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Related papers: Reverberation Mapping and Broad-Line Region Models

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Machine Learning algorithms have had a profound impact on the field of computer science over the past few decades. These algorithms performance is greatly influenced by the representations that are derived from the data in the learning…

Line broadening and variability are observational hallmarks of active galactic nuclei which allow us to measure supermassive black hole masses as well as constrain the geometry and kinematics of the emitting gas, with the most precise…

Astrophysics of Galaxies · Physics 2025-07-14 Kirk Long , Jason Dexter

The linear inverse problem is fundamental to the development of various scientific areas. Innumerable attempts have been carried out to solve different variants of the linear inverse problem in different applications. Nowadays, the rapid…

Signal Processing · Electrical Eng. & Systems 2020-10-30 Yanna Bai , Wei Chen , Jie Chen , Weisi Guo

In this paper, we mainly investigate distortion and covering theorems on some classes of pluriharmonic mappings.

Complex Variables · Mathematics 2014-10-07 Sh. Chen , S. Ponnusamy

Deep learning has received considerable empirical successes in recent years. However, while many ad hoc tricks have been discovered by practitioners, until recently, there has been a lack of theoretical understanding for tricks invented in…

Machine Learning · Computer Science 2020-12-29 Cong Fang , Hanze Dong , Tong Zhang

Problems solved? Pulsar research must be considered - 35 years after the detection of pulsars - a mature science, where the basic questions have been raised and discussed. One would hope that many if not all generic and important problems…

Astrophysics · Physics 2007-05-23 W. Sieber

Large matrices arise in many machine learning and data analysis applications, including as representations of datasets, graphs, model weights, and first and second-order derivatives. Randomized Numerical Linear Algebra (RandNLA) is an area…

Machine Learning · Computer Science 2024-06-21 Michał Dereziński , Michael W. Mahoney

By using standard broad-band VRI photometry we were able to discriminate the variations of the broad hydrogen alpha line from the continuum variations for the active galaxy Mkn 279. Cross-correlating both light curves enabled us to…

Astrophysics of Galaxies · Physics 2014-03-20 R. Bachev , A. Strigachev , E. Semkov , S. Boeva , S. Peneva , S. Ibryamov , K. Stoyanov , B. Spassov , S. Tsvetkova , B. Mihov , G. Latev , D. Dimitrov

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…

Machine Learning · Computer Science 2019-04-25 Nicolas Audebert , Bertrand Saux , Sébastien Lefèvre

Results from a few decades of reverberation mapping (RM) studies have revealed a correlation between the radius of the broad-line emitting region (BLR) and the continuum luminosity of active galactic nuclei. This "radius-luminosity"…

We present dynamical modeling of the broad line region (BLR) for a sample of five Seyfert 1 galaxies using reverberation mapping data taken by the Lick AGN Monitoring Project in 2008. By modeling the AGN continuum light curve and H$\beta$…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-18 Anna Pancoast , Brendon J. Brewer , Tommaso Treu , Daeseong Park , Aaron J. Barth , Misty C. Bentz , Jong-Hak Woo

The field of computational modeling of the brain is advancing so rapidly that now it is possible to model large scale networks representing different brain regions with a high level of biological detail in terms of numbers and synapses. For…

Thanks to the recent advances in processing speed and data acquisition and storage, machine learning (ML) is penetrating every facet of our lives, and transforming research in many areas in a fundamental manner. Wireless communications is…

Information Theory · Computer Science 2019-04-30 Deniz Gunduz , Paul de Kerret , Nicholas D. Sidiropoulos , David Gesbert , Chandra Murthy , Mihaela van der Schaar

Continuum reverberation mapping probes the size scale of the optical continuum-emitting region in active galactic nuclei (AGN). The source of this emission has long been thought to originate from the accretion disk, but recent studies…

Astrophysics of Galaxies · Physics 2025-11-11 Jake A. Miller , Edward M. Cackett , Misty C. Bentz , Michael R. Goad , Kirk T. Korista , Ian M. McHardy

Deep learning research aims at discovering learning algorithms that discover multiple levels of distributed representations, with higher levels representing more abstract concepts. Although the study of deep learning has already led to…

Machine Learning · Computer Science 2013-06-10 Yoshua Bengio

After a review of linear imperfections and their causes, we discuss how to model them, the diagnostic equipment needed to monitor them, and the correction algorithms to fix the problem they cause. We first address linear systems - beam…

Accelerator Physics · Physics 2020-06-22 V. Ziemann

Graph representation learning (GRL) has emerged as a pivotal field that has contributed significantly to breakthroughs in various fields, including biomedicine. The objective of this survey is to review the latest advancements in GRL…

Machine Learning · Computer Science 2024-01-25 Fang Li , Yi Nian , Zenan Sun , Cui Tao

This tutorial paper describes the problem of image reconstruction from interferometric data with a particular focus on the specific problems encountered at optical (visible/IR) wavelengths. The challenging issues in image reconstruction…

Instrumentation and Methods for Astrophysics · Physics 2011-04-20 Éric Thiébaut , Jean-François Giovannelli

Recent estimates of the scale of structures at the heart of quasars suggest that the region responsible for the broad line emission are smaller than previously thought. With this revision of scale, the broad line region is amenable to the…

Astrophysics · Physics 2009-11-10 Geraint F. Lewis , Rodrigo A. Ibata

This paper provides a primer on Large Language Models (LLMs) and identifies their strengths, limitations, applications and research directions. It is intended to be useful to those in academia and industry who are interested in gaining an…

Computation and Language · Computer Science 2024-12-09 Sandra Johnson , David Hyland-Wood