Zobrazeno 1 - 10
of 8 529
pro vyhledávání: '"Zarei, P."'
Autor:
Zarei, Sanaz
Photonic neural networks capable of rapid programming are indispensable to realize many functionalities. Phase change technology can provide nonvolatile programmability in photonic neural networks. Integrating direct laser writing technique with phas
Externí odkaz:
http://arxiv.org/abs/2411.05723
This paper proposes an AI-based scheme for islanding detection in active distribution networks. By reviewing existing studies, it is clear that there are several gaps in the field to ensure reliable islanding detection, including (i) model complexity
Externí odkaz:
http://arxiv.org/abs/2410.13926
Interfering-or-not-interfering quantum key distribution (INI-QKD) is an innovative protocol whose performance surpasses existing twin-field protocol variants. In this study, we introduce an additional step of advantage distillation (AD) after the qua
Externí odkaz:
http://arxiv.org/abs/2410.00205
Autor:
Wulle, Dennis, Zarei, Masoumeh
The present article explores the relationship between positive sectional curvature and the geometric and topological properties of Eschenburg $6$-orbifolds. First, we prove that positive sectional curvature imposes restrictions on the their singular
Externí odkaz:
http://arxiv.org/abs/2409.19105
Autor:
Zarei, Sanaz
A thorough investigation of diffractive optical neural networks provides evidence that such networks are not capable of performing complex tasks. In this short report, these evidences are represented succinctly.
Externí odkaz:
http://arxiv.org/abs/2407.18493
We study a two-field model where a quintessence field with an exponential potential $e^{-\beta\phi/M_P}$ is coupled to the Higgs field. It is claimed that this model is consistent with the proposed Swampland conjecture. We check this claim by calcula
Externí odkaz:
http://arxiv.org/abs/2406.15790
We investigate the sensing capacity of non-equilibrium dynamics in quantum systems exhibiting Bloch oscillations. By focusing on the resource efficiency of the probe, quantified by quantum Fisher information, we find different scaling behaviors in tw
Externí odkaz:
http://arxiv.org/abs/2406.13921
Autor:
Zarei, Arman, Rezaei, Keivan, Basu, Samyadeep, Saberi, Mehrdad, Moayeri, Mazda, Kattakinda, Priyatham, Feizi, Soheil
Recent text-to-image diffusion-based generative models have the stunning ability to generate highly detailed and photo-realistic images and achieve state-of-the-art low FID scores on challenging image generation benchmarks. However, one of the primar
Externí odkaz:
http://arxiv.org/abs/2406.07844
Identifying the origin of data is crucial for data provenance, with applications including data ownership protection, media forensics, and detecting AI-generated content. A standard approach involves embedding-based retrieval techniques that match qu
Externí odkaz:
http://arxiv.org/abs/2406.02836
We examine the impact of time delay on two coupled massive oscillators within the second-order Kuramoto model, which is relevant to the operations of real-world networks that rely on signal transmission speed constraints. Our analytical and numerical
Externí odkaz:
http://arxiv.org/abs/2406.01208