Related papers: Exoplanet Detection Using Machine Learning Models …
While previous works have shown that machine learning (ML) can improve the prediction accuracy of coarse-grid climate models, these ML-augmented methods are more vulnerable to irregular inputs than the traditional physics-based models they…
Despite their successes in the field of self-learning AI, Convolutional Neural Networks (CNNs) suffer from having too many trainable parameters, impacting computational performance. Several approaches have been proposed to reduce the number…
Direct imaging of exoplanets is particularly challenging due to the high contrast between the planet and the star luminosities, and their small angular separation. In addition to tailored instrumental facilities implementing adaptive optics…
Spectral retrieval has long been a powerful tool for interpreting planetary remote sensing observations. Flexible, parameterised, agnostic models are coupled with inversion algorithms in order to infer atmospheric properties directly from…
Stars and their associated planets originate from the same cloud of gas and dust, making a star's elemental composition a valuable indicator for indirectly studying planetary compositions. While the connection between a star's iron (Fe)…
Future space telescopes may be able to directly image $\sim$10 - 100 planets with sizes and orbits consistent with habitable surface conditions ("exo-Earth candidates" or EECs), but observers will face difficulty in distinguishing these…
Spectral retrieval techniques are currently our best tool to interpret the observed exoplanet atmospheric data. Said techniques retrieve the optimal atmospheric components and parameters by identifying the best fit to an observed…
Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratio of exoplanet observations require a Bayesian approach to determine posterior probability distributions of each…
Large-scale photometric surveys are revolutionizing astronomy by delivering unprecedented amounts of data. The rich data sets from missions such as the NASA Kepler and TESS satellites, and the upcoming ESA PLATO mission, are a treasure…
This chapter reviews various methods of detecting planetary companions to stars from an observational perspective, focusing on radial velocities, astrometry, direct imaging, transits, and gravitational microlensing. For each method, this…
With the rise of electronic data, particularly Earth observation data, data-based geospatial modelling using machine learning (ML) has gained popularity in environmental research. Accurate geospatial predictions are vital for domain…
The physical characterization of exoplanets will require to take spectra at several orbital positions. For that purpose, a direct imaging capability is necessary. Direct imaging requires an efficient stellar suppression mechanism,…
We focus on the automated classification of eclipsing binary stars using deep learning methods to handle the vast data generated by large-scale photometric sky surveys. These surveys produce extensive datasets that are impractical for…
We summarize the status of a computer simulator for microlens planet surveys. The simulator generates synthetic light curves of microlensing events observed with specified networks of telescopes over specified periods of time. Particular…
In this work, six convolutional neural networks (CNNs) have been trained based on %different feature images and arrays from the database including 15,638 superflare candidates on solar-type stars, which are collected from the three-years…
Rare extragalactic objects can carry substantial information about the past, present, and future universe. Given the size of astronomical databases in the information era it can be assumed that very many outlier galaxies are included in…
Observing extrasolar planetary transits is one of the only ways that we may infer the masses and radii of planets outside the Solar System. As such, the detections made by photometric transit surveys are one of the only foreseeable ways…
Multi-planet system architectures are frequently used to constrain possible formation and evolutionary pathways of observed exoplanets. Therefore, understanding the predictive and descriptive power of empirical models of these systems is…
Exoplanets can be detected with various observational techniques. Among them, radial velocity (RV) has the key advantages of revealing the architecture of planetary systems and measuring planetary mass and orbital eccentricities. RV…
We propose a new parametrization of the impact parameter u0 and impact angle {\alpha} for microlensing systems composed by an Earth-like Exoplanet around a Solar mass Star at 1 AU. We present the caustic topology of such system, as well as…