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Exoplanet detection opens the door to the discovery of new habitable worlds and helps us understand how planets were formed. With the objective of finding earth-like habitable planets, NASA launched Kepler space telescope and its follow up…
General purpose Search Engines (SEs) crawl all domains (e.g., Sports, News, Entertainment) of the Web, but sometimes the informational need of a query is restricted to a particular domain (e.g., Medical). We leverage the work of SEs as part…
We are at a unique timeline in the history of human evolution where we may be able to discover earth-like planets around stars outside our solar system where conditions can support life or even find evidence of life on those planets. With…
Kepler, K2, TESS, and similar time-domain photometric projects, while designed with exoplanet detection in mind, are also well-suited projects for searches for large artificial structures orbiting other stars in the Galaxy. An effort to…
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…
We present a catalog of cool dwarf targets ($V-J>2.7$, $T_{\rm eff} \lesssim 4000 K$) and their stellar properties for the upcoming Transiting Exoplanet Survey Satellite (TESS), for the purpose of determining which cool dwarfs should be…
The Transiting Exoplanet Survey Satellite (TESS) is a NASA Astrophysics Explorer mission. Following its scheduled launch in 2017, TESS will focus on detecting exoplanets around the nearest and brightest stars in the sky, for which detailed…
Transfer learning is an important approach for addressing the challenges posed by limited data availability in various applications. It accomplishes this by transferring knowledge from well-established source domains to a less familiar…
The large amounts of astrophysical data being provided by existing and future instrumentation require efficient and fast analysis tools. Transfer learning is a new technique promising higher accuracy in the derived data products, with…
Up to date planet ephemerides are becoming increasingly important as exoplanet science moves from detecting exoplanets to characterising their architectures and atmospheres in depth. In this work ephemerides are updated for 22 Kepler…
Exoplanetary science heavily relies on transit depth ($D$) measurements. Yet, as instrumental precision increases, the uncertainty on $D$ appears to increasingly drift from expectations driven solely by photon-noise. Here we characterize…
Driven largely by multiple ground-based radial-velocity (RV) surveys and photometric space missions such as Kepler and K2, the discovery of new exoplanets has increased rapidly since the early 2000s. However, due to a target selection bias…
The upcoming TESS mission will detect thousands of candidate transiting exoplanets. Those candidates require extensive follow-up observations to distinguish genuine planets from false positives, and to resolve the physical properties of the…
The Transiting Exoplanet Survey Satellite (TESS) will perform a two-year survey of nearly the entire sky, with the main goal of detecting exoplanets smaller than Neptune around bright and nearby stars. There do not appear to be any…
Due to the efforts by numerous ground-based surveys and NASA's Kepler and TESS, there will be hundreds, if not thousands, of transiting exoplanets ideal for atmospheric characterization via spectroscopy with large platforms such as JWST and…
The high-precision measurements of exoplanet transit light curves that are now available contain information about the planet properties, their orbital parameters, and stellar limb darkening (LD). Recent 3D magneto-hydrodynamical (MHD)…
We present a novel approach for classifying stars as binary or exoplanet using deep learning techniques. Our method utilizes feature extraction, wavelet transformation, and a neural network on the light curves of stars to achieve…
The determination of exoplanet properties and occurrence rates using Kepler data critically depends on our knowledge of the fundamental properties (such as temperature, radius and mass) of the observed stars. We present revised stellar…
The NASA Transiting Exoplanet Survey Satellite (TESS) is observing tens of millions of stars with time spans ranging from $\sim$ 27 days to about 1 year of continuous observations. This vast amount of data contains a wealth of information…
This study introduces an approach to detecting exocomet transits in the dataset of the Transiting Exoplanet Survey Satellite (TESS), specifically within its Sector 1. Given the limited number of exocomet transits detected in the observed…