Related papers: ExoReL$^\Re$: A Bayesian Inverse Retrieval Framewo…
We develop an inversion technique of annual scattered light curves to sketch a two-dimensional albedo map of exoplanets in face-on orbits. As a test-bed for future observations of extrasolar terrestrial planets, we apply this mapping…
Tau-REx (Tau Retrieval of Exoplanets) is a novel, fully Bayesian atmospheric retrieval code custom built for extrasolar atmospheres. In Waldmann et al. (2015) the transmission spectroscopic case was introduced, here we present the emission…
Thanks to the advances in modern instrumentation we have learned about many exoplanets that span a wide range of masses and composition. Studying their atmospheres provides insight into planetary origin, evolution, dynamics, and…
High-contrast imaging for the detection and characterization of exoplanets relies on the instrument's capability to block out the light of the host star. Some current post-processing methods for calibrating out the residual speckles use…
In this paper, we present YunMa, an exoplanet cloud simulation and retrieval package, which enables the study of cloud microphysics and radiative properties in exoplanetary atmospheres. YunMa simulates the vertical distribution and sizes of…
Exoplanet atmospheric retrieval is a computational technique widely used to infer properties of planetary atmospheres from remote spectroscopic observations. Retrieval codes typically employ Bayesian sampling algorithms or machine learning…
Future space telescopes will directly image extrasolar planets at visible wavelengths. Time-resolved reflected light from an exoplanet encodes information about atmospheric and surface inhomogeneities. Previous research has shown that the…
Spectra of exoplanet atmospheres provide us the opportunity to improve our understanding of these objects just as remote sensing in our own solar system has increased our understanding of the solar system bodies. The challenge is to…
We propose a method for observing transiting exoplanets with near-infrared high-resolution spectrometers. We aim to create a robust data analysis method for recovering atmospheric transmission spectra from transiting exoplanets over a wide…
We have investigated the information content in reflected-starlight spectra of exoplanets. We specify our analysis to Barnard's Star b candidate super-Earth, for which we assume a radius 0.6 times that of Neptune, an atmosphere dominated by…
We study the influence of low-level water and high-level ice clouds on low-resolution reflection spectra and planetary albedos of Earth-like planets orbiting different types of stars in both the visible and near infrared wavelength range.…
Exoplanetary atmospheric retrieval refers to the inference of atmospheric properties of an exoplanet given an observed spectrum. The atmospheric properties include the chemical compositions, temperature profiles, clouds/hazes, and energy…
Retrieval methods are a powerful analysis technique for modelling exoplanetary atmospheres by estimating the bulk physical and chemical properties that combine in a forward model to best-fit an observed spectrum, and they are increasingly…
Over the last several years, spectroscopic observations of transiting exoplanets have begun to uncover information about their atmospheres, including atmospheric composition and indications of the presence of clouds and hazes. Spectral…
The characterization of planetary atmospheres is a daunting task, pushing current observing facilities to their limits. The next generation of high-resolution spectrographs mounted on large telescopes -- such as ESPRESSO@VLT and HIRES@ELT…
Hi-resolution spectroscopy (R > 25,000) has recently emerged as one of the leading methods to detect atomic and molecular species in the atmospheres of exoplanets. However, it has so far been lacking in a robust method to extract…
EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian Inference, we can test…
Techniques to retrieve the atmospheric properties of exoplanets via direct observation of their reflected light have often been limited in scope due to computational constraints imposed by the forward-model calculations. We have developed a…
Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using machine learning algorithms for atmospheric…
We aim to interpret future photometric and spectral measurements from these instruments, in terms of physical parameters of the planets, with an atmospheric model using a minimal number of assumptions and parameters. We developed Exoplanet…