Related papers: Parameter Inference of Black Hole Images using Dee…
The images of supermassive black holes captured by the Event Horizon Telescope (EHT) collaboration have allowed us to have access to the physical processes that occur in the vicinity of the event horizons of these objects. This has enabled…
The Event Horizon Telescope (EHT) aims to spatially resolve the silhouette (or shadow) of the supermassive black holes in the Galactic Centre (Sgr A$^\star$) and M87. The primary scientific objectives are to test general relativity in the…
Black holes are among the most compelling predictions of general relativity (GR) and are now strongly supported by observations from gravitational-wave detectors and the Event Horizon Telescope (EHT). While standard black hole solutions…
Photon rings near the edge of a black hole shadow is supposed to be a unique tool to validate general relativity and provide reliable measurements of principal black hole parameters: spin and mass. Such measurements are possible though only…
The emergent behavior of quantum materials is governed by their electronic structure, which can be experimentally probed by photoemission spectroscopy techniques that generate a four-dimensional dataset of energy and momentum. However, the…
Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because…
The Event Horizon Telescope (EHT) has produced images of two supermassive black holes, Messier~87* (M 87*) and Sagittarius~A* (Sgr A*). The EHT collaboration used these images to indirectly constrain black hole parameters by calibrating…
Interpreting horizon-scale black hole images currently relies on computationally intensive General Relativistic Ray Tracing (GRRT) simulations, which pose a significant bottleneck for rapid parameter exploration and high-precision tests of…
In this paper, we introduce a novel data augmentation methodology based on Conditional Progressive Generative Adversarial Networks (CPGAN) to generate diverse black hole (BH) images, accounting for variations in spin and electron…
Systems of two black holes with unbound orbits can produce a diverse array of gravitational wave signals with rich morphology. This parameter space encompasses both hyperbolic orbit scattering events and dynamical captures, including…
General relativity predicts that images of optically thin accretion flows around black holes should generically have a ``photon ring,'' composed of a series of increasingly sharp subrings that correspond to increasingly strongly lensed…
We show how Event Horizon Telescope (EHT) observations of the supermassive object at the center of M87 can constrain deviations from General Relativity (GR) in a relatively model-independent way. We focus on the class of theories whose…
Deep unrolling is an emerging deep learning-based image reconstruction methodology that bridges the gap between model-based and purely deep learning-based image reconstruction methods. Although deep unrolling methods achieve…
Deep learning algorithms have recently shown to be a successful tool in estimating parameters of statistical models for which simulation is easy, but likelihood computation is challenging. But the success of these approaches depends on…
Accurately inferring black hole spin is crucial for understanding black hole dynamics and their astrophysical environments. In this work, we outline a geometric method for spin estimation by using the interferometric shape of the first…
The recent advent of the Event Horizon Telescope (EHT) has made direct imaging of supermassive black holes a reality. Simulated images of black holes produced via general relativistic ray tracing and radiative transfer provide a key…
We propose a simple, analytic dual-cone accretion model for horizon scale images of the cores of Low-Luminosity Active Galactic Nuclei (LLAGN), including those observed by the Event Horizon Telescope (EHT). Our underlying model is of…
Searching for violations of the no-hair theorem (NHT) is a powerful way to test gravity, and more generally fundamental physics, particularly with regards to the existence of additional scalar fields. The first observation of a black hole…
Deep Learning (DL) has been successfully applied to a wide range of application domains, including safety-critical ones. Several DL testing approaches have been recently proposed in the literature but none of them aims to assess how…
The capability of the Event Horizon Telescope (EHT) to image the nearest supermassive black hole candidates at horizon-scale resolutions offers a novel means to study gravity in its strongest regimes and to test different models for these…