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Related papers: Deep modeling of quasar variability

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We present the results of a systematic search for quasars in the Catalina Real-time Transient Survey exhibiting both strong photometric and spectroscopic variability over a decadal baseline. We identify 73 sources with specific patterns of…

Optical spectropolarimetry carried out by Kishimoto et al. (2004) has shown that several luminous type 1 quasars show a strong decrease of the polarized continuum flux in the rest-frame near-UV wavelengths of $\lambda<4000$\AA. In the…

Astrophysics of Galaxies · Physics 2016-06-15 Mitsuru Kokubo

Turbulence, namely, irregular fluctuations in space and time characterize fluid flows in general and atmospheric flows in particular.The irregular,i.e., nonlinear space-time fluctuations on all scales contribute to the unpredictable nature…

General Physics · Physics 2007-05-23 J. S. Pethkar , A. M. Selvam

Gaia Data Release 3 (DR3) published for the first time epoch photometry, BP/RP (XP) low-resolution mean spectra, and supervised classification results for millions of variable sources. This extensive dataset offers a unique opportunity to…

We develop a new computational tool and framework for characterizing the scattering of photons by energy-nonconserving Hamiltonians into unidirectional (chiral) waveguides, for example, with coherent pulsed excitation. The temporal…

Quantum Physics · Physics 2018-05-30 Kevin A. Fischer , Rahul Trivedi , Vinay Ramasesh , Irfan Siddiqi , Jelena Vučković

We suggest and implement an approach for the bottom-up description of systems undergoing large-scale structural changes and chemical transformations from dynamic atomically resolved imaging data, where only partial or uncertain data on…

Materials Science · Physics 2021-04-23 Sergei V. Kalinin , Ondrej Dyck , Stephen Jesse , Maxim Ziatdinov

Recurrent neural networks are widely used on time series data, yet such models often ignore the underlying physical structures in such sequences. A new class of physics-based methods related to Koopman theory has been introduced, offering…

Computational Physics · Physics 2020-07-01 Omri Azencot , N. Benjamin Erichson , Vanessa Lin , Michael W. Mahoney

Abstract abridged. Eclipsing binary systems provide the opportunity to measure the fundamental parameters of their component stars in a stellar-model-independent way. This makes them ideal candidates for testing and calibrating theories of…

Instrumentation and Methods for Astrophysics · Physics 2024-02-12 Luc W. IJspeert , Andrew Tkachenko , Cole Johnston , Andrej Prša , Mark A. Wells , Conny Aerts

The variational autoencoder (VAE) is a popular deep latent variable model used to analyse high-dimensional datasets by learning a low-dimensional latent representation of the data. It simultaneously learns a generative model and an…

Machine Learning · Computer Science 2023-11-21 Mine Öğretir , Siddharth Ramchandran , Dimitrios Papatheodorou , Harri Lähdesmäki

Electron, optical, and scanning probe microscopy methods are generating ever increasing volume of image data containing information on atomic and mesoscale structures and functionalities. This necessitates the development of the machine…

Machine Learning · Computer Science 2023-04-03 Mani Valleti , Yongtao Liu , Sergei Kalinin

Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for learning features relevant to discriminative tasks.…

Machine Learning · Statistics 2011-10-27 Jasper Snoek , Ryan Prescott Adams , Hugo Larochelle

Optimal computations under uncertainty require an adequate probabilistic representation about beliefs. Deep generative models, and specifically Variational Autoencoders (VAEs), have the potential to meet this demand by building latent…

Time-domain astrophysics relies on heterogeneous and multi-modal data. Specialized models are often constructed to extract information from a single modality, but this approach ignores the wealth of cross-modality information that may be…

Instrumentation and Methods for Astrophysics · Physics 2025-07-23 Yunyi Shen , Alexander T. Gagliano

Emission from Active Galactic Nuclei is known to vary strongly over time over a wide energy band, but the origin of the variability and especially of the inter-band correlations is still not well established. Here we present the results of…

Astrophysics · Physics 2009-11-13 P. Arévalo , P. Uttley , S. Kaspi , E. Breedt , P. Lira , I. M. McHardy

Given the anisotropic emission from quasar accretion discs, their viewing angle affects estimates of the quasar luminosity, black-hole mass and Eddington ratio. Discs appear overluminous when viewed pole-on and underluminous when viewed at…

Astrophysics of Galaxies · Physics 2023-06-28 Ji-Jia Tang , Christian Wolf , John Tonry , Samuel Lai , Suk Yee Yong , Zachary Steyn

We examine the long-term evolution of the intra-hour variable quasar, J1819+3845, whose variations have been attributed to interstellar scintillation by extremely local turbulent plasma, located only 1-3pc from Earth. The variations in this…

Astrophysics of Galaxies · Physics 2015-06-22 A. G. de Bruyn , J. -P. Macquart

We present the results of an automated variability analysis of the Kepler public data measured in the first quarter (Q1) of the mission. In total, about 150 000 light curves have been analysed to detect stellar variability, and to identify…

Solar and Stellar Astrophysics · Physics 2015-05-27 J. Debosscher , J. Blomme , C. Aerts , J. De Ridder

Broad absorption lines (BALs) in quasar spectra are prominent signatures of high-velocity outflows, which might be present in all quasars and could be a major contributor to feedback to galaxy evolution. Studying the variability in these…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-12 Daniel M. Capellupo , Fred Hamann , Joseph C. Shields , Jules P. Halpern , Tom A. Barlow

A tight non-linear relation between the X-ray and the optical-ultraviolet (UV) emission has been observed in Active Galactic Nuclei (AGN) over a wide range of redshift and several orders of magnitude in luminosity, suggesting the existence…

Astrophysics of Galaxies · Physics 2019-11-06 Francesco Salvestrini , Guido Risaliti , Susanna Bisogni , Elisabeta Lusso , Cristian Vignali

This work investigates a practical and novel method for automated unsupervised fault detection in vehicles using a fully convolutional autoencoder. The results demonstrate the algorithm we developed can detect anomalies which correspond to…

Machine Learning · Computer Science 2024-09-10 Anthony Geglio , Eisa Hedayati , Mark Tascillo , Dyche Anderson , Jonathan Barker , Timothy C. Havens