Related papers: Machine learning application to detect light echoe…
We compute fully relativistic disc response functions in the case of the "lamp-post" geometry using the full observed reflection spectrum for various X-ray source heights, disc inclination, and spin values of the central black hole. Since…
Most active supermassive black holes (SMBH) in present-day galaxies are underfed and consist of low-luminosity active galactic nuclei (LLAGN). They have multiwavelength broadband spectral energy distributions (SED) dominated by non-thermal…
We propose a new method to determine the dark matter density profile in the vicinity of distant supermassive black holes (SMBH) using reverberation mapping (RM) measurements of active galactic nuclei (AGN). The mapping of multiple emission…
We present the results of a detailed study of the X-ray power spectra density (PSD) functions of twelve X-ray bright AGN, using almost all the archival XMM-Newton data. The total net exposure of the EPIC-pn light curves is larger than 350…
Cosmic shear is a primary cosmological probe for several present and upcoming surveys investigating dark matter and dark energy, such as Euclid or WFIRST. The probe requires an extremely accurate measurement of the shapes of millions of…
We develop neural network models to predict the black hole mass using 22 reverberating AGN samples in the XMM-Newton archive. The model features include the fractional excess variance ($F_{\rm var}$) in 2-10 keV band, Fe-K lag amplitude,…
We investigate the physical nature of active galactic nuclei (AGNs) using machine learning (ML) tools. We show that the redshift, $z$, bolometric luminosity, $L_{\rm Bol}$, central mass of the supermassive black hole (SMBH), $M_{\rm BH}$,…
Symbolic regression (SR) is a regression analysis based on genetic algorithms to search for mathematical expressions that best fit a given data set, by allowing the expressions themselves to mutate. We use the SR to analyze the parameter…
We present a general method to analyze reverberation mapping data that provides both estimates for the black hole mass and for the geometry and dynamics of the broad line region (BLR) in active galactic nuclei (AGN). Our method directly…
Characteristic signatures that X-ray reverberation from an extended corona can manifest in the observed PSD of AGN are investigated. The presence of two X-ray blobs illuminating an accretion disc can cause the interference between two…
Using different kinds of velocity tracers derived from the broad H$\beta$ profile (in the mean or rms spectrum) and the corresponding virial factors $f$, the central supermassive black hole (SMBH) masses ($M_{\rm BH}$) are calculated for a…
We explore the application of computer vision and machine learning (ML) techniques to predict material properties (e.g. compressive strength) based on SEM images. We show that it's possible to train ML models to predict materials…
X-ray reverberation is a powerful technique which maps out the structure of the inner regions of accretion disks around black holes using the echoes of the coronal emission reflected by the disk. While the theory of X-ray reverberation has…
Supermassive black holes (SMBHs) are ubiquitously found at the centers of most galaxies. Measuring SMBH mass is important for understanding the origin and evolution of SMBHs. However, traditional methods require spectral data which is…
Accreting black holes show characteristic reflection features in their X-ray spectrum, including an iron K$\alpha$ line, resulting from hard X-ray continuum photons illuminating the accretion disk. The reverberation lag resulting from the…
The central engines of Active Galactic Nuclei (AGNs) are powered by accreting supermassive black holes, and while AGNs are known to play an important role in galaxy evolution, the key physical processes occur on scales that are too small to…
Speech communication systems are prone to performance degradation in reverberant and noisy acoustic environments. Dereverberation and noise reduction algorithms typically require several model parameters, e.g. the speech, reverberation and…
The study of machine learning (ML) techniques for the autonomous classification of astrophysical sources is of great interest, and we explore its applications in the context of a multifrequency data-frame. We test the use of supervised ML…
We developed and trained a pipeline of three machine learning (ML) models than can predict which sources are more likely to be an AGN and to be detected in specific radio surveys. Also, it can estimate redshift values for predicted…
Reverberation mapping is now a well-established technique for investigating spatially-unresolved structures in the nuclei of distant galaxies with actively-accreting supermassive black holes. Structural parameters for the broad…