ﻻ يوجد ملخص باللغة العربية
PHOEBE 2 is a Python package for modeling the observables of eclipsing star systems, but until now has focused entirely on the forward-model -- that is, generating a synthetic model given fixed values of a large number of parameters describing the system and the observations. The inverse problem, obtaining orbital and stellar parameters given observational data, is more complicated and computationally expensive as it requires generating a large set of forward-models to determine which set of parameters and uncertainties best represent the available observational data. The process of determining the best solution and also of obtaining reliable and robust uncertainties on those parameters often requires the use of multiple algorithms, including both optimizers and samplers. Furthermore, the forward-model of PHOEBE has been designed to be as physically robust as possible, but is computationally expensive compared to other codes. It is useful, therefore, to use whichever code is most efficient given the reasonable assumptions for a specific system, but learning the intricacies of multiple codes presents a barrier to doing this in practice. Here we present the 2.3 release of PHOEBE (publicly available from http://phoebe-project.org) which introduces a general framework for defining and handling distributions on parameters, and utilizing multiple different estimation, optimization, and sampling algorithms. The presented framework supports multiple forward-models, including the robust model built into PHOEBE itself.
Hubble Space Telescope (HST) Fine Guidance Sensor (FGS) trigonometric parallax observations were obtained to directly determine distances to five nearby M-dwarf / M-dwarf eclipsing binary systems. These systems are intrinsically interesting as benchm
The Kepler Mission has provided unprecedented, nearly continuous photometric data of $sim$200,000 objects in the $sim$105 deg$^{2}$ field of view from the beginning of science operations in May of 2009 until the loss of the second reaction wheel in M
We are entering an era of unprecedented quantities of data from current and planned survey telescopes. To maximise the potential of such surveys, automated data analysis techniques are required. Here we implement a new methodology for variable star c
We highlight the importance of eclipsing double-line binaries in our understanding on star formation and evolution. We review the recent discoveries of low-mass and sub-stellar eclipsing binaries belonging to star-forming regions, open clusters, and
The goal of this work is to conduct a photometric study of eclipsing binaries in M31. We apply a modified box-fitting algorithm to search for eclipsing binary candidates and determine their period. We classify these candidates into detached, semi-det