philipp, Linnhoff-Popien, Claudia
A central challenge in quantum machine learning is the design and training of parameterized quantum circuits (PQCs). Much like in deep learning, vanishing gradients pose significant obstacles to the trainability of PQCs, arising from various sources.
Externí odkaz:
http://arxiv.org/abs/2408.04751
Using a focused He$^+$ beam for nanopatterning and writing of Josephson barriers we fabricated specially shaped Josephson junctions of in-line geometry in YBa$_2$Cu$_3$O$_7$ thin film microbridges with an asymmetry ratio of critical currents of oppos
Externí odkaz:
http://arxiv.org/abs/2408.01521
Autor:
Kölle, Michael, Seidl, Daniel, Zorn, Maximilian, Altmann, Philipp, Stein, Jonas, Gabor, Thomas
Quantum Reinforcement Learning (QRL) offers potential advantages over classical Reinforcement Learning, such as compact state space representation and faster convergence in certain scenarios. However, practical benefits require further validation. QR
Externí odkaz:
http://arxiv.org/abs/2408.01187
Autor:
Kölle, Michael, Ahouzi, Afrae, Debus, Pascal, Çetiner, Elif, Müller, Robert, Schuman, Daniëlle, Linnhoff-Popien, Claudia
Quantum one-class support vector machines leverage the advantage of quantum kernel methods for semi-supervised anomaly detection. However, their quadratic time complexity with respect to data size poses challenges when dealing with large datasets. In
Externí odkaz:
http://arxiv.org/abs/2407.20753
Autor:
Kölle, Michael, Schneider, Karola, Egger, Sabrina, Topp, Felix, Phan, Thomy, Altmann, Philipp, Nüßlein, Jonas, Linnhoff-Popien, Claudia
In recent years, Multi-Agent Reinforcement Learning (MARL) has found application in numerous areas of science and industry, such as autonomous driving, telecommunications, and global health. Nevertheless, MARL suffers from, for instance, an exponenti
Externí odkaz:
http://arxiv.org/abs/2407.20739