Zobrazeno 1 - 10
of 20 271
pro vyhledávání: '"Morabito, A"'
Coupling between relativistic jets launched by accreting supermassive black holes and the surrounding gaseous media is a vital ingredient in galaxy evolution models. To constrain the environments in which this feedback takes place over cosmic time, w
Externí odkaz:
http://arxiv.org/abs/2407.18744
Digital Twins (DTs) are set to become a key enabling technology in future wireless networks, with their use in network management increasing significantly. We developed a DT framework that leverages the heterogeneity of network access technologies as
Externí odkaz:
http://arxiv.org/abs/2407.15520
Autor:
de Jong, J. M. G. H. J., van Weeren, R. J., Sweijen, F., Oonk, J. B. R., Shimwell, T. W., Offringa, A. R., Morabito, L. K., Röttgering, H. J. A., Kondapally, R., Escott, E. L., Best, P. N., Bondi, M., Ye, H., Petley, J. W.
We present the deepest wide-field 115-166 MHz image at sub-arcsecond resolution spanning an area of 2.5 by 2.5 degrees centred at the ELAIS-N1 deep field. To achieve this, we improved the calibration for the International LOFAR Telescope. This enhanc
Externí odkaz:
http://arxiv.org/abs/2407.13247
Autor:
Behera, Adarsh Prasad, Daubaris, Paulius, Bravo, Iñaki, Gallego, José, Morabito, Roberto, Widmer, Joerg, Champati, Jaya Prakash Varma
On-device inference holds great potential for increased energy efficiency, responsiveness, and privacy in edge ML systems. However, due to less capable ML models that can be embedded in resource-limited devices, use cases are limited to simple infere
Externí odkaz:
http://arxiv.org/abs/2407.11061
As the use of Large Language Models (LLMs) becomes more widespread, understanding their self-evaluation of confidence in generated responses becomes increasingly important as it is integral to the reliability of the output of these models. We introdu
Externí odkaz:
http://arxiv.org/abs/2405.16282
Autor:
Das, Soumyadeep, Smith, Daniel J. B., Haskell, Paul, Hardcastle, Martin J., Best, Philip N., Duncan, Kenneth J., Arnaudova, Marina I., Shenoy, Shravya, Kondapally, Rohit, Cochrane, Rachel K., Drake, Alyssa B., Gürkan, Gülay, Małek, Katarzyna, Morabito, Leah K., Prandoni, Isabella
Spectral energy distribution (SED) fitting has been extensively used to determine the nature of the faint radio source population. Recent efforts have combined fits from multiple SED-fitting codes to account for the host galaxy and any active nucleus
Externí odkaz:
http://arxiv.org/abs/2405.01624
This article introduces Follow-Me AI, a concept designed to enhance user interactions with smart environments, optimize energy use, and provide better control over data captured by these environments. Through AI agents that accompany users, Follow-Me
Externí odkaz:
http://arxiv.org/abs/2404.12486
The Hierarchical Inference (HI) paradigm employs a tiered processing: the inference from simple data samples are accepted at the end device, while complex data samples are offloaded to the central servers. HI has recently emerged as an effective meth
Externí odkaz:
http://arxiv.org/abs/2406.09424
Autor:
Morabito, Francesco, Trifa, Ibrahim
Given a pre-monotone Lagrangian link, we obtain Hofer energy estimates for Hamiltonian diffeomorphisms preserving it. Such estimates depend on the braid type of the Hamiltonian diffeomorphism only, and the natural language to talk about this phenomen
Externí odkaz:
http://arxiv.org/abs/2404.01052
Autor:
Vladisavlevici, I. -M., Vlachos, C., Dubois, J. -L., Huerta, A., Agarwal, S., Ahmed, H., Apiñaniz, J. I., Cernaianu, M., Gugiu, M., Krupka, M., Lera, R., Morabito, A., Sangwan, D., Ursescu, D., Curcio, A., Fefeu, N., Pérez-Hernández, J. A., Vacek, T., Vicente, P., Woolsey, N., Gatti, G., Rodríguez-Frías, M. D., Santos, J. J., Bradford, P. W., Ehret, M.
We present a novel scheme for rapid quantitative analysis of debris generated during experiments with solid targets following relativistic laser-plasma interaction at high-power laser facilities. Experimental data indicates that predictions by availa
Externí odkaz:
http://arxiv.org/abs/2403.10431