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of 3 862
pro vyhledávání: '"Wong, Kenneth"'
Combining neural networks with galaxy light subtraction for discovering strong lenses in the HSC SSP
Galaxy-scale strong gravitational lenses are valuable objects for a variety of astrophysical and cosmological applications. Strong lensing galaxies are rare, so efficient search methods, such as convolutional neural networks, are often used on large
Externí odkaz:
http://arxiv.org/abs/2411.07492
Autor:
Wong, Kenneth C., Dux, Frédéric, Shajib, Anowar J., Suyu, Sherry H., Millon, Martin, Mozumdar, Pritom, Wells, Patrick R., Agnello, Adriano, Birrer, Simon, Buckley-Geer, Elizabeth J., Courbin, Frédéric, Fassnacht, Christopher D., Frieman, Joshua, Galan, Aymeric, Lin, Huan, Marshall, Philip J., Poh, Jason, Schuldt, Stefan, Sluse, Dominique, Treu, Tommaso
Publikováno v:
A&A 689, A168 (2024)
Time-delay cosmography is a powerful technique to constrain cosmological parameters, particularly the Hubble constant ($H_{0}$). The TDCOSMO collaboration is performing an ongoing analysis of lensed quasars to constrain cosmology using this method. I
Externí odkaz:
http://arxiv.org/abs/2406.02683
Autor:
More, Anupreeta, Canameras, Raoul, Jaelani, Anton T., Shu, Yiping, Ishida, Yuichiro, Wong, Kenneth C., Inoue, Kaiki Taro, Schuldt, Stefan, Sonnenfeld, Alessandro
Efficient algorithms are being developed to search for strong gravitational lens systems owing to increasing large imaging surveys. Neural networks have been successfully used to discover galaxy-scale lens systems in imaging surveys such as the Kilo
Externí odkaz:
http://arxiv.org/abs/2405.12975
Autor:
Zhou, Yi, Hsieh, Jih-Liang, Oguz, Ilker, Yildirim, Mustafa, Dinc, Niyazi Ulas, Gigli, Carlo, Wong, Kenneth K. Y., Moser, Christophe, Psaltis, Demetri
Electronic computers have evolved drastically over the past years with an ever-growing demand for improved performance. However, the transfer of information from memory and high energy consumption have emerged as issues that require solutions. Optica
Externí odkaz:
http://arxiv.org/abs/2403.02452
Autor:
Lin, Li, Liu, Yixiang, Wu, Jiewei, Cheng, Pujin, Cai, Zhiyuan, Wong, Kenneth K. Y., Tang, Xiaoying
Federated learning (FL) effectively mitigates the data silo challenge brought about by policies and privacy concerns, implicitly harnessing more data for deep model training. However, traditional centralized FL models grapple with diverse multi-cente
Externí odkaz:
http://arxiv.org/abs/2402.17502
Autor:
Jaelani, Anton T., More, Anupreeta, Wong, Kenneth C., Inoue, Kaiki T., Chao, Dani C. -Y., Premadi, Premana W., Cañameras, Raoul
We apply a novel model based on convolutional neural networks (CNNs) to identify gravitationally-lensed galaxies in multi-band imaging of the Hyper Suprime Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample
Externí odkaz:
http://arxiv.org/abs/2312.07333
Autor:
Di, Jiyun, Egami, Eiichi, Wong, Kenneth C., Lee, Chien-Hsiu, Ning, Yuanhang, Ota, Naomi, Tanaka, Masayuki
The discovery of the Eye of Horus (EoH), a rare double source-plane lens system ($z_{\rm lens}=$ 0.795; $z_{\rm src}=$ 1.302 and 1.988), has also led to the identification of two high-redshift ($z_{\rm phot}\sim$ 0.8) galaxy clusters in the same fiel
Externí odkaz:
http://arxiv.org/abs/2312.02140
Autor:
Holloway, Philip, Marshall, Philip J., Verma, Aprajita, More, Anupreeta, Cañameras, Raoul, Jaelani, Anton T., Ishida, Yuichiro, Wong, Kenneth C.
The arrival of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), Euclid-Wide and Roman wide area sensitive surveys will herald a new era in strong lens science in which the number of strong lenses known is expected to rise from
Externí odkaz:
http://arxiv.org/abs/2311.07455