Zobrazeno 1 - 10
of 15 323
pro vyhledávání: '"Geraci, A. A."'
This paper presents a new system model to evaluate the capacity and power consumption of multi-layer 6G networks utilising the upper mid-band (FR3). The model captures heterogeneous 4G, 5G, and 6G deployments, analyzing their performance under differ
Externí odkaz:
http://arxiv.org/abs/2411.09660
Autor:
Elahi, Shafaq Gulzar, Schut, Martine, Dana, Andrew, Grinin, Alexey, Bose, Sougato, Mazumdar, Anupam, Geraci, Andrew
The Quantum Gravity Mediated Entanglement (QGEM) protocol offers a novel method to probe the quantumness of gravitational interactions at non-relativistic scales. This protocol leverages the Stern-Gerlach effect to create $\mathcal{O}(\sim \mu m)$ sp
Externí odkaz:
http://arxiv.org/abs/2411.02325
We propose a practical framework for designing a physically consistent reconfigurable intelligent surface (RIS) to overcome the inefficiency of the conventional phase gradient approach. For a section of Cape Town and across three different coverage e
Externí odkaz:
http://arxiv.org/abs/2409.17738
Autor:
Sprague, Jacob R., Larson, Shane L., Wang, Zhiyuan, Klomp, Shelby, Laeuger, Andrew, Winstone, George, Aggarwal, Nancy, Geraci, Andrew A., Kalogera, Vicky
Ultralight scalar fields can experience runaway `superradiant' amplification near spinning black holes, resulting in a macroscopic `axion cloud' which slowly dissipates via continuous monochromatic gravitational waves. For a particular range of boson
Externí odkaz:
http://arxiv.org/abs/2409.03714
In this article, we introduce a method to optimize 5G massive multiple-input multiple-output (mMIMO) connectivity for unmanned aerial vehicles (UAVs) on aerial highways through strategic cell association. UAVs operating in 3D space encounter distinct
Externí odkaz:
http://arxiv.org/abs/2409.01812
Autor:
Menon, Karthik, Zanoni, Andrea, Khan, Owais, Geraci, Gianluca, Nieman, Koen, Schiavazzi, Daniele E., Marsden, Alison L.
Simulations of coronary hemodynamics have improved non-invasive clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches
Externí odkaz:
http://arxiv.org/abs/2409.02247
Autor:
Laing, Shaun, Klomp, Shelby, Winstone, George, Grinin, Alexey, Dana, Andrew, Wang, Zhiyuan, Widyatmodjo, Kevin Seca, Bateman, James, Geraci, Andrew A.
Optically-levitated dielectric objects are promising for precision force, acceleration, torque, and rotation sensing due to their extreme environmental decoupling. While many levitated opto-mechanics experiments employ spherical objects, for some app
Externí odkaz:
http://arxiv.org/abs/2409.00782
Autor:
Zanoni, Andrea, Geraci, Gianluca, Salvador, Matteo, Marsden, Alison L., Schiavazzi, Daniele E.
We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a one-dimensional neural active manifold (NeurAM) capturing the model outp
Externí odkaz:
http://arxiv.org/abs/2408.03534
Autor:
Nunez, David, Wilhelmi, Francesc, Galati-Giordano, Lorenzo, Geraci, Giovanni, Bellalta, Boris
IEEE 802.11 networks continuously adapt to meet the stringent requirements of emerging applications like cloud gaming, eXtended Reality (XR), and video streaming services, which require high throughput, low latency, and high reliability. To address t
Externí odkaz:
http://arxiv.org/abs/2407.16390
We introduce a new training algorithm for variety of deep neural networks that utilize random complex exponential activation functions. Our approach employs a Markov Chain Monte Carlo sampling procedure to iteratively train network layers, avoiding g
Externí odkaz:
http://arxiv.org/abs/2407.11894