Zobrazeno 1 - 10
of 287 084
pro vyhledávání: '"Fonseca AS"'
In this study, we meticulously construct a 3-form Lagrangian designed to mimic the dynamics of both dust matter in the past and dark energy driving the acceleration in the present era. A dynamical systems approach is used to investigate the underlyin
Externí odkaz:
http://arxiv.org/abs/2410.11658
Autor:
Shin, Kaitlyn, Leung, Calvin, Simha, Sunil, Andersen, Bridget C., Fonseca, Emmanuel, Nimmo, Kenzie, Bhardwaj, Mohit, Brar, Charanjot, Chatterjee, Shami, Cook, Amanda M., Gaensler, B. M., Joseph, Ronniy C., Jow, Dylan, Kaczmarek, Jane, Kahinga, Lordrick, Kaspi, Victoria M., Kharel, Bikash, Lanman, Adam E., Lazda, Mattias, Main, Robert A., Mas-Ribas, Lluis, Masui, Kiyoshi W., Mena-Parra, Juan, Michilli, Daniele, Pandhi, Ayush, Patil, Swarali Shivraj, Pearlman, Aaron B., Pleunis, Ziggy, Prochaska, J. Xavier, Rafiei-Ravandi, Masoud, Sammons, Mawson W., Sand, Ketan R., Smith, Kendrick, Stairs, Ingrid
Fast radio bursts (FRBs) are unique probes of extragalactic ionized baryonic structure as each signal, through its burst properties, holds information about the ionized matter it encounters along its sightline. FRB 20200723B is a burst with a scatter
Externí odkaz:
http://arxiv.org/abs/2410.07307
Autor:
Júnior, W. L. Aldá, Alves, G. A., Amarilo, K. M., Filho, M. Barroso Ferreira, Bernardes, C. A., da Costa, E. M., da Graça, U. de Freitas Carneiro, Damião, D. de Jesus, Fonseca, S. de Souza, Mendes, L. M. Domingues, Donadelli, M., da Silveira, G. Gil, Hensel, C., Jahnke, C., Malbouisson, H., Marin, J . L., Martins, D. E., Massafferri, A., Herrera, C. Mora, Nasteva, I., de Souza, E. E. Purcino, Queiroz, F. S., Rangel, M., Teles, P. Rebello, Thiel, M., Tomei, T. R. F. P., Pereira, A. Vilela
This proposal outlines the future plans of the Brazilian High-Energy Physics (HEP) community for upcoming collider experiments. With the construction of new particle colliders on the horizon and the ongoing operation of the High-Luminosity LHC, sever
Externí odkaz:
http://arxiv.org/abs/2410.05205
In Reinforcement Learning (RL), multi-armed Bandit (MAB) problems have found applications across diverse domains such as recommender systems, healthcare, and finance. Traditional MAB algorithms typically assume stationary reward distributions, which
Externí odkaz:
http://arxiv.org/abs/2410.04217
Autor:
Bell, Andrew, Fonseca, Joao
Recent high profile incidents in which the use of Large Language Models (LLMs) resulted in significant harm to individuals have brought about a growing interest in AI safety. One reason LLM safety issues occur is that models often have at least some
Externí odkaz:
http://arxiv.org/abs/2410.05305
Autor:
Waters, Dacen, Waleffe, Derek, Thompson, Ellis, Arreguin-Martinez, Esmeralda, Fonseca, Jordan, Poirier, Thomas, Edgar, James H., Watanabe, Kenji, Taniguchi, Takashi, Xu, Xiaodong, Cobden, David, Yankowitz, Matthew
Field-effect devices constructed by stacking flakes of van der Waals (vdW) materials, with hexagonal boron nitride (hBN) playing the role of gate dielectric, often exhibit virtually no hysteresis in their characteristics. This permits exquisitely det
Externí odkaz:
http://arxiv.org/abs/2410.02699
Autor:
Chacon-Chamorro, Manuela, Giraldo, Luis Felipe, Quijano, Nicanor, Vargas-Panesso, Vicente, González, César, Pinzón, Juan Sebastián, Manrique, Rubén, Ríos, Manuel, Fonseca, Yesid, Gómez-Barrera, Daniel, Perdomo-Pérez, Mónica
Resilience refers to the ability of systems to withstand, adapt to, and recover from disruptive events. While studies on resilience have attracted significant attention across various research domains, the precise definition of this concept within th
Externí odkaz:
http://arxiv.org/abs/2409.13187
Autor:
Fonseca, Tássylla O., Mendonça, Bruno H. S., de Moraes, Elizane E., de Oliveira, Alan B., Barbosa, Marcia C.
Through Monte Carlo simulations and the Associating Lattice Gas Model, the phases of a two-dimensional fluid under hydrophilic confinement are evaluated. The model, in its unconfined version, reproduces the anomalous behavior of water regarding its d
Externí odkaz:
http://arxiv.org/abs/2409.13089
Autor:
Peixoto, Myron David Lucena Campos, Baia, Davy de Medeiros, Nascimento, Nathalia, Alencar, Paulo, Fonseca, Baldoino, Ribeiro, Márcio
Background: Manual testing is vital for detecting issues missed by automated tests, but specifying accurate verifications is challenging. Aims: This study aims to explore the use of Large Language Models (LLMs) to produce verifications for manual tes
Externí odkaz:
http://arxiv.org/abs/2409.12405
Autor:
da Silva, Davide Clode, Bernardes, Marina Musse, Ceretta, Nathalia Giacomini, de Souza, Gabriel Vaz, Silva, Gabriel Fonseca, Bordini, Rafael Heitor, Musse, Soraia Raupp
Machine learning has significantly advanced healthcare by aiding in disease prevention and treatment identification. However, accessing patient data can be challenging due to privacy concerns and strict regulations. Generating synthetic, realistic da
Externí odkaz:
http://arxiv.org/abs/2409.04424