Zobrazeno 1 - 10
of 7 332
pro vyhledávání: '"Ă. Svendsen"'
Embedding materials in optical cavities has emerged as an intriguing perspective for controlling quantum materials, but a key challenge lies in measuring properties of the embedded matter. Here, we propose a framework for probing strongly correlated
Externí odkaz:
http://arxiv.org/abs/2410.21515
Autor:
Voskakis, Dimitris, Føre, Martin, Svendsen, Eirik, Liland, Aleksander Perlic, Planellas, Sonia Rey, Eguiraun, Harkaitz, Klebert, Pascal
The aquaculture industry is constantly making efforts to improve fish welfare while maintaining the ethically sustainable farming practises. This work presents an enhanced tank environment designed for testing and developing novel combinations of tec
Externí odkaz:
http://arxiv.org/abs/2409.14730
Autor:
Khorrami, Mohammad S., Goyal, Pawan, Mianroodi, Jaber R., Svendsen, Bob, Benner, Peter, Raabe, Dierk
The purpose of the current work is the development and comparison of Fourier neural operators (FNOs) for surrogate modeling of the quasi-static mechanical response of polycrystalline materials. Three types of such FNOs are considered here: a physics-
Externí odkaz:
http://arxiv.org/abs/2408.15408
Autor:
Olsen, Markus Ditlev Sjøgren, Ambsdorf, Jakob, Lin, Manxi, Taksøe-Vester, Caroline, Svendsen, Morten Bo Søndergaard, Christensen, Anders Nymark, Nielsen, Mads, Tolsgaard, Martin Grønnebæk, Feragen, Aasa, Pegios, Paraskevas
Congenital malformations of the brain are among the most common fetal abnormalities that impact fetal development. Previous anomaly detection methods on ultrasound images are based on supervised learning, rely on manual annotations, and risk missing
Externí odkaz:
http://arxiv.org/abs/2408.03654
Autor:
La Quatra, Moreno, Turco, Maria Francesca, Svendsen, Torbjørn, Salvi, Giampiero, Orozco-Arroyave, Juan Rafael, Siniscalchi, Sabato Marco
This work is concerned with devising a robust Parkinson's (PD) disease detector from speech in real-world operating conditions using (i) foundational models, and (ii) speech enhancement (SE) methods. To this end, we first fine-tune several foundation
Externí odkaz:
http://arxiv.org/abs/2406.16128
Autor:
Jaramillo-Fernandez, Juliana, Poblet, Martin, Alonso-Tomás, David, Bertelsen, Christian Vinther, López-Aymerich, Elena, Arenas-Ortega, Daniel, Svendsen, Winnie E., Capuj, Néstor E., Romano-Rodríguez, Albert, Navarro-Urrios, Daniel
Nanomechanical resonators can serve as ultrasensitive, miniaturized force probes. While vertical structures like nanopillars are ideal for this purpose, transducing their motion is challenging. Pillar-based photonic crystals (PhCs) offer a potential
Externí odkaz:
http://arxiv.org/abs/2405.18319
We propose a novel mechanism for generating single photons in the mid-Infrared (MIR) using a solid-state or molecular quantum emitter. The scheme utilises cavity QED effects to selectively enhance a Frank-Condon transition, deterministically preparin
Externí odkaz:
http://arxiv.org/abs/2405.12777
Autor:
Lu, I-Te, Shin, Dongbin, Svendsen, Mark Kamper, Hübener, Hannes, De Giovannini, Umberto, Latini, Simone, Ruggenthaler, Michael, Rubio, Angel
Strong laser pulses can control superconductivity, inducing non-equilibrium transient pairing by leveraging strong-light matter interaction. Here we demonstrate theoretically that equilibrium ground-state phonon-mediated superconductive pairing can b
Externí odkaz:
http://arxiv.org/abs/2404.08122
Publikováno v:
Quantum 8, 1488 (2024)
We establish the concept of topological pumping in one-dimensional systems with long-range couplings and apply it to the transport of a photon in quantum optical systems. In our theoretical investigation, we introduce an extended version of the Rice-
Externí odkaz:
http://arxiv.org/abs/2404.05570
Autor:
Wong, Chun Kit, Ngo, Mary, Lin, Manxi, Bashir, Zahra, Heen, Amihai, Svendsen, Morten Bo Søndergaard, Tolsgaard, Martin Grønnebæk, Christensen, Anders Nymark, Feragen, Aasa
Despite the rapid development of AI models in medical image analysis, their validation in real-world clinical settings remains limited. To address this, we introduce a generic framework designed for deploying image-based AI models in such settings. U
Externí odkaz:
http://arxiv.org/abs/2404.00032