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Explainable AI (XAI) is an active research area to interpret a neural network's decision by ensuring transparency and trust in the task-specified learned models. Recently, perturbation-based model analysis has shown better interpretation,…

Computer Vision and Pattern Recognition · Computer Science 2021-02-17 Mahesh Sudhakar , Sam Sattarzadeh , Konstantinos N. Plataniotis , Jongseong Jang , Yeonjeong Jeong , Hyunwoo Kim

Relatively uniform light curves and spectral evolution of Type Ia supernovae (SNe Ia) have led to the use of SNe Ia as a ``standard candle'' to determine cosmological parameters. Whether a statistically significant value of the cosmological…

We present an eigenfunction method to analyze 161 visual light curves (LCs) of Type Ia supernovae (SNe Ia) obtained by the Carnegie Supernova Project to characterize their diversity and host-galaxy correlations. The eigenfunctions are based…

A convolution neural network (CNN) based classification method for broadband DOA estimation is proposed, where the phase component of the short-time Fourier transform coefficients of the received microphone signals are directly fed into the…

Sound · Computer Science 2019-12-18 Soumitro Chakrabarty , Emanuël. A. P. Habets

Early polarization observations on Type Ia supernovae (SNe Ia) may reveal the geometry of supernova ejecta, and then put constraints on their explosion mechanism and their progenitor model. We performed a literature search of SNe Ia with…

High Energy Astrophysical Phenomena · Physics 2017-05-31 Xiangcun Meng , Jujia Zhang , Zhanwen Han

The remarkable uniformity of Type Ia supernovae (SNe Ia) has allowed astronomers to use them as distance indicators to measure the properties and expansion history of the Universe. However, SNe Ia exhibit intrinsic variation in both their…

Astrophysics · Physics 2009-09-29 William Michael Wood-Vasey

Although type Ia supernovae (SNe Ia) are very useful in many astrophysical fields, their exact progenitor nature is still unclear. A basic method to distinguish the different progenitor models is to search the signal from the single…

High Energy Astrophysical Phenomena · Physics 2018-03-21 Xiangcun Meng , Zhanwen Han

Recent studies indicate that Type Ia supernovae (SNe Ia) consist of two groups - a "prompt" component whose rates are proportional to the host galaxy star formation rate, whose members have broader lightcurves and are intrinsically more…

Astrophysics · Physics 2014-10-13 D. Andrew Howell , Mark Sullivan , Alex Conley , Ray Carlberg

The Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp satellite series provides important measurements for Numerical Weather Prediction (NWP). Retrieving accurate atmospheric parameters from the raw data provided by…

Atmospheric and Oceanic Physics · Physics 2020-12-21 David Malmgren-Hansen , Allan Aasbjerg Nielsen , Valero Laparra , Gustau Camps- Valls

Photometric classification of Type Ia supernovae is essential for modern time-domain surveys, where spectroscopic confirmation is not always feasible for the full transient sample. In this work, we investigate a compact and physically…

Instrumentation and Methods for Astrophysics · Physics 2026-03-17 Anurag Garg

We reconstruct the expansion history of the Universe using type Ia supernovae (SN Ia) in a manner independent of any cosmological model assumptions. To do so, we implement a non-parametric iterative smoothing method on the Joint Light-curve…

Cosmology and Nongalactic Astrophysics · Physics 2020-08-12 Hanwool Koo , Arman Shafieloo , Ryan E. Keeley , Benjamin L'Huillier

Type Ia supernova (SN Ia) cosmology relies on the estimation of lightcurve parameters to derive precision distances that leads to the estimation of cosmological parameters. The empirical SALT2 lightcurve modeling that relies on only two…

Type Ia supernovae (SNe Ia) play key roles in revealing the accelerating expansion of the universe, but our knowledge about their progenitors is still very limited. Here we report the discovery of a rigid dichotomy in circumstellar (CS)…

High Energy Astrophysical Phenomena · Physics 2019-09-25 Xiaofeng Wang , Jia Chen , Lifan Wang , Maokai Hu , Gaobo Xi , Yi Yang , Xulin Zhao , Wenxiong Li

Supernovae are essential to understanding the chemical evolution of the Universe. Type Ia supernovae also provide the most powerful observational tool currently available for studying the expansion history of the Universe and the nature of…

Convolutional neural network (CNN) is a class of artificial neural networks widely used in computer vision tasks. Most CNNs achieve excellent performance by stacking certain types of basic units. In addition to increasing the depth and…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Junyi An , Fengshan Liu , Jian Zhao , Furao Shen

The fields of neural computation and artificial neural networks have developed much in the last decades. Most of the works in these fields focus on implementing and/or learning discrete functions or behavior. However, technical, physical,…

Neural and Evolutionary Computing · Computer Science 2016-06-15 Frieder Stolzenburg , Florian Ruh

Back-propagation algorithm is one of the most widely used and popular techniques to optimize the feed forward neural network training. Nature inspired meta-heuristic algorithms also provide derivative-free solution to optimize complex…

Neural and Evolutionary Computing · Computer Science 2012-09-13 Sudarshan Nandy , Partha Pratim Sarkar , Achintya Das

In response to a recently reported observation of evidence for two classes of Type Ia Supernovae (SNe Ia) distinguished by their brightness in the rest-frame near ultraviolet (NUV), we search for the phenomenon in publicly available…

Cosmology and Nongalactic Astrophysics · Physics 2017-01-16 David Cinabro , Daniel Scolnic , Richard Kessler , Ashley Li , Jake Miller

Type Ia supernovae are bright stellar explosions distinguished by standardizable light curves that allow for their use as distance indicators for cosmological studies. Despite their highly successful use in this capacity, the progenitors of…

Solar and Stellar Astrophysics · Physics 2015-06-05 Alan C. Calder , Brendan K. Krueger , Aaron P. Jackson , Dean M. Townsley , Edward F. Brown , Francis X. Timmes

Cosmologists are facing the problem of the analysis of a huge quantity of data when observing the sky. The methods used in cosmology are, for the most of them, relying on astrophysical models, and thus, for the classification, they usually…

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