Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Bravo-Abad Jorge"'
Reinforcement learning is a subfield of machine learning that is having a huge impact in the different conventional disciplines, including physical sciences. Here, we show how reinforcement learning methods can be applied to solve optimization proble
Externí odkaz:
http://arxiv.org/abs/2408.15727
Publikováno v:
Nanophotonics, Vol 9, Iss 5, Pp 1041-1057 (2020)
Deep learning has become the dominant approach in artificial intelligence to solve complex data-driven problems. Originally applied almost exclusively in computer-science areas such as image analysis and nature language processing, deep learning has
Externí odkaz:
https://doaj.org/article/9361b3f9bf6a4a39a9d8ea058817114b
Long-range interactions are a key resource in many quantum phenomena and technologies. Free-space photons mediate power-law interactions but lack tunability and suffer from decoherence processes due to their omnidirectional emission. Engineered diele
Externí odkaz:
http://arxiv.org/abs/2406.13042
Publikováno v:
Phys. Rev. B 109, 085137 (2024)
The Weyl-Mott insulator (WMI) has been postulated as a novel type of correlated insulator with non-trivial topological properties. We introduce a minimal microscopic model that captures generic features of the WMI transition in Weyl semimetals. The m
Externí odkaz:
http://arxiv.org/abs/2307.10102
Generative adversarial networks (GANs) are one of the most robust and versatile techniques in the field of generative artificial intelligence. In this work, we report on an application of GANs in the domain of synthetic spectral data generation, offe
Externí odkaz:
http://arxiv.org/abs/2307.07454
Publikováno v:
Sci. Adv.9,eadf8257(2023)
Fermi arcs, i.e., surface states connecting topologically-distinct Weyl points, represent a paradigmatic manifestation of the topological aspects of Weyl physics. Here, we investigate a light-matter interface based on the photonic counterpart of thes
Externí odkaz:
http://arxiv.org/abs/2210.09073
Tackling Multimodal Device Distributions in Inverse Photonic Design using Invertible Neural Networks
Inverse design, the process of matching a device or process parameters to exhibit a desired performance, is applied in many disciplines ranging from material design over chemical processes and to engineering. Machine learning has emerged as a promisi
Externí odkaz:
http://arxiv.org/abs/2208.14212
Publikováno v:
Phys. Rev. Applied. 16, 064006 (2021)
Deep learning is having a tremendous impact in many areas of computer science and engineering. Motivated by this success, deep neural networks are attracting an increasing attention in many other disciplines, including physical sciences. In this work
Externí odkaz:
http://arxiv.org/abs/2109.03114
Resonant transmission of light is a surface-wave assisted phenomenon that enables funneling light through subwavelength apertures milled in otherwise opaque metallic screens. In this work, we introduce a deep learning approach to efficiently compute
Externí odkaz:
http://arxiv.org/abs/2106.12898
Publikováno v:
Phys. Rev. A 103, 033511 (2021)
Weyl photons appear when two three-dimensional photonic bands with linear dispersion are degenerate at a single momentum point, labeled as Weyl point. These points have remarkable properties such as being robust topological monopoles of Berry curvatu
Externí odkaz:
http://arxiv.org/abs/2012.12885