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Weak lensing causes spatially coherent fluctuations in flux of type Ia supernovae (SNe Ia). This lensing magnification allows for weak lensing measurement independent of cosmic shear. It is free of shape measurement errors associated with…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-11 Pengjie Zhang

Despite the success of deep learning for static image understanding, it remains unclear what are the most effective network architectures for the spatial-temporal modeling in videos. In this paper, in contrast to the existing CNN+RNN or…

Computer Vision and Pattern Recognition · Computer Science 2018-12-12 Dongliang He , Zhichao Zhou , Chuang Gan , Fu Li , Xiao Liu , Yandong Li , Limin Wang , Shilei Wen

Graph neural networks have emerged as a powerful tool for learning spatiotemporal interactions. However, conventional approaches often rely on predefined graphs, which may obscure the precise relationships being modeled. Additionally,…

Machine Learning · Computer Science 2025-02-21 Jeehong Kim , Minchan Kim , Jaeseong Ju , Youngseok Hwang , Wonhee Lee , Hyunwoo Park

To search for optical counterparts to gravitational waves, it is crucial to develop an efficient follow-up method that allows for both a quick telescopic scan of the event localization region and search through the resulting image data for…

Instrumentation and Methods for Astrophysics · Physics 2021-08-25 Katarzyna Wardęga , Adam Zadrożny , Martin Beroiz , Richard Camuccio , Mario C. Díaz

Change detection of high-resolution remote sensing images is an important task in earth observation and was extensively investigated. Recently, deep learning has shown to be very successful in plenty of remote sensing tasks. The current…

Image and Video Processing · Electrical Eng. & Systems 2026-03-25 Shuting Sun , Lin Mu , Lizhe Wang , Peng Liu

Since the wide employment of deep learning frameworks in video salient object detection, the accuracy of the recent approaches has made stunning progress. These approaches mainly adopt the sequential modules, based on optical flow or…

Computer Vision and Pattern Recognition · Computer Science 2021-03-18 Yi Tang , Yuanman Li , Wenbin Zou

Deep neural networks are efficient learning machines which leverage upon a large amount of manually labeled data for learning discriminative features. However, acquiring substantial amount of supervised data, especially for videos can be a…

Computer Vision and Pattern Recognition · Computer Science 2018-08-16 Sujoy Paul , Sourya Roy , Amit K. Roy-Chowdhury

Searches and analyses of strong gravitational lenses are challenging due to the rarity and image complexity of these astronomical objects. Next-generation surveys (both ground- and space-based) will provide more opportunities to derive…

Astrophysics of Galaxies · Physics 2019-11-18 Clecio Bom , Jason Poh , Brian Nord , Manuel Blanco-Valentin , Luciana Dias

The light from distant supernovae (SNe) can be magnified through gravitational lensing when a foreground galaxy is located along the line of sight. This line-up allows for detailed studies of SNe at high redshift that otherwise would not be…

High Energy Astrophysical Phenomena · Physics 2017-07-26 T. Petrushevska , R. Amanullah , M. Bulla , M. Kromer , R. Ferretti , A. Goobar , S. Papadogiannakis

Strong gravitational lenses are a singular probe of the universe's small-scale structure $\unicode{x2013}$ they are sensitive to the gravitational effects of low-mass $(<10^{10} M_\odot)$ halos even without a luminous counterpart. Recent…

Cosmology and Nongalactic Astrophysics · Physics 2024-04-24 Sebastian Wagner-Carena , Jaehoon Lee , Jeffrey Pennington , Jelle Aalbers , Simon Birrer , Risa H. Wechsler

Recent rapid progress in time domain surveys makes it possible to detect various types of explosive transients in the Universe in large numbers, some of which will be gravitationally lensed into multiple images. Although a large number of…

Cosmology and Nongalactic Astrophysics · Physics 2020-01-08 Masamune Oguri

We report non-zero weak lensing convergence correlation signal of Type-Ia supernovae from 5-year Supernovae Legacy Survey data. For our analysis we utilize 296 supernovae magnification data from 5-year SNLS in the weak lensing limit. The…

Cosmology and Nongalactic Astrophysics · Physics 2019-11-19 Ayan Mitra , Arnab Paul , Barun Pal , Supratik Pal

The magnification resulting from strong gravitational lensing is a powerful tool to add new constraints to the cosmic evolution of supernova progenitors by enabling the study of distant supernovae that would otherwise not be observable.…

High Energy Astrophysical Phenomena · Physics 2026-02-04 Ana Sainz de Murieta , Mark R. Magee , Tian Li , Thomas E. Collett , Joel Johansson

Type Ia supernovae (SNe Ia) constitute an historical probe to derive cosmological parameters through the fit of the Hubble-Lema\^itre diagram, i.e. SN Ia distance modulus versus their redshift. In the era of precision cosmology, realistic…

Type Ia supernovae (SNe Ia) are standarizable candles whose observed light curves can be used to infer their distances, which can in turn be used in cosmological analyses. As the quantity of observed SNe Ia grows with current and upcoming…

Instrumentation and Methods for Astrophysics · Physics 2024-10-29 Ana Sofía M. Uzsoy , Stephen Thorp , Matthew Grayling , Kaisey S. Mandel

We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys' Data Release 9. Targeting the identification of new strong…

Instrumentation and Methods for Astrophysics · Physics 2022-06-23 George Stein , Jacqueline Blaum , Peter Harrington , Tomislav Medan , Zarija Lukic

The rapid growth of earth observation systems calls for a scalable approach to interpolate remote-sensing observations. These methods in principle, should acquire more information about the observed field as data grows. Gaussian processes…

Machine Learning · Computer Science 2024-12-17 Weibin Chen , Azhir Mahmood , Michel Tsamados , So Takao

The High-Z Supernova Search is an international collaboration to discover and monitor type Ia supernovae (SN Ia) at $z > 0.2$ with the aim of measuring cosmic deceleration and global curvature. Our collaboration has pursued a basic…

An emerging generative artificial intelligence (AI) based on neural networks starts to grow in popularity with a revolutionizing capability of creating new and original content. As giant generative models with millions to billions of…

Emerging Technologies · Computer Science 2023-12-05 Shuang Zheng , Jiawei Zhang , Weifeng Zhang

Using data from the Pantheon SN Ia compilation and the Sloan Digital Sky Survey (SDSS), we propose an estimator for weak lensing convergence incorporating positional and photometric data of foreground galaxies. The correlation between this…

Cosmology and Nongalactic Astrophysics · Physics 2022-07-06 Paul Shah , Pablo Lemos , Ofer Lahav
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