相关论文: Physics of Eclipsing Binaries. V. General Framewor…

The formalism of Bayesian model selection provides a very elegant way of ranking different physical models in terms of how compatible they are with a given set of observed data. However, its practical application is often hampered by the…

Microwave Imaging is an essential technique for reconstructing the electrical properties of an inaccessible medium. Many approaches have been proposed employing algorithms to solve the Electromagnetic Inverse Scattering Problem associated…

Quantifying and reducing uncertainty in Earth system model parameterizations is essential to improving their reliability in decision-making. Forward uncertainty propagation is used to derive parameter sensitivity but requires physically…

Extracting additional information from old or incomplete fireball datasets remains a challenge. To address missing point-by-point observations, we introduce a method for estimating atmospheric flight parameters of meteoroids using…

We present the physical parameters of an eclipsing binary system EPIC 211982753 derived through photometric and radial velocity data modeling. We make use of photometric data from NASA's K2 mission, ASAS-SN, and 1.3-m Devasthal Fast Optical…

The precise measurement of the masses and radii of stars in eclipsing binary systems provides a window into uncertain processes in stellar evolution, especially mixing at convective boundaries. Recently, these data have been used to…

The evolution of binary stellar systems involves a wide range of physical processes, many of which are not yet well understood. We aim to build a general-purpose algorithm based on inverse population synthesis techniques, able to…

Eclipsing binary systems with pulsating components offer a unique possibility to accurately measure the most important parameters of pulsating stars, to study their evolution, and to test the pulsation theory. I will show what we can learn…

ESCAPE is a free python package and framework for creating applications for simulating and fitting of X-ray and neutron scattering data with current support for specular reflectivity, polarized neutron reflectometry, high resolution X-ray…

In September 2024, eclipsing binary star practitioners gathered in Litomysl, Czech Republic, the birth town of Zdenek Kopal, one of the most celebrated pioneers of our field, to discuss the latest developments and state-of-the-art. I was…

We present a computational framework for estimating the uncertainty in the numerical solution of linearized infinite-dimensional statistical inverse problems. We adopt the Bayesian inference formulation: given observational data and their…

We introduce a new multivariate statistical problem that we refer to as the Ensemble Inverse Problem (EIP). The aim of EIP is to invert for an ensemble that is distributed according to the pushforward of a prior under a forward process. In…

Context: Multiple stellar systems are unique laboratories for astrophysics. Analysis of their orbital dynamics may reveal invaluable information about the physical properties of the participating stars. Unfortunately, there are only a few…

The Projection on Proper elements (PoPe) is a novel method of code control dedicated to 1) checking the correct implementation of models, 2) determining the convergence of numerical methods and 3) characterizing the residual errors of any…

We present a new, fast, and easy to use tool for modelling light and radial velocity curves of close eclipsing binaries with built-in methods for solving an inverse problem. The main goal of ELISa (Eclipsing binary Learning and Interactive…

In this work, we adopt a general framework based on the Gibbs posterior to update belief distributions for inverse problems governed by partial differential equations (PDEs). The Gibbs posterior formulation is a generalization of standard…

The measurement of spin-precession and orbital eccentricity in gravitational-wave (GW) signals is a key priority in GW astronomy, as these effects not only provide insights into the astrophysical formation and evolution of compact binaries…

Consider a problem where a set of feasible observations are provided by an expert and a cost function is defined that characterizes which of the observations dominate the others and are hence, preferred. Our goal is to find a set of linear…

The inverse problem methodology is a commonly-used framework in the sciences for parameter estimation and inference. It is typically performed by fitting a mathematical model to noisy experimental data. There are two significant sources of…

This study presents a multi-task machine learning framework for simultaneous morphology classification and physical parameter estimation of eclipsing binaries using photometric light curves. We train Random Forest and XGBoost ensemble…