Zobrazeno 1 - 10
of 1 679
pro vyhledávání: '"Pavanello, P."'
Autor:
Chen, Xin, Martinez, Jessica, Shao, Xuecheng, Riera, Marc, Paesani, Francesco, Andreussi, Oliviero, Pavanello, Michele
We present a reformulation of QM/MM as a fully quantum mechanical theory of interacting subsystems, all treated at the level of density functional theory (DFT). For the MM subsystem, which lacks orbitals, we assign an ad hoc electron density and appl
Externí odkaz:
http://arxiv.org/abs/2411.17844
Autor:
Marchesin, Federico, Hejda, Matěj, Carmona, Tzamn Melendez, Di Carlo, Stefano, Savino, Alessandro, Pavanello, Fabio, Van Vaerenbergh, Thomas, Bienstman, Peter
Matrix-vector multiplications (MVMs) are essential for a wide range of applications, particularly in modern machine learning and quantum computing. In photonics, there is growing interest in developing architectures capable of performing linear opera
Externí odkaz:
http://arxiv.org/abs/2411.02243
We propose a novel hybrid mode interferometer (HMI) leveraging the interference of hybridized TE-TM modes in a silicon-on-insulator (SOI) waveguide integrated with a GeSe phase change material (PCM) layer. The SOI waveguide's dimensions are optimized
Externí odkaz:
http://arxiv.org/abs/2410.19587
The kinetic energy (KE) kernel, which is defined as the second order functional derivative of the KE functional with respect to density, is the key ingredient to the construction of KE models for orbital free density functional theory (OFDFT) applica
Externí odkaz:
http://arxiv.org/abs/2409.12625
Autor:
Hejda, Matěj, Marchesin, Federico, Papadimitriou, George, Gizopoulos, Dimitris, Charbonnier, Benoit, Orobtchouk, Régis, Bienstman, Peter, Van Vaerenbergh, Thomas, Pavanello, Fabio
In this work, we discuss our vision for neuromorphic accelerators based on integrated photonics within the framework of the Horizon Europe NEUROPULS project. Augmented integrated photonic architectures that leverage phase-change and III-V materials f
Externí odkaz:
http://arxiv.org/abs/2407.06240
Autor:
de Queiroz, Mauricio Gomes, Jimenez, Paul, Cardoso, Raphael, Costa, Mateus Vidaletti, Abdalla, Mohab, O'Connor, Ian, Bosio, Alberto, Pavanello, Fabio
Publikováno v:
APL Mach. Learn. 1 September 2024; 2 (3): 036109
Photonic Neural Networks (PNNs) are gaining significant interest in the research community due to their potential for high parallelization, low latency, and energy efficiency. PNNs compute using light, which leads to several differences in implementa
Externí odkaz:
http://arxiv.org/abs/2406.18757
The optimization of fuel-optimal low-thrust collision avoidance maneuvers (CAMs) in scenarios involving multiple encounters between spacecraft is addressed. The optimization's objective is the minimization of the total fuel consumption while respecti
Externí odkaz:
http://arxiv.org/abs/2406.03654
A simple and reliable algorithm for collision avoidance maneuvers (CAMs), capable of computing impulsive, multi-impulsive, and low-thrust maneuvers, is proposed. The probability of collision (PoC) is approximated by a polynomial of arbitrary order as
Externí odkaz:
http://arxiv.org/abs/2406.01949
Autor:
Jimenez, Paul, Cardoso, Raphael, de Queiroz, Maurìcio Gomes, Abdalla, Mohab, Marchand, Cédric, Letartre, Xavier, Pavanello, Fabio
The study of regularity in signals can be of great importance, typically in medicine to analyse electrocardiogram (ECG) or electromyography (EMG) signals, but also in climate studies, finance or security. In this work we focus on security primitives
Externí odkaz:
http://arxiv.org/abs/2402.17488
Autor:
B., Jessica A. Martinez, De Santis, Matteo, Pavanello, Michele, Vallet, Valérie, Gomes, André Severo Pereira
In this work we introduce a novel subsystem-based electronic structure embedding method that combines the projection-based block-orthogonalized Manby-Miller embedding (BOMME) with the density-based Frozen Density Embedding (FDE) methods. Our approach
Externí odkaz:
http://arxiv.org/abs/2401.14548