Related papers: Exoplanet Cartography using Convolutional Neural N…
We develop a new retrieval scheme for obtaining two-dimensional surface maps of exoplanets from scattered light curves. In our scheme, the combination of the L1-norm and Total Squared Variation, which is one of the techniques used in sparse…
With the ever-growing number of exoplanets detected, the issue of characterization is becoming more and more relevant. Direct imaging is certainly the most efficient but the most challenging tool to probe the atmosphere of exoplanets and…
The next generation of ground and space-based telescopes will image habitable planets around nearby stars. A growing literature describes how to characterize such planets with spectroscopy, but less consideration has been given to the…
It is the most appropriate time to characterize the Earth-like exoplanets in order to detect biosignature beyond the Earth because such exoplanets will be the prime targets of big-budget missions like JWST, Roman Space Telescope, HabEx,…
We have surveyed all conventional methods proposed or conceivable for obtaining resolved images of an Earth-like exoplanet. Generating a 10 x 10 pixel map of a 1 R_E world at 10 pc demands ~0.85 uas angular resolution and photon-collection…
The observed sub-structures, like annular gaps, in dust emissions from protoplanetary disk, are often interpreted as signatures of embedded planets. Fitting a model of planetary gaps to these observed features using customized simulations…
Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…
This paper presents a data processing algorithm with machine learning for polarization extraction and event selection applied to photoelectron track images taken with X-ray polarimeters. The method uses a convolutional neural network (CNN)…
Future direct-imaging exoplanet missions such as WFIRST/AFTA, Exo-C, and Exo-S will measure the reflectivity of exoplanets at visible wavelengths. The exoplanets to be observed will be located further away from their parent stars than is…
It is expected that the next generation of high-contrast imaging instruments will deliver the first unresolved image of an extrasolar planet. The emitted thermal infrared light from the planet should show no phase effect assuming the planet…
The discovery of many Earth-like planets has renewed interest in whether life and technological civilizations exist elsewhere. The Search for Extraterrestrial Intelligence (SETI) seeks evidence for technological civilizations via…
The polarization state of starlight reflected by a planetary atmosphere uniquely reveals coverage, particle size, and composition of aerosols as well as changing cloud patterns. It is not possible to obtain a comparable level of detailed…
Direct detection, also known as direct imaging, is a method for discovering and characterizing the atmospheres of planets at intermediate and wide separations. It is the only means of obtaining spectra of non-transiting exoplanets.…
Habitable planets are often defined as terrestrial worlds capable of maintaining surface liquid water. As a result, atmospheric water vapor can be a critical indicator of habitability. Thus, habitability-themed exoplanet investigations…
We investigate the possibility of exoplanet detection orbiting source stars in microlensing events through WFIRST observations. We perform a Monto Carlo simulation on the detection rate of exoplanets via microlensing, assuming that each…
The characterization of an exoplanet's interior is an inverse problem, which requires statistical methods such as Bayesian inference in order to be solved. Current methods employ Markov Chain Monte Carlo (MCMC) sampling to infer the…
The probability of the detection of Earth-like exoplanets may increase in the near future after the launch of the space missions using the transit photometry as observation method. By using this technique only the semi-major axis of the…
It has recently been demonstrated that deep learning has significant potential to automate parts of the exoplanet detection pipeline using light curve data from satellites such as Kepler \cite{borucki2010kepler} \cite{koch2010kepler} and…
Direct imaging of exoplanets presents a formidable technical challenge owing to the small angular separation and high contrast between exoplanets and their host stars. High Dispersion Coronagraphy (HDC) is a pathway to achieve unprecedented…
Here we introduce the RobERt (Robotic Exoplanet Recognition) algorithm for the classification of exoplanetary emission spectra. Spectral retrievals of exoplanetary atmospheres frequently requires the preselection of molecular/atomic…