Related papers: Analyzing X-ray variability by State Space Models
This paper introduces new techniques for using convex optimization to fit input-output data to a class of stable nonlinear dynamical models. We present an algorithm that guarantees consistent estimates of models in this class when a small…
Active galactic nuclei (AGNs) exhibit stochastic optical variability, commonly characterized by a damped random walk. The damping timescale is of particular interest because it is related to fundamental properties of the central black hole,…
The four-year X-ray all-sky survey (eRASS) of the eROSITA telescope aboard the Spektrum-Roentgen-Gamma satellite will detect ~3 million active galactic nuclei (AGN) with a median redshift of z~1 and a typical luminosity of L_(0.5-2.0 keV) ~…
According to the standard paradigm, the strong and compact luminosity of active galactic nuclei (AGN) is due to multi-temperature black body emission originating from an accretion disk formed around a supermassive black hole. This central…
We carried out a systematic analysis of time lags between X-ray energy bands in a large sample (32 sources) of unabsorbed, radio quiet active galactic nuclei (AGN), observed by XMM-Newton. The analysis of X-ray lags (up to the…
The identification of black-box nonlinear state-space models requires a flexible representation of the state and output equation. Artificial neural networks have proven to provide such a representation. However, as in many identification…
A technique for timescale analysis of spectral lags performed directly in the time domain is developed. Simulation studies are made to compare the time domain technique with the Fourier frequency analysis for spectral time lags. The time…
The analysis of nonstationary time series is of great importance in many scientific fields such as physics and neuroscience. In recent years, Gaussian process regression has attracted substantial attention as a robust and powerful method…
A class of methods for measuring time delays between astronomical time series is introduced in the context of quasar reverberation mapping, which is based on measures of randomness or complexity of the data. Several distinct statistical…
The class of autoregressive (AR) processes is extensively used to model temporal dependence in observed time series. Such models are easily available and routinely fitted using freely available statistical software like R. A potential…
This article introduces the GNAR package, which fits, predicts, and simulates from a powerful new class of generalised network autoregressive processes. Such processes consist of a multivariate time series along with a real, or inferred,…
The fluctuating brightness of cosmic X-ray sources, particularly accreting black holes and neutron star systems, has enabled enormous progress in understanding the physics of turbulent accretion flows, the behaviour of matter on the…
Time series prediction with missing values is an important problem of time series analysis since complete data is usually hard to obtain in many real-world applications. To model the generation of time series, autoregressive (AR) model is a…
The evolution of physical systems are often modeled by simple Markovian processes. When settled into stationary states, the probability distributions of such systems are time independent, by definition. However, they do not necessarily fall…
Strong gravitational lensing of time variable sources such as quasars and supernovae creates observable time delays between the multiple images. Time delays can provide a powerful cosmographic probe through the "time delay distance"…
The ubiquity of multiscale interactions in complex systems is well-recognized, with development and heredity serving as a prime example of how processes at different temporal scales influence one another. This work introduces a novel…
X-rays are a powerful probe of the physical conditions in the nuclei of active galaxies. We review the X-ray properties of radio-quiet AGN, LINERs and ultraluminous IR galaxies based on observations carried out with the X-ray satellite…
Modeling nonstationary processes is of paramount importance to many scientific disciplines including environmental science, ecology, and finance, among others. Consequently, flexible methodology that provides accurate estimation across a…
This paper deals with the noise identification of a linear time-varying stochastic dynamic system described by the state-space model. In particular, the stress is laid on the design of the correlation measurement difference method for…
Pulsars are unique astrophysical laboratories because of their clock-like timing precision, providing new ways to test general relativity and detect gravitational waves. One impediment to high-precision pulsar timing experiments is timing…