Related papers: Estimating Exoplanet Mass using Machine Learning o…
Various methods have been proposed to search for extrasolar planets. Compared to the other methods, microlensing has unique applicabilities to the detections of Earth-mass and free-floating planets. However, the microlensing method is…
We introduce a new method of searching for and characterizing extra-solar planets. We show that by monitoring the center-of-light motion of microlensing alerts using the next generation of high precision astrometric instruments the…
Numerical N-body simulations are commonly used to explore stability regions around exoplanets, offering insights into the possible existence of satellites and ring systems. This study aims to utilize Machine Learning (ML) techniques to…
We present the latest velocities for 10 multi-planet systems, including a re-analysis of archival Keck and Lick data, resulting in improved velocities that supersede our previously published measurements. We derive updated orbital fits for…
Atmospheric characterization of Earth-like exoplanets through reflected light spectroscopy is a key goal for upcoming direct imaging missions. A critical challenge in this endeavor is the accurate determination of planetary mass, which may…
Features in the distribution of exoplanet parameters by period demonstrate that the distribution of planet parameters is rich with information that can provide essential guidance to understanding planet histories. Structure has been found…
The evolution of space technology in recent years, fueled by advancements in computing such as Artificial Intelligence (AI) and machine learning (ML), has profoundly transformed our capacity to explore the cosmos. Missions like the James…
With the development of ever-improving telescopes capable of observing exoplanet atmospheres in greater detail and number, there is a growing demand for enhanced 3D climate models to support and help interpret observational data from space…
Retrieving the physical parameters from spectroscopic observations of exoplanets is key to understanding their atmospheric properties. Exoplanetary atmospheric retrievals are usually based on approximate Bayesian inference and rely on…
It is suggested that the distribution of orbital eccentricities for extrasolar planets is well-described by the Beta distribution. Several properties of the Beta distribution make it a powerful tool for this purpose. For example, the Beta…
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…
The gravitational influence of a planet on a nearby disk provides a powerful tool for detecting and studying extrasolar planetary systems. Here we demonstrate that gaps can be opened in dynamically cold debris disks at the mean-motion…
Understanding planet formation requires robust population studies, which are designed to reveal trends in planet properties. In this work, we aim to determine if different methods for selecting populations of exoplanets for atmospheric…
In the first three years of operation the Kepler mission found 3,697 planet candidates from a set of 18,406 transit-like features detected on over 200,000 distinct stars. Vetting candidate signals manually by inspecting light curves and…
Planets can affect debris disk structure by creating gaps, sharp edges, warps, and other potentially observable signatures. However, there is currently no simple way for observers to deduce a disk-shepherding planet's properties from the…
Aims: We predict the exoplanet yield of a space-based mid-infrared nulling interferometer using Monte Carlo simulations. We quantify the number and properties of detectable exoplanets and identify those target stars that have the highest or…
We use both the conventional and more recently developed methods of cluster analysis to study the data of extra-solar planets. Using the data set with planetary mass M, orbital period P, and orbital eccentricity e, we investigate the…
Deep learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly non-linear relations and solve interesting problems in a data-driven manner. Several works have attempted to…
Computing the mass of planetary envelopes and the critical mass beyond which planets accrete gas in a runaway fashion is important when studying planet formation, in particular for planets up to the Neptune mass range. This computation…
We present a novel, model-independent framework for studying the architecture of an exoplanetary system at the system level. This framework allows us to characterise, quantify, and classify the architecture of an individual planetary…