相关论文: Neuro-Parametric Spectral Classification of Black …

A deep neural network (DNN) model consisting of two hidden layers was proposed for predicting the immediate environments of specific atoms based on X-ray absorption near-edge spectra (XANES). The output layer of the DNN can be adjusted to…

Spectroscopic surveys require fast and efficient analysis methods to maximize their scientific impact. Here we apply a deep neural network architecture to analyze both SDSS-III APOGEE DR13 and synthetic stellar spectra. When our…

Nonlinear methods such as Deep Neural Networks (DNNs) are the gold standard for various challenging machine learning problems, e.g., image classification, natural language processing or human action recognition. Although these methods…

Wide field small aperture telescopes are widely used for optical transient observations. Detection and classification of astronomical targets in observed images are the most important and basic step. In this paper, we propose an…

We systematically analyzed about a terabyte of data from Galactic binary systems to characterize how these spectra change as a function of mass accretion rate. With this volume of data we are able to identify the differences in behaviour of…

The accumulation of certain types of dark matter particles in neutron star cores due to accretion over long timescales can lead to the formation of a mini black hole. In this scenario, the neutron star is destabilized and implodes to form a…

X-ray binaries, as bright local sources with short variability timescales for a wide range of accretion processes, represent ideal targets for high-resolution X-ray spectroscopy. In this chapter, we present a high-resolution X-ray spectral…

We develop a method for identifying a compact object in binary systems with astrometric measurements and apply it to some binaries. Compact objects in some high-mass X-ray binaries and gamma-ray binaries are unknown, which is responsible…

Deep neural networks are powerful machine learning approaches that have exhibited excellent results on many classification tasks. However, they are considered as black boxes and some of their properties remain to be formalized. In the…

We present a theoretical framework for the formation of X-ray linear polarization in black hole (BH) source. The X-ray linear polarization originates from up-scatterings of initially soft photons within a hot, optically thick Compton cloud…

We introduce QuasarNET, a deep convolutional neural network that performs classification and redshift estimation of astrophysical spectra with human-expert accuracy. We pose these two tasks as a \emph{feature detection} problem: presence or…

We present a multi-domain spectral method to compute initial data of binary systems in General Relativity. By utilizing adapted conformal coordinates, the vacuum region exterior to the gravitational sources is divided up into two subdomains…

Single-shot imaging with femtosecond X-ray lasers is a powerful measurement technique that can achieve both high spatial and temporal resolution. However, its accuracy has been severely limited by the difficulty of applying conventional…

This chapter for the new CUP book "Compact Stellar Sources" reviews the state of work on multi-wavelength observations of high mass and low mass X-ray binaries. Both neutron star and black hole systems are considered for this work.

This dissertation is written as an annotated collection of selected articles. The dissertation focuses on the modelling of accretion disks in X-ray binaries with a black hole or neutron star. The main objective is to use advanced numerical…

Massive black hole binaries (MBHBs) are binary systems formed by black holes with mass exceeding millions of solar masses, expected to form and evolve in the nuclei of galaxies. The extreme compact nature of such objects determines a loud…

Recent X-ray timing and spectral observations of black hole binaries in outburst have redefined methods for investigating the properties of Galactic black holes and the physics of accretion flows. High-frequency X-ray QPOs in 5 systems…

The prediction of spin magnitudes in binary black hole and neutron star mergers is crucial for understanding the astrophysical processes and gravitational wave (GW) signals emitted during these cataclysmic events. In this paper, we present…

We introduce deep learning models to estimate the masses of the binary components of black hole mergers, $(m_1,m_2)$, and three astrophysical properties of the post-merger compact remnant, namely, the final spin, $a_f$, and the frequency…

Model spectra of neutron star atmospheres are nowadays widely used to fit the observed thermal X-ray spectra of neutron stars. This fitting is the key element in the method of the neutronstar radius determination. Here, we present the basic…