Zobrazeno 1 - 10
of 5 151
pro vyhledávání: '"Ezzeddine, A."'
Autor:
Guo, Yanjun, Storm, Nicholas, Bergemann, Maria, Lian, Jianhui, Alexeeva, Sofya, Yan, Hongliang, Li, Yangyang, Ezzeddine, Rana, Jeffrey, Gerber, Chen, XueFei
Accurate measurements of europium abundances in cool stars are essential for an enhanced understanding of the r-process mechanisms. We measure the abundance of Eu in solar spectra and a sample of metal-poor stars in the Galactic halo and metal-poor d
Externí odkaz:
http://arxiv.org/abs/2412.06277
We study the rate-distortion problem for both scalar and vector memoryless heavy-tailed $\alpha$-stable sources ($0 < \alpha < 2$). Using a recently defined notion of ``strength" as a power measure, we derive the rate-distortion function for $\alpha$
Externí odkaz:
http://arxiv.org/abs/2411.08549
Autor:
Hirai, Yutaka, Beers, Timothy C., Lee, Young Sun, Wanajo, Shinya, Roederer, Ian U., Tanaka, Masaomi, Chiba, Masashi, Saitoh, Takayuki R., Placco, Vinicius M., Hansen, Terese T., Ezzeddine, Rana, Frebel, Anna, Holmbeck, Erika M., Sakari, Charli M.
We study the formation of stars with varying amounts of heavy elements synthesized by the rapid neutron-capture process ($r$-process) based on our detailed cosmological zoom-in simulation of a Milky Way-like galaxy with an $N$-body/smoothed particle
Externí odkaz:
http://arxiv.org/abs/2410.11943
Autor:
Bandyopadhyay, Avrajit, Ezzeddine, Rana, Prieto, Carlos Allende, Aria, Nima, Shah, Shivani P., Beers, Timothy C., Frebel, Anna, Hansen, Terese T., Holmbeck, Erika M., Placco, Vinicius M., Roederer, Ian U., Sakari, Charli M.
Publikováno v:
The Astrophysical Journal Supplement , 2024, Volume 274, Number 2, Page 39
Understanding the abundance pattern of metal-poor stars and the production of heavy elements through various nucleosynthesis processes offers crucial insights into the chemical evolution of the Milky Way, revealing primary sites and major sources of
Externí odkaz:
http://arxiv.org/abs/2408.03731
Autor:
Ezzeddine, Fatima
Machine learning (ML) models, demonstrably powerful, suffer from a lack of interpretability. The absence of transparency, often referred to as the black box nature of ML models, undermines trust and urges the need for efforts to enhance their explain
Externí odkaz:
http://arxiv.org/abs/2406.15789
Autor:
Roederer, Ian U., Beers, Timothy C., Hattori, Kohei, Placco, Vinicius M., Hansen, Terese T., Ezzeddine, Rana, Frebel, Anna, Holmbeck, Erika M., Sakari, Charli M.
We present stellar parameters and chemical abundances of 47 elements detected in the bright (V = 11.63) very metal-poor ([Fe/H] = -2.20 +- 0.12) star 2MASS J22132050-5137385. We observed this star using the Magellan Inamori Kyocera Echelle spectrogra
Externí odkaz:
http://arxiv.org/abs/2406.02691
Our understanding of early-type galaxies (ETGs) has grown in the past decade with the advance of full-spectrum fitting techniques used to infer the properties of the stellar populations that make-up the galaxy. We present ages, central velocity dispe
Externí odkaz:
http://arxiv.org/abs/2404.13459
Autor:
Ezzeddine, Fatima, Saad, Mirna, Ayoub, Omran, Andreoletti, Davide, Gjoreski, Martin, Sbeity, Ihab, Langheinrich, Marc, Giordano, Silvia
Anomaly detection (AD), also referred to as outlier detection, is a statistical process aimed at identifying observations within a dataset that significantly deviate from the expected pattern of the majority of the data. Such a process finds wide app
Externí odkaz:
http://arxiv.org/abs/2404.06144
Autor:
Xylakis-Dornbusch, T., Hansen, T. T., Beers, T. C., Christlieb, N., Ezzeddine, R., Frebel, A., Holmbeck, E., Placco, V. M., Roederer, I. U., Sakari, C. M., Sneden, C.
Context. In recent years, the R-Process Alliance (RPA) has conducted a successful search for stars enhanced in elements produced by the rapid neutron-capture (r-)process. In particular, the RPA has uncovered a number of stars strongly enriched in lig
Externí odkaz:
http://arxiv.org/abs/2404.03379
In recent years, there has been a notable increase in the deployment of machine learning (ML) models as services (MLaaS) across diverse production software applications. In parallel, explainable AI (XAI) continues to evolve, addressing the necessity
Externí odkaz:
http://arxiv.org/abs/2404.03348