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This study examines the characterization of binary star systems using Spectral Energy Distributions (SEDs), a technique increasingly essential with the rise of large-scale astronomical surveys. Binaries can emit flux at different regions of…

太阳与恒星天体物理 · 物理学 2025-03-20 Vikrant V. Jadhav

In recent years, deep learning techniques revolutionized the way remote sensing data are processed. Classification of hyperspectral data is no exception to the rule, but has intrinsic specificities which make application of deep learning…

机器学习 · 计算机科学 2019-04-25 Nicolas Audebert , Bertrand Saux , Sébastien Lefèvre

The conventional, widely used treatment of deep learning models as black boxes provides limited or no insights into the mechanisms that guide neural network decisions. Significant research effort has been dedicated to building interpretable…

计算机视觉与模式识别 · 计算机科学 2023-09-21 Apostolos Avranas , Marios Kountouris

The radio astronomy community is rapidly adopting deep learning techniques to deal with the huge data volumes expected from the next generation of radio observatories. Bayesian neural networks (BNNs) provide a principled way to model…

机器学习 · 计算机科学 2024-05-29 Devina Mohan , Anna M. M. Scaife

Neutron star X-ray binaries emit a compact, optically thick, relativistic radio jet during low-luminosity, usually hard states, as Galactic black-hole X-ray binaries do. When radio emission is bright, a hard power-law tail without evidence…

高能天体物理现象 · 物理学 2016-06-08 P. Reig , N. Kylafis

From a uniform analysis of a large (8.5 Ms) Rossi X-ray Timing Explorer data set of Low Mass X-ray Binaries, we present a complete identification of all the variability components in the power spectra of black holes in their canonical…

天体物理学 · 物理学 2009-11-13 M. Klein-Wolt , M. van der Klis

Nearby galaxy surveys have long classified X-ray binaries (XRBs) by the mass category of their donor stars (high-mass and low-mass). The NuSTAR observatory, which provides imaging data at E $>10$ keV, has enabled the classification of…

In this paper, we propose a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by learning a nonlinear embedding of a high-dimensional activation vector of a deep network layer into a…

计算机视觉与模式识别 · 计算机科学 2020-12-14 Zhongang Qi , Saeed Khorram , Fuxin Li

Emission-line regions are key to understanding the properties of galaxies, as they trace the exchange of matter and energy between stars and the interstellar medium (ISM). In nearby galaxies, individual nebulae can be identified as HII…

What are the most important conditions and processes governing the growth of stellar-origin compact objects? The identification of compact object type as either black hole (BH) or neutron star (NS) is fundamental to understanding their…

This chapter discusses the implications of X-ray binaries on our knowledge of Type Ibc and Type II supernovae. X-ray binaries contain accreting neutron stars and stellar--mass black holes which are the end points of massive star evolution.…

高能天体物理现象 · 物理学 2018-04-25 Jorge Casares , Peter G. Jonker , Garik Israelian

X-ray binaries are binary star systems in which a compact object (a neutron star or a black hole) and a relatively normal star orbit a common centre of mass. Since the discovery of X-ray binaries with the first X-ray telescopes in the…

天体物理学 · 物理学 2008-02-07 David Russell

Deep learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly non-linear relations and solve interesting problems in a data-driven manner. Several works have attempted to…

地球与行星天体物理 · 物理学 2021-07-26 Kai Hou Yip , Quentin Changeat , Nikolaos Nikolaou , Mario Morvan , Billy Edwards , Ingo P. Waldmann , Giovanna Tinetti

We present techniques for successfully performing numerical relativity simulations of binary black holes with fourth-order accuracy. Our simulations are based on a new coding framework which currently supports higher order finite…

广义相对论与量子宇宙学 · 物理学 2009-11-11 Y. Zlochower , J. G. Baker , M. Campanelli , C. O. Lousto

Deep neural networks can be trained in reciprocal space, by acting on the eigenvalues and eigenvectors of suitable transfer operators in direct space. Adjusting the eigenvalues, while freezing the eigenvectors, yields a substantial…

Black Hole Low Mass X-ray Binaries (BH-LMXBs) are excellent observational laboratories for studying many open questions in accretion physics. However, determining the physical properties of BH-LMXBs necessitates knowing their distances.…

高能天体物理现象 · 物理学 2024-04-17 Youssef Abdulghani , Anne M Lohfink , Jaiverdhan Chauhan

The representations of neural networks are often compared to those of biological systems by performing regression between the neural network responses and those measured from biological systems. Many different state-of-the-art deep neural…

神经元与认知 · 定量生物学 2023-12-13 Abdulkadir Canatar , Jenelle Feather , Albert Wakhloo , SueYeon Chung

We review the properties and behavior X-ray binaries that contain an accreting black hole. The larger majority of such systems are X-ray transients, and many of them were observed in daily pointings with RXTE throughout the course of their…

天体物理学 · 物理学 2008-11-26 Ronald A. Remillard , Jeffrey E. McClintock

We find a very strong correlation between the intrinsic spectral slope in X-rays and the amount of Compton reflection from a cold medium in Seyfert AGNs and in hard state of X-ray binaries with either black holes or weakly-magnetized…

天体物理学 · 物理学 2009-10-31 A. A. Zdziarski , P. Lubiski , D. A. Smith

The X-ray spectra of Low Mass X-ray Binaries (LMXB) can change on short time-scales, making it difficult to follow their spectral characteristics in detail through model fitting. Colour-colour (C-C) diagrams are therefore often used as…