Zobrazeno 1 - 10
of 68 628
pro vyhledávání: '"P, Ramon"'
Autor:
Napolitano, Lucas, Myers, Adam D., Aguilar, Jessica, Ahlen, Steven, Bianchi, Davide, Brooks, David, Claybaugh, Todd, Cole, Shaun, de la Macorra, Axel, Dey, Biprateep, Font-Ribera, Andreu, Forero-Romero, Jaime E., Gaztañaga, Enrique, Gontcho, Satya Gontcho A, Gutierrez, Gaston, Honscheid, Klaus, Juneau, Stephanie, Lambert, Andrew, Landriau, Martin, Guillou, Laurent Le, Meisner, Aaron, Miquel, Ramon, Moustakas, John, Newman, Jeffrey A., Prada, Francisco, Pérez-Ràfols, Ignasi, Rossi, Graziano, Sanchez, Eusebio, Schlegel, David, Schubnell, Michael, Sprayberry, David, Tarlé, Gregory, Weaver, Benjamin Alan, Zou, Hu
In this paper, we study how absorption-line systems affect the spectra and redshifts of quasars (QSOs), using catalogs of Mg II absorbers from the early data release (EDR) and first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI
Externí odkaz:
http://arxiv.org/abs/2412.15383
Autor:
Naumkina, Anna, Plaza, Ramón G.
A family of generalized Korteweg-de Vries-Burgers equations in one space dimension with a nonlinear source is considered. The purpose of this contribution is twofold. On one hand, the local well-posedness of the Cauchy problem on periodic Sobolev spa
Externí odkaz:
http://arxiv.org/abs/2412.14041
Autor:
Bahl, Henning, Elmer, Nina, Favaro, Luigi, Haußmann, Manuel, Plehn, Tilman, Winterhalder, Ramon
Neural networks for LHC physics have to be accurate, reliable, and controlled. Using surrogate loop amplitudes as a use case, we first show how activation functions can be systematically tested with KANs. For reliability and control, we learn uncerta
Externí odkaz:
http://arxiv.org/abs/2412.12069
Autor:
Whitford, Abbé M., Rivera-Morales, Hugo, Howlett, Cullan, Vargas-Magaña, Mariana, Fromenteau, Sébastien, Davis, Tamara M., Pérez-Fernández, Alejandro, de Mattia, Arnaud, Ahlen, Steven, Bianchi, Davide, Brooks, David, Burtin, Etienne, Claybaugh, Todd, de la Macorra, Axel, Doel, Peter, Ferraro, Simone, Forero-Romero, Jaime E., Gaztañaga, Enrique, Gontcho, Satya Gontcho A, Gutierrez, Gaston, Juneau, Stephanie, Kehoe, Robert, Kirkby, David, Kisner, Theodore, Koposov, Sergey, Landriau, Martin, Guillou, Laurent Le, Meisner, Aaron, Miquel, Ramon, Prada, Francisco, Pérez-Ràfols, Ignasi, Rossi, Graziano, Sanchez, Eusebio, Schubnell, Michael, Sprayberry, David, Tarlé, Gregory, Weaver, Benjamin Alan, Zarrouk, Pauline, Zou, Hu
In the early Universe, neutrinos decouple quickly from the primordial plasma and propagate without further interactions. The impact of free-streaming neutrinos is to create a temporal shift in the gravitational potential that impacts the acoustic wav
Externí odkaz:
http://arxiv.org/abs/2412.05990
Numerical N-body simulations are commonly used to explore stability regions around exoplanets, offering insights into the possible existence of satellites and ring systems. This study aims to utilize Machine Learning (ML) techniques to generate predi
Externí odkaz:
http://arxiv.org/abs/2412.04568
We prove that every element of a Lipschitz-free space admits an expression as a convex series of elements with compact support. As a consequence, we conclude that all extreme points of the unit ball of Lipschitz-free spaces are elementary molecules,
Externí odkaz:
http://arxiv.org/abs/2412.04312
The theory of pebble accretion (PA) has become a popular planet formation theory during the past decade. However, PA studies generally rely on large planetary embryos, much larger than those expected from the streaming instability. This study analyse
Externí odkaz:
http://arxiv.org/abs/2412.02571
In this paper, we address a data dependent modification of the moving least squares (MLS) problem. We propose a novel approach by replacing the traditional weight functions with new functions that assign smaller weights to nodes that are close to dis
Externí odkaz:
http://arxiv.org/abs/2412.02304
Shepard method is a fast algorithm that has been classically used to interpolate scattered data in several dimensions. This is an important and well-known technique in numerical analysis founded in the main idea that data that is far away from the ap
Externí odkaz:
http://arxiv.org/abs/2412.02286
The first paper in this series introduced a new approach to strong convergence of random matrices that is based primarily on soft arguments. This method was applied to achieve a refined qualitative and quantitative understanding of strong convergence
Externí odkaz:
http://arxiv.org/abs/2412.00593