Related papers: ExoData: A python package to handle large exoplane…
The astronomy, astroparticle and particle physics communities are brought together through the ESCAPE (European Science Cluster of Astronomy and Particle Physics ESFRI research infrastructures) project to create a cluster focused on common…
Time series data of celestial objects are commonly used to study valuable and unexpected objects such as extrasolar planets and supernova in time domain astronomy. Due to the rapid growth of data volume, traditional manual methods are…
Context: Exoplanets have now been proven to be very common. The number of its detections continues to grow following the development of better instruments and missions. One key step for the understanding of these worlds is their…
Observations of exoplanetary systems provide clues about the intrinsic distribution of planetary systems, their architectures, and how they formed. We develop a forward modelling framework for generating populations of planetary systems and…
PyUnfold is a Python package for incorporating imperfections of the measurement process into a data analysis pipeline. In an ideal world, we would have access to the perfect detector: an apparatus that makes no error in measuring a desired…
Over 300 extrasolar planets (exoplanets) have been detected orbiting nearby stars. We now hope to conduct a census of all planets around nearby stars and to characterize their atmospheres and surfaces with spectroscopy. Rocky planets within…
We present the first stable release of Halotools (v0.2), a community-driven Python package designed to build and test models of the galaxy-halo connection. Halotools provides a modular platform for creating mock universes of galaxies…
Understanding a planet's atmosphere is a necessary condition for understanding not only the planet itself, but also its formation, structure, evolution, and habitability, This puts a premium on obtaining spectra, and developing credible…
At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parametrising such models to conform to the multitude of available experimental constraints is a global nonlinear optimisation…
A brief review is given of a university outreach programme by a commercial organisation, which uses the Kepler exoplanet data. Key insights derived from this research are presented, along with discussion of the benefi ts and challenges of…
The search for exoplanets is an active field in astronomy, with direct imaging as one of the most challenging methods due to faint exoplanet signals buried within stronger residual starlight. Successful detection requires advanced image…
I present ExoIris, a user-friendly Python package for exoplanet transmission and emission spectroscopy. Unlike existing tools, ExoIris models two-dimensional spectrophotometric transit time series directly and supports the joint analysis of…
High contrast direct imaging of exoplanets can provide many important observables, including measurements of the orbit, spectra that probe the lower layers of the atmosphere, and phase variations of the planet, but cannot directly measure…
Data gridding is a common task in astronomy and many other science disciplines. It refers to the resampling of irregularly sampled data to a regular grid. We present cygrid, a library module for the general purpose programming language…
The exploration of planetary bodies in our Solar system and beyond relies on the processing and interpretation of large, spatio-temporally inconsistent, and heterogeneous datasets. Recent advances in machine learning (ML) provide…
The holy grail of exoplanet searches is an exo-Earth, an Earth mass planet in the habitable zone around a nearby star. Mass is the most important parameter of a planet and can only be measured by observing the motion of the star around the…
A simple metric can be used to determine whether a planet or exoplanet can clear its orbital zone during a characteristic time scale, such as the lifetime of the host star on the main sequence. This criterion requires only estimates of star…
AOtools is a Python package which is open-source and aimed at providing tools for adaptive optics users and researchers. We present version 1.0 which contains tools for adaptive optics processing, including analysing data in the pupil…
X-ray observations of star-planet systems are important to grow our understanding of exoplanets; these observation allow for studies of photoevaporation of the exoplanetary atmosphere, and in some cases even estimations of the size of the…
We explore the efficacy of machine learning (ML) in characterizing exoplanets into different classes. The source of the data used in this work is University of Puerto Rico's Planetary Habitability Laboratory's Exoplanets Catalog (PHL-EC).…