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We investigate the use of a Hamiltonian Monte Carlo to map out the posterior density function for supermassive black hole binaries. While previous Markov Chain Monte Carlo (MCMC) methods, such as Metropolis-Hastings MCMC, have been…

General Relativity and Quantum Cosmology · Physics 2019-08-19 Edward K. Porter , Jérôme Carré

The space-borne gravitational-wave (GW) detectors will open a new mass and redshift regime, allowing us to observe massive black hole binaries (MBHBs) throughout the Universe. A subset of these systems is expected to produce electromagnetic…

General Relativity and Quantum Cosmology · Physics 2026-04-28 Xue-Ting Zhang , Jonathan Gair , Chris Messenger , Natalia Korsakova , Yi-Ming Hu , Hong-Yu Chen

Autoencoders have been extensively used in the development of recent anomaly detection techniques. The premise of their application is based on the notion that after training the autoencoder on normal training data, anomalous inputs will…

Machine Learning · Computer Science 2024-03-29 Amin Ghafourian , Huanyi Shui , Devesh Upadhyay , Rajesh Gupta , Dimitar Filev , Iman Soltani Bozchalooi

Black hole X-ray binaries (BHXBs) show rich phenomenology in the spectral and timing properties. We collected the spectral data of 20 BHXBs from the literature across different spectral states. The spectral properties are studied in the…

High Energy Astrophysical Phenomena · Physics 2022-10-26 Arghajit Jana

Self-consistent vertical structure models together with non-LTE radiative transfer should produce spectra from accretion disks around black holes which differ from multitemperature blackbodies at levels which may be observed. High…

Astrophysics · Physics 2009-11-11 Shane W. Davis , Ivan Hubeny

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…

Astrophysics · Physics 2007-05-23 R. A. Remillard

Autoencoders gained popularity in the deep learning revolution given their ability to compress data and provide dimensionality reduction. Although prominent deep learning methods have been used to enhance autoencoders, the need to provide…

Machine Learning · Computer Science 2022-04-29 Rohitash Chandra , Mahir Jain , Manavendra Maharana , Pavel N. Krivitsky

Gravitational wave (GW) detection is now commonplace and as the sensitivity of the global network of GW detectors improves, we will observe $\mathcal{O}(100)$s of transient GW events per year. The current methods used to estimate their…

Instrumentation and Methods for Astrophysics · Physics 2022-01-21 Hunter Gabbard , Chris Messenger , Ik Siong Heng , Francesco Tonolini , Roderick Murray-Smith

We present a unified picture to explain the spectral states of BH binaries based on the two-flow model. In our view, the central regions have a multi-flow configuration consisting in (1) an outer standard accretion disc (SAD) down to a…

Astrophysics · Physics 2008-11-26 P. O. Petrucci , J. Ferreira , C. Cabanac , G. Henri , G. Pelletier

Variational autoencoders (VAEs) are popular likelihood-based generative models which can be efficiently trained by maximizing an Evidence Lower Bound (ELBO). There has been much progress in improving the expressiveness of the variational…

Machine Learning · Statistics 2023-08-29 Marcel Hirt , Vasileios Kreouzis , Petros Dellaportas

Structural equation models are commonly used to capture the relationship between sets of observed and unobservable variables. Traditionally these models are fitted using frequentist approaches but recently researchers and practitioners have…

Methodology · Statistics 2023-02-22 Khue-Dung Dang , Luca Maestrini

We introduce the use of autoregressive normalizing flows for rapid likelihood-free inference of binary black hole system parameters from gravitational-wave data with deep neural networks. A normalizing flow is an invertible mapping on a…

Instrumentation and Methods for Astrophysics · Physics 2020-11-25 Stephen R. Green , Christine Simpson , Jonathan Gair

Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some scenarios this is infeasible and alternative methods are needed. Simulation-based inference…

Machine Learning · Computer Science 2025-12-10 Linnea M Wolniewicz , Peter Sadowski , Claudio Corti

We report on a new general relativistic computational model enhancing, in various respects, the capability of presently available tools for fitting spectra of X-ray sources. The new model is intended for spectral analysis of black-hole…

Astrophysics · Physics 2011-02-22 M. Dovciak , V. Karas , A. Martocchia , G. Matt , T. Yaqoob

Recently proposed normalizing flow models such as Glow have been shown to be able to generate high quality, high dimensional images with relatively fast sampling speed. Due to their inherently restrictive architecture, however, it is…

Machine Learning · Computer Science 2020-04-14 Rogan Morrow , Wei-Chen Chiu

In this paper we use an RXTE library of spectral models from 10 black-hole and 9 pulsar X-ray binaries, as well as model spectra available in the literature from 13 extra-galactic Ultra-luminous X-ray sources (ULXs). We compute average…

High Energy Astrophysical Phenomena · Physics 2022-04-06 K. Anastasopoulou , A. Zezas , J. F. Steiner , P. Reig

Eclipsing binaries provide one of the most direct mechanisms for measuring stellar properties such as mass and radius, but historically, determining these properties has been non-trivial and computationally prohibitive. As such, only a…

X-ray binaries are known to exhibit different spectral states which are often associated with different black hole accretion modes. The exact geometry and properties of these accretion modes is still uncertain. Recent IXPE measurements of…

High Energy Astrophysical Phenomena · Physics 2024-04-05 Monika Moscibrodzka

In this chapter, we give an overview of our current understanding of the physics of accreting massive black hole binaries (MBHBs), with a special focus on the latest developments in numerical simulations and General-Relativistic…

High Energy Astrophysical Phenomena · Physics 2024-05-24 Eduardo M. Gutiérrez , Luciano Combi , Geoffrey Ryan

Parameter estimation of binary-black-hole merger events in gravitational-wave data relies on matched-filtering techniques, which, in turn, depend on accurate model waveforms. Here we characterize the systematic biases introduced in…

General Relativity and Quantum Cosmology · Physics 2013-05-08 Tyson B. Littenberg , John G. Baker , Alessandra Buonanno , Bernard J. Kelly